Next up, a review published in Nature of the latest book by Douglas Hofstadter. Interesting, but God it’s long.
_______________________________________________________________
Surfaces and Essences
Douglas Hofstadter & Emmanuel Sander
Basic Books, 2013
608 pages
$35.00
ISBN 978-0-465-01847-5
I finished this review and stored the file in the 'Nature' folder on my desktop, then emailed it to the editor. Or did I? A file, after all, was once a sheaf of papers, and a folder a cardboard sleeve for holding them. A desktop was wooden, and mail needed a stamp (no, it needed a little piece of adhesive paper). But all I did was use an interfacing device (named for the most superficial resemblance to a rodent) to rearrange the settings of some microprocessor circuits. To see that almost everything we say and do refers by analogy to other things we or others have once said or done – which is the main point of Surfaces and Essences – there is no better illustration than the way we have constructed our computer software as a conceptual and visual simulacrum of the offices our grandparents knew.
On the one hand this is kind of obvious. Why (science fiction writers take note) would we invent new categories and labels for things when we can aid comprehension by borrowing old ones, even if the physical resemblance is negligible? What cognitive scientists Douglas Hofstadter Hofstadter and Emmanuel Sander set out to show, however, is that this sort of elision is not merely a convenience: all our thinking depends on it, from the half-truths of everyday speech ("that always happens to me too!") to the most abstruse of mathematical reasoning. I was convinced, and the ramifications are often thought-provoking. But when you have had authors telling you the same thing again and again for 500 pages, perhaps you’ll believe it whether it's true or not. I’ll come back to that.
Hofstadter is famous for his earlier, Pulitzer-prize-winning treatise on how we think, Gödel, Escher, Bach (1979). Fans of that dazzling performance might find this book surprisingly sober, but it is also lucid and, page for page, a delight to read. Whether there is any conceptual continuity between that and this vision of how we think is debatable, except perhaps that GEB’s delight in puns here becomes an assertion that pretty much all our cognition depends on punning elevated to analogy.
The claim that drawing parallels between one thing and another central in our thinking seems obvious in art: analogies are the bread and butter (there we go again) of the visual, literary and theatrical arts. (Of these, the authors seem curiously unconcerned about anything except poetry.) Yet Hofstadter and Sander are really inverting that usual picture: it is precisely because the brain seems to be an analogy machine that art is possible and meaningful.
They focus most on the use of analogy in language. Moving steadily from words to phrases and narratives, they show just how deeply embedded is our tendency to generalize, compare, categorize, and forge links. Individual examples seem trivial until you realise their ubiquity: tables have legs, melodies are hauting, time is discussed in spatial terms, and idioms are invariably analogical, if you get my drift. Thus the lexical precision on which dictionaries seem to insist is illusory – words are always standing in for other words, their boundaries malleable. This flexibility extends to our actions: we see that a spoon can serve as a knife when no knife is available. (Indeed, the spoon then becomes a knife – objects may be fixed, but their labels aren’t.)
These arguments can be carried too far. Is to extrapolate to make an analogy (I expect the future to be like the past)? Is a Freudian slip an analogy, or mere crosstalk of neural circuits? Is convention an analogy (why don’t we write mc2=E?). Can we, in fact, turn any mental process into an analogy, by that very process of analogy? These are not rhetorical questions, for one might at least examine whether the same neural circuitry is involved in each case. But a lack of interest in neuroscientific examination of their idea is another of the book’s odd lacunae.
In fact this intriguing, frustrating book seems to exist almost in an intellectual vacuum. Unless one combs through the bibliography, one could mistakenly imagine that it is the first attempt to explore the notion of analogy and metaphor in linguistics, overlooking the work of Raymond Gibbs, Andrew Ortony, Sam Glucksberg, Esa Itkonen and many others. And one is forced to take an awful lot on trust. Hofstadter and Sander describe, for example, the evolution of the concept of ‘mother’ in the mind of a child as he learns to generalize from experience. It all sounds plausible, but the authors offer no empirical evidence for the developmental pathway they describe.
Neither is there any real explanation of why we think this way. Isn't it perhaps, in part, a way of minimizing the mental resources we need to engage in a situation, to avoid having to start from scratch with every unfamiliar encounter, object or perspective? Is it an adaptive technique for making predictions? Are mirror neurons part of a built-in cognitive apparatus for analogizing ourselves into others’ shoes?
The lack of historical perspective is also a problem – it is as if people always thought like they did now. Analogy was arguably all we once had for navigating experience, for example in the Neoplatonic idea of correspondences: “as above, so below.” This “just as… so…” thinking remains at the root of pseudoscience: the Moon influences the tides, so why not our body fluids? So how do we distinguish between good and bad analogies?
There are gems of insight in here, but again flawed by the authors’ relaxed attitude towards evidence. An analysis of Einstein's thought is splendid, explaining what is missing from conventional accounts of the discoveries of light quanta, relativity and mass-energy equivalence, namely what qualities distinguish Einstein from his peers. These qualities are convincingly shown to be analogical: Einstein was able to take leaps of faith and make connections that postpone rigour and are certainly not self-evidently true. One would usually call this intuition - Einstein's friend and biographer Banesh Hoffmann did just that. But it is shown here to be intuition based on a conviction that different areas of physics were comparable. In other words, his intuition is not left ineffable but is taken apart so that the inner workings – some of them – can be seen. As a result, we see that Einstein's insights were very subtle and not self-evidently true. Analogies, the authors say, left Einstein like J. S. Bach on hearing a theme: "very quickly able to imagine all of its possible consequences." All very fine – but such a detailed account must surely be supported by Einstein’s own words. Almost none are offered; we get only fragments of Hoffmann’s commentary.
Maybe at least some of these questions are merely evidence of the fecundity of the authors’ thesis. But they’d have more excuse for not answering them if they did not fill so much space with endless examples to ram the point home: they never give one when 60 will do, and I’m not exaggerating.
Such things make me wonder whom the book is for. Academic linguists will be irritated by the absence of references to other work. Physical scientists aren’t indulged until page 450. General readers could have been given the basic ideas, with equal conviction, in half the length, and will occasionally get the feeling they have been led along and then dumped. The thesis suggests no obvious mode of further development, no manner of testing and probing. It remains stimulating, but less would certainly have been more.
Monday, April 29, 2013
Happy holidays
Here’s the previous piece for my Under the Radar column on BBC Future – there will be another column up very shortly. Peter Dodds, tells me that he and his colleagues have now created a “hedometer” site at http://www.hedonometer.org that will “provide a real-time measure of happiness that will be useful for many entities including governments at all scales, journalists, analysts, and citizens.” Peter adds that “initially, we'll be showing an interactive happiness time-series for Twitter but we'll be expanding to geography, social networks, etc., as well as other languages and other emotions.” It sounds rather fabulous, and will be free and open to all users when it goes live tomorrow.
________________________________________
Feeling low? Over-worked, anxious, bored with life? A holiday will do your mood the world of good. Really it will: there’s now scientific proof. A team of researchers at the University of Vermont in the United States has found that tweets contain significantly more happy words the further from home they are sent [1].
This is the latest dispatch from an emerging discipline in which social-networking media are mined to gauge people’s moods and opinions. Twitter is one of the most fertile sources of information for this kind of study, partly because the comments are less guarded and self-conscious than responses to questionnaires (the social scientist’s traditional means of sampling opinion) but also because huge amounts of data are available, with automatically searchable content. What’s more, Twitter feeds sometimes come accompanied with useful information such as the tweeter’s profile and location.
Previous studies in “twitteromics” have, for example, monitored the spread of news, the demographics of different languages, and the correlations between obesity and expressions of hunger in particular populations. Since public mood changes such as brewing social unrest will show up on Twitter and other social media, governments, police forces and security organizations are showing an increasing interest in twitteromics, raising questions about the right balance between privacy and security. Meanwhile, potential insights into the emergence and propagation of trends are a gift to company marketing departments.
The new study of the link between happiness and geographical location by Christopher Danforth and colleagues at Vermont takes advantage of the “garden hose” public-access feed for Twitter, which makes freely available a random 10 percent of all messages posted. This provided the researchers with four billion tweets for the year 2011 to analyse.
Since Danforth and colleagues were interested in how the mood expressed in the messages correlated with the location from which they were sent, they sifted through this immense data set to pick out those tweets that were accompanied by the precise latitude and longitude of the sender’s mobile phone – a facility optionally available for tweets, which uses the Global Positioning System (GPS) to locate the message’s origin within a 10m radius. About 1% of the messages included this information, giving a data set of 37 million messages sent by more than 180,000 individuals from all over the planet.
But identifying where the sender is situated doesn’t in itself reveal what the researchers wanted to know. They were interested in how the message content varied with distance from home. How could they know where ‘home’ was?
It turns out that positional information disclosed by our mobile phones reveals this pretty clearly. In 2008 a team of researchers in the US used the locations of mobile phones – recorded by phone companies whenever calls are made – to track the trajectories of 100,000 (anonymized) individuals [2]. They found that, as we might imagine, we tend to return over and over again to certain places, especially our homes and workplaces, and only rarely venture very far from these locations.
In much the same way, Danforth and colleagues could figure out the most common locations for each individual in their survey, along with an associated number describing how widely the person tended to roam from those places. They found that people generally have two such preferred locations, just a short distance apart, which they attributed to the home and workplace.
How, then, do the messages differ when individuals are at home, at work, or further away? To assess the ‘happiness’ of a tweet, the Vermont team has developed what they call a ‘hedonometer’ [3]: an algorithm that searches the text for words implying a positive or enjoyable context (such as ‘new’, ‘great’, ‘coffee’ and ‘lunch’) or a negative one (‘no’, ‘not’, ‘hate’, ‘damn’, ‘bored’). On this basis the hedonometer assigns each message a happiness score.
The authors report that “we see a general decline in the use of negative words as individuals travel further from their expected [home] location”. More precisely, the average happiness score first declines slightly for distances of around 1 km – the kind of distance expected for a short commute to work – and then rises steadily with increasing distances of up to several thousand kilometres. What’s more, individuals with a larger typical ‘roaming radius’ use happy words more often – a result that probably reflects the higher socioeconomic status of such jet-setting types.
So it seems we’re least happy at work and most happy when we are farthest from home. At least, that’s the case for the roughly 15% of American adults who use Twitter, or to be even more cautious, for the English-speaking subset of those who chose to ‘geotag’ their tweets. One key question is whether this sample is representative of the population as a whole – Twitter is less used among older people, for example. It’s also an open question whether ‘happy words’ are a true indicator of one’s state of mind – are you less likely to tweet about your holiday when the weather is awful and the family is fractious? But such quibbles aside, you might want to consider that costly flight to Bermuda or Kathmandu after all.
References
1. M. R. Frank, L. Mitchell, P. S. Dodds & C. M. Danforth, preprint http://www.arxiv.org/abs/1304.1296 (2013).
2. M. C. Gonzalez, C. A. Hidalgo & A. L. Barabasi, Nature 453, 779-782 (2008).
3. P. S. Dodds, K. D. Harris, I. M. Kloumann, C. A. Bliss & C. M. Danforth, PLoS ONE 6(12), e26752 (2011).
________________________________________
Feeling low? Over-worked, anxious, bored with life? A holiday will do your mood the world of good. Really it will: there’s now scientific proof. A team of researchers at the University of Vermont in the United States has found that tweets contain significantly more happy words the further from home they are sent [1].
This is the latest dispatch from an emerging discipline in which social-networking media are mined to gauge people’s moods and opinions. Twitter is one of the most fertile sources of information for this kind of study, partly because the comments are less guarded and self-conscious than responses to questionnaires (the social scientist’s traditional means of sampling opinion) but also because huge amounts of data are available, with automatically searchable content. What’s more, Twitter feeds sometimes come accompanied with useful information such as the tweeter’s profile and location.
Previous studies in “twitteromics” have, for example, monitored the spread of news, the demographics of different languages, and the correlations between obesity and expressions of hunger in particular populations. Since public mood changes such as brewing social unrest will show up on Twitter and other social media, governments, police forces and security organizations are showing an increasing interest in twitteromics, raising questions about the right balance between privacy and security. Meanwhile, potential insights into the emergence and propagation of trends are a gift to company marketing departments.
The new study of the link between happiness and geographical location by Christopher Danforth and colleagues at Vermont takes advantage of the “garden hose” public-access feed for Twitter, which makes freely available a random 10 percent of all messages posted. This provided the researchers with four billion tweets for the year 2011 to analyse.
Since Danforth and colleagues were interested in how the mood expressed in the messages correlated with the location from which they were sent, they sifted through this immense data set to pick out those tweets that were accompanied by the precise latitude and longitude of the sender’s mobile phone – a facility optionally available for tweets, which uses the Global Positioning System (GPS) to locate the message’s origin within a 10m radius. About 1% of the messages included this information, giving a data set of 37 million messages sent by more than 180,000 individuals from all over the planet.
But identifying where the sender is situated doesn’t in itself reveal what the researchers wanted to know. They were interested in how the message content varied with distance from home. How could they know where ‘home’ was?
It turns out that positional information disclosed by our mobile phones reveals this pretty clearly. In 2008 a team of researchers in the US used the locations of mobile phones – recorded by phone companies whenever calls are made – to track the trajectories of 100,000 (anonymized) individuals [2]. They found that, as we might imagine, we tend to return over and over again to certain places, especially our homes and workplaces, and only rarely venture very far from these locations.
In much the same way, Danforth and colleagues could figure out the most common locations for each individual in their survey, along with an associated number describing how widely the person tended to roam from those places. They found that people generally have two such preferred locations, just a short distance apart, which they attributed to the home and workplace.
How, then, do the messages differ when individuals are at home, at work, or further away? To assess the ‘happiness’ of a tweet, the Vermont team has developed what they call a ‘hedonometer’ [3]: an algorithm that searches the text for words implying a positive or enjoyable context (such as ‘new’, ‘great’, ‘coffee’ and ‘lunch’) or a negative one (‘no’, ‘not’, ‘hate’, ‘damn’, ‘bored’). On this basis the hedonometer assigns each message a happiness score.
The authors report that “we see a general decline in the use of negative words as individuals travel further from their expected [home] location”. More precisely, the average happiness score first declines slightly for distances of around 1 km – the kind of distance expected for a short commute to work – and then rises steadily with increasing distances of up to several thousand kilometres. What’s more, individuals with a larger typical ‘roaming radius’ use happy words more often – a result that probably reflects the higher socioeconomic status of such jet-setting types.
So it seems we’re least happy at work and most happy when we are farthest from home. At least, that’s the case for the roughly 15% of American adults who use Twitter, or to be even more cautious, for the English-speaking subset of those who chose to ‘geotag’ their tweets. One key question is whether this sample is representative of the population as a whole – Twitter is less used among older people, for example. It’s also an open question whether ‘happy words’ are a true indicator of one’s state of mind – are you less likely to tweet about your holiday when the weather is awful and the family is fractious? But such quibbles aside, you might want to consider that costly flight to Bermuda or Kathmandu after all.
References
1. M. R. Frank, L. Mitchell, P. S. Dodds & C. M. Danforth, preprint http://www.arxiv.org/abs/1304.1296 (2013).
2. M. C. Gonzalez, C. A. Hidalgo & A. L. Barabasi, Nature 453, 779-782 (2008).
3. P. S. Dodds, K. D. Harris, I. M. Kloumann, C. A. Bliss & C. M. Danforth, PLoS ONE 6(12), e26752 (2011).
Friday, April 26, 2013
Can Google predict the markets?
Here’s another Nature news story. I’ll be interested to see what other media outlets make of it.
____________________________________________________________
Traders reveal their mood in the search terms they use.
Suppose you had a direct line into the minds of stock market traders. Would you be able to predict which investment decisions they will take, and thus anticipate the markets?
A team of researchers in the UK and US now suggests that such a crystal ball might exist, in the form of the search terms recorded and made publicly available by Google Trends. Tobias Preis of the University of Warwick Business School and his colleagues say that their analyses of Google Trends data show “early warning signs” of how the markets will shift – including the financial crash of 2008 [1].
Don’t, however, imagine that this is the way to make a fast buck. It’s one thing to offer a retrospective account of why markets behave as they do – which is what Preis and colleagues have done – and quite another to provide a genuinely predictive tool.
That’s why the work is “interesting but not earth-shattering”, in the view of British economist Paul Ormerod of the consultancy Volterra Partners in London.
Mathematical physicist Didier Sornette of the Swiss Federal Institute of Technology (ETH) in Zürich agrees, pointing out that the predictive power of the strategies the authors deduced from Google Trends data are only slightly better than predictions which assume traders make random decisions. “No investor or hedge-fund would be interested in such a strategy”, he says.
The predictive value of Google Trends has been demonstrated in other areas of social science. Most famously, outbreaks of influenza have been seen emerging in real time by monitoring the numbers of Google searches for terms related to flu prevention and cure [2].
The potential of using such information to study economic behaviour has already been spotted. Preis and coauthor Gene Stanley of Boston University have themselves shown that certain search terms reflect the volume of stock market transactions [3]. Sornette, in collaboration with Japanese economists, has found that the volatility (fluctuations) of financial markets can be correlated with the prevalence of particular topics in business news [4].
But what traders and investors really want is a method not just to assess the current state of markets but to anticipate their future course. In particular, episodes of instability, such as the financial crisis of 2008, are often preceded by periods of concern during which investors avidly seek information to decide whether to buy or sell.
Preis and colleagues figured that such anxieties and moods might be signaled by Google search terms. Just before the onset of the latest crisis, for instance, “debt” might be expected to feature prominently. That’s just what the researchers found.
To test if such correlations could be made predictive, they devised trading strategies in which a decision to buy or sell is linked to the recent prevalence of particular search terms. They simulated how these strategies would have performed between 2004 and 2011 based on real data from the financial markets.
Of the 98 ‘Google Trends’ strategies the researchers explored, that based on “debt” performed best. By 2011 it would have increased the value of a portfolio by more than 300 percent, compared with just 16 percent for a common conventional investment strategy.
Although this sounds impressive, the relevance of a predictive Google search term isn’t always clear. The second-best strategy, for example, was linked to “color”, and the fourth best to “restaurant”.
Even the use of “debt” is not obvious, since its role in the financial crash was apparent only as it happened. “How would they know in advance that they should use ‘debt’?” asks Sornette.
“In retrospect it is always possible to derive what appear to be highly successful trading strategies”, says Ormerod. “But what we want is to be able to do that before the event, not after.”
What’s more, economists acknowledge that any transparently profitable strategy for playing the markets will quickly lead to a change of trader behaviour that cancels it – a principle called Goodhart’s Law, after the British economist Charles Goodhart. “Social systems have the complication that the system may directly react to predictions being made about its behaviour”, coauthor Susannah Moat of University College London agrees.
The researchers suggest, however, that a key outcome of their approach might be to elucidate the psychological mechanisms that guide traders to their decisions, which could be encoded in their information-gathering. “Stock market data themselves tell us little about how traders make decisions”, says Preis.
“We think that the overall pattern we observe may reflect loss aversion”, he adds – the fact that humans are more concerned about losing money than they are about missing an opportunity to gain the same amount.
References
1. Preis, T., Moat, H. S. & Stanley, H. E. Nat. Sci. Rep. 3, 1684 (2013).
2. Ginsberg, J. et al. Nature 457, 1012–1014 (2009).
3. Preis, T., Reith, D. & Stanley, H. E. Phil. Trans. R. Soc. A 368, 5707–5719 (2010).
4. Hisano, R. et al., preprint http://www.arxiv.org/abs/1210.6321 (2012).
____________________________________________________________
Traders reveal their mood in the search terms they use.
Suppose you had a direct line into the minds of stock market traders. Would you be able to predict which investment decisions they will take, and thus anticipate the markets?
A team of researchers in the UK and US now suggests that such a crystal ball might exist, in the form of the search terms recorded and made publicly available by Google Trends. Tobias Preis of the University of Warwick Business School and his colleagues say that their analyses of Google Trends data show “early warning signs” of how the markets will shift – including the financial crash of 2008 [1].
Don’t, however, imagine that this is the way to make a fast buck. It’s one thing to offer a retrospective account of why markets behave as they do – which is what Preis and colleagues have done – and quite another to provide a genuinely predictive tool.
That’s why the work is “interesting but not earth-shattering”, in the view of British economist Paul Ormerod of the consultancy Volterra Partners in London.
Mathematical physicist Didier Sornette of the Swiss Federal Institute of Technology (ETH) in Zürich agrees, pointing out that the predictive power of the strategies the authors deduced from Google Trends data are only slightly better than predictions which assume traders make random decisions. “No investor or hedge-fund would be interested in such a strategy”, he says.
The predictive value of Google Trends has been demonstrated in other areas of social science. Most famously, outbreaks of influenza have been seen emerging in real time by monitoring the numbers of Google searches for terms related to flu prevention and cure [2].
The potential of using such information to study economic behaviour has already been spotted. Preis and coauthor Gene Stanley of Boston University have themselves shown that certain search terms reflect the volume of stock market transactions [3]. Sornette, in collaboration with Japanese economists, has found that the volatility (fluctuations) of financial markets can be correlated with the prevalence of particular topics in business news [4].
But what traders and investors really want is a method not just to assess the current state of markets but to anticipate their future course. In particular, episodes of instability, such as the financial crisis of 2008, are often preceded by periods of concern during which investors avidly seek information to decide whether to buy or sell.
Preis and colleagues figured that such anxieties and moods might be signaled by Google search terms. Just before the onset of the latest crisis, for instance, “debt” might be expected to feature prominently. That’s just what the researchers found.
To test if such correlations could be made predictive, they devised trading strategies in which a decision to buy or sell is linked to the recent prevalence of particular search terms. They simulated how these strategies would have performed between 2004 and 2011 based on real data from the financial markets.
Of the 98 ‘Google Trends’ strategies the researchers explored, that based on “debt” performed best. By 2011 it would have increased the value of a portfolio by more than 300 percent, compared with just 16 percent for a common conventional investment strategy.
Although this sounds impressive, the relevance of a predictive Google search term isn’t always clear. The second-best strategy, for example, was linked to “color”, and the fourth best to “restaurant”.
Even the use of “debt” is not obvious, since its role in the financial crash was apparent only as it happened. “How would they know in advance that they should use ‘debt’?” asks Sornette.
“In retrospect it is always possible to derive what appear to be highly successful trading strategies”, says Ormerod. “But what we want is to be able to do that before the event, not after.”
What’s more, economists acknowledge that any transparently profitable strategy for playing the markets will quickly lead to a change of trader behaviour that cancels it – a principle called Goodhart’s Law, after the British economist Charles Goodhart. “Social systems have the complication that the system may directly react to predictions being made about its behaviour”, coauthor Susannah Moat of University College London agrees.
The researchers suggest, however, that a key outcome of their approach might be to elucidate the psychological mechanisms that guide traders to their decisions, which could be encoded in their information-gathering. “Stock market data themselves tell us little about how traders make decisions”, says Preis.
“We think that the overall pattern we observe may reflect loss aversion”, he adds – the fact that humans are more concerned about losing money than they are about missing an opportunity to gain the same amount.
References
1. Preis, T., Moat, H. S. & Stanley, H. E. Nat. Sci. Rep. 3, 1684 (2013).
2. Ginsberg, J. et al. Nature 457, 1012–1014 (2009).
3. Preis, T., Reith, D. & Stanley, H. E. Phil. Trans. R. Soc. A 368, 5707–5719 (2010).
4. Hisano, R. et al., preprint http://www.arxiv.org/abs/1210.6321 (2012).
Crowdsourcing in manhunts can work
So much to post right now… but I will start with the easy stuff. Here is a news story for Nature on a preprint that seemed almost too topical to be true.
________________________________________________________________
Despite mistakes over the Boston bombers, social media can help to find people quickly.
The social news website Reddit was left red-faced after mis-identifying the suspects for the Boston marathon bombings last week, raising questions about whether crowd-sourcing to gather information might do more harm than good in such situations.
But work by a team of scientists from the United Arab Emirates and coworkers in the US and UK offers a more upbeat message about the potential of social media to assist in crime investigations and societal searches. Last year they enlisted communities on networks such as Twitter and Facebook to look for five people in different cities around the world, and were able to find three of them within the 12-hour deadline imposed [1].
In a new preprint, the researchers now analyse the behaviour that made this possible. They say that participants responded to the urgency of the search not by sending out messages to their contacts in an indiscriminate, blind panic, but by becoming even more focused and directed about whom they contacted [2].
The experiment, by computer scientist Iyad Rahwan at the Masdar Institute of Science and Technology in Abu Dhabi and his colleagues, constituted the team’s entry in the Tag Challenge staged by the US State Department in March 2012. The Tag Challenge required teams to find individuals (posing as jewel thieves) in New York City, Washington DC, London, Stockholm and Bratislava within 12 hours. Participants were given only a ‘mug shot’ of each target wearing a T-shirt bearing the competition logo, released on the morning when the competition started.
Rahwan’s team used crowd-sourcing to find the targets, offering cash incentives to individuals for uploading photos of suspects to web and cell phone apps and for recruiting more searchers. Although they failed to locate the targets in London and Stockholm, the team out-performed all others and won the competition [1].
The results showed that “among this noisy stream of tweeting and retweeting, of news articles and messages being fired off to acquaintances around the globe, people are able to efficiently guide a message towards a target in a particular city”, says Rahwan’s colleague Alex Rutherford at the Masdar Institute.
The new analysis of the information provided by participants shows that communications such as tweets became more specific and targeted as the day of the competition approached, being increasingly directed towards other users in the target cities. “Despite increasing time pressure, and its associated cognitive load, people actually became more selective in their recruitment of others, making sure information is directed in an intelligent manner”, says Rahwan.
“This makes good sense to me, and it's what I would have expected”, says Peter Sheridan Dodds of the University of Vermont. In 2003 Dodds and coworkers conducted a social-search experiment [3] to route emails to a few target people worldwide – an electronic version of the famous ‘small-world’ experiment by psychologist Stanley Milgram in 1967, in which he asked random people to forward letters to addressees identified only by name, profession and city [4]. “In our small-world experiment we found that successful searches were much more focused than unsuccessful ones and less likely to involve scattershot, connect-to-everyone attempts,” Dodds says.
Defence and security organizations have a growing interest in these outcomes. In 2009 the US defence research agency DARPA staged the Red Balloon Challenge, in which competitors were challenged to locate ten red weather balloons tethered at random locations all over the US. That challenge was won by a team at the Massachusetts Institute of Technology led by Manuel Cebrian, who collaborated with Rahwan and colleagues for the Tag Challenge. The MIT team found the red balloons in 9 hours by harnessing social-networking media [5,6].
How does all this reflect on the search for the Boston bombers? Last week, Reddit users, acting on photographs of suspects posted by the FBI, collectively pointed the finger at several individuals who had nothing to do with the bombings, including an innocent student from Brown University. The eventual arrest of Dzhokhar Tsarnaev, who previously escaped with wounds after a shootout with police, came after a neighbour spotted blood on the tarpaulin covering the boat in which he was hiding.
“The Boston manhunt is an example of how things can go wrong”, says Rahwan. “It appears that information was very much misdirected. This may be, in part, due to the high profile of the event, which led everyone to want to help even if they were incapable or misinformed.”
“There may be a tradeoff between mass mobilization and effective mobilization of a more specialized group of reliable and well-informed individuals”, he adds. “Having too many people involved might actually make things worse.” He and his colleagues have begun to explore schemes for supporting the checking and verification of crowd-sourced reporting [7].
Even President Barack Obama has commented on the hazards of search efforts like those on Reddit. “Crowd-sourcing via social media can be incredibly powerful in mobilizing people”, says Rahwan, “but it is not a silver bullet.”
“I think the web-enhanced ‘collective detective’ is potentially very powerful and is here to stay”, agrees Dodds. “But we have to ensure that the distributed social search is always used for good, meaning for example that ‘bad’ actors cannot corrupt the search, and that good, well-intentioned actors are prevented from collectively generating errors leading to witch hunts.”
“There's a lot of wisdom in the crowd when people are actually aggregating independent pieces of information”, says David Liben-Nowell of Carleton College in Northfield, Minnesota, a specialist on the searching of social networks. “But when purported information is amplified and echoed by people without truly independent information being collected, as seemed to happen in the Reddit case, then we may end up with the folly of the mob instead.”
In situations like that, says Dodds, “unofficial efforts are very important, but the onus is now on governments to create and maintain distributed social search sites that allow the public to aid in finding people. A system should already be in place that is transparent and sophisticated, and that allows for the public to provide analysis, not just photos.”
“It's not just for finding bad guys”, he adds. “Missing children are an obvious example.”
“With any kind of task like this one, we have to accept that there's a tradeoff between the risk of a false negative and a false positive”, says Liben-Nowell. “As a society, we have to think carefully about where we want to be in that spectrum.”
References
1. Rahwan, I. et al., IEEE Computer April, 68-75 (2013).
2. Rutherford, A. et al., preprint http://www.arxiv.org/abs/1304.5097.
3. Dodds, P. S., Muhamad, R. & Watts, D. J. Science 301, 827-829 (2003).
4. Milgram, S. Psychology Today 61, 60-67 (1967).
5. Tang, J. et al., Commun. ACM 54, 78-85 (2011).
6. Rutherford, A. et al., Proc. Natl Acad. Sci. USA 110, 6281-6286 (2013).
7. Naroditskiy, V., Rahwan, I., Cebrian, M. & Jennings, N. R. PLoS ONE 7, e45924 (2012).
________________________________________________________________
Despite mistakes over the Boston bombers, social media can help to find people quickly.
The social news website Reddit was left red-faced after mis-identifying the suspects for the Boston marathon bombings last week, raising questions about whether crowd-sourcing to gather information might do more harm than good in such situations.
But work by a team of scientists from the United Arab Emirates and coworkers in the US and UK offers a more upbeat message about the potential of social media to assist in crime investigations and societal searches. Last year they enlisted communities on networks such as Twitter and Facebook to look for five people in different cities around the world, and were able to find three of them within the 12-hour deadline imposed [1].
In a new preprint, the researchers now analyse the behaviour that made this possible. They say that participants responded to the urgency of the search not by sending out messages to their contacts in an indiscriminate, blind panic, but by becoming even more focused and directed about whom they contacted [2].
The experiment, by computer scientist Iyad Rahwan at the Masdar Institute of Science and Technology in Abu Dhabi and his colleagues, constituted the team’s entry in the Tag Challenge staged by the US State Department in March 2012. The Tag Challenge required teams to find individuals (posing as jewel thieves) in New York City, Washington DC, London, Stockholm and Bratislava within 12 hours. Participants were given only a ‘mug shot’ of each target wearing a T-shirt bearing the competition logo, released on the morning when the competition started.
Rahwan’s team used crowd-sourcing to find the targets, offering cash incentives to individuals for uploading photos of suspects to web and cell phone apps and for recruiting more searchers. Although they failed to locate the targets in London and Stockholm, the team out-performed all others and won the competition [1].
The results showed that “among this noisy stream of tweeting and retweeting, of news articles and messages being fired off to acquaintances around the globe, people are able to efficiently guide a message towards a target in a particular city”, says Rahwan’s colleague Alex Rutherford at the Masdar Institute.
The new analysis of the information provided by participants shows that communications such as tweets became more specific and targeted as the day of the competition approached, being increasingly directed towards other users in the target cities. “Despite increasing time pressure, and its associated cognitive load, people actually became more selective in their recruitment of others, making sure information is directed in an intelligent manner”, says Rahwan.
“This makes good sense to me, and it's what I would have expected”, says Peter Sheridan Dodds of the University of Vermont. In 2003 Dodds and coworkers conducted a social-search experiment [3] to route emails to a few target people worldwide – an electronic version of the famous ‘small-world’ experiment by psychologist Stanley Milgram in 1967, in which he asked random people to forward letters to addressees identified only by name, profession and city [4]. “In our small-world experiment we found that successful searches were much more focused than unsuccessful ones and less likely to involve scattershot, connect-to-everyone attempts,” Dodds says.
Defence and security organizations have a growing interest in these outcomes. In 2009 the US defence research agency DARPA staged the Red Balloon Challenge, in which competitors were challenged to locate ten red weather balloons tethered at random locations all over the US. That challenge was won by a team at the Massachusetts Institute of Technology led by Manuel Cebrian, who collaborated with Rahwan and colleagues for the Tag Challenge. The MIT team found the red balloons in 9 hours by harnessing social-networking media [5,6].
How does all this reflect on the search for the Boston bombers? Last week, Reddit users, acting on photographs of suspects posted by the FBI, collectively pointed the finger at several individuals who had nothing to do with the bombings, including an innocent student from Brown University. The eventual arrest of Dzhokhar Tsarnaev, who previously escaped with wounds after a shootout with police, came after a neighbour spotted blood on the tarpaulin covering the boat in which he was hiding.
“The Boston manhunt is an example of how things can go wrong”, says Rahwan. “It appears that information was very much misdirected. This may be, in part, due to the high profile of the event, which led everyone to want to help even if they were incapable or misinformed.”
“There may be a tradeoff between mass mobilization and effective mobilization of a more specialized group of reliable and well-informed individuals”, he adds. “Having too many people involved might actually make things worse.” He and his colleagues have begun to explore schemes for supporting the checking and verification of crowd-sourced reporting [7].
Even President Barack Obama has commented on the hazards of search efforts like those on Reddit. “Crowd-sourcing via social media can be incredibly powerful in mobilizing people”, says Rahwan, “but it is not a silver bullet.”
“I think the web-enhanced ‘collective detective’ is potentially very powerful and is here to stay”, agrees Dodds. “But we have to ensure that the distributed social search is always used for good, meaning for example that ‘bad’ actors cannot corrupt the search, and that good, well-intentioned actors are prevented from collectively generating errors leading to witch hunts.”
“There's a lot of wisdom in the crowd when people are actually aggregating independent pieces of information”, says David Liben-Nowell of Carleton College in Northfield, Minnesota, a specialist on the searching of social networks. “But when purported information is amplified and echoed by people without truly independent information being collected, as seemed to happen in the Reddit case, then we may end up with the folly of the mob instead.”
In situations like that, says Dodds, “unofficial efforts are very important, but the onus is now on governments to create and maintain distributed social search sites that allow the public to aid in finding people. A system should already be in place that is transparent and sophisticated, and that allows for the public to provide analysis, not just photos.”
“It's not just for finding bad guys”, he adds. “Missing children are an obvious example.”
“With any kind of task like this one, we have to accept that there's a tradeoff between the risk of a false negative and a false positive”, says Liben-Nowell. “As a society, we have to think carefully about where we want to be in that spectrum.”
References
1. Rahwan, I. et al., IEEE Computer April, 68-75 (2013).
2. Rutherford, A. et al., preprint http://www.arxiv.org/abs/1304.5097.
3. Dodds, P. S., Muhamad, R. & Watts, D. J. Science 301, 827-829 (2003).
4. Milgram, S. Psychology Today 61, 60-67 (1967).
5. Tang, J. et al., Commun. ACM 54, 78-85 (2011).
6. Rutherford, A. et al., Proc. Natl Acad. Sci. USA 110, 6281-6286 (2013).
7. Naroditskiy, V., Rahwan, I., Cebrian, M. & Jennings, N. R. PLoS ONE 7, e45924 (2012).
Wednesday, April 24, 2013
Scooped
Here’s a piece I wrote for BBC Future this week, before discovering that the blighters on their science news desk were covering the work already. So there will be something else from me on Under the Radar later this week…
______________________________________________________________
Attempts to measure and define intelligence are always controversial and open to interpretation. But none, perhaps, is quite as recondite as that now proposed by two mathematical physicists. They say that there’s a kind of rudimentary intelligence that comes from acting in a way that maximizes your future options.
Alex Wissner-Gross of Harvard University in Cambridge, Massachusetts, and Cameron Freer of the University of Hawaii at Manoa have figured out a ‘law’ that enables inanimate objects to behave this way, in effect allowing them to glimpse their own future. If they follow this law, they can show behaviour reminiscent of some of the things humans do: for example, cooperating or using ‘tools’ to conduct a task.
The researchers think that their mathematical principle might help to provide a “physics of intelligence”: an explanation of smart actions rooted in the laws of thermodynamics.
Central to their claim is the concept of entropy. Popularly described as a measure of disorder, entropy more properly describes the number of different equivalent states a system can adopt. Think of a box full of gas molecules. There are lots more ways that they can disperse uniformly throughout the available space than there are ways they can all congregate in one corner. The former situation has greater entropy.
In principle, either arrangement could arise purely from the random motions of the molecules. But there are so many more configurations of the uniformly spread gas that it is much more likely, and in practice we never see all the gas shift into one corner. This illustrates the second law of thermodynamics, which states that the total entropy of the universe always increases – simply because that’s more probable than the alternatives.
Some scientists have generalized this idea to propose that all processes of change happen in a way that has the greatest rate of entropy production. Not only do things head for the highest-entropy state, but they do so along a route that produces entropy at the greatest rate. There’s no rigorous proof that all things must happen this way, but the hypothesis of maximum entropy production has been used to account for processes such as the appearance of life, and also to design artificial-intelligence strategies that allow computers to become adept at complex games such as Go.
Wissner-Gross and Freer wondered if this hint at a link between maximal entropy production and intelligence could be made more concrete. They hit on the idea that ‘true’ intelligence is not, as they put it, “just greedily maximizing instantaneous entropy production”, but involves foresight: looking for a path that maximizes its production between now and some distant time horizon. For example, a good computer algorithm for playing Go might seek a strategy that offers the player the greatest number of options at all points into the future, rather than playing itself into a corner.
But how would an inanimate particle find that strategy? The researchers show that it can be defined via a mathematical expression for what they call the ‘causal path entropy’: the entropy production for all possible paths the particle might take. How would a particle behave if governed by the law that it must, at every instant, maximize this casual path entropy – which means, in effect, planning ahead?
Objects whose motions are guided solely by the conventional laws of motion are doomed to a blind, dumb presentism – they just go where the prevailing forces take them. Think again of those gas molecules in a box: each particle wanders aimlessly in a random walk, exploring the confining space without prejudice.
Yet when Wissner-Gross and Freer impose on such a meandering particle the demand that it move in a way that maximizes the casual path entropy, its behaviour is quite different: it tends to hover around in the centre of the box, where it suffers the least constraints on its future motion. They then explored the consequences of their new law for a so-called ‘cart and pole’ – a pendulum attached to a mobile cart, which can be stabilized in an inverted, head-up position by moving the cart back and forth, like balancing a stick on your palm. Early hominids are thought to have mastered such a delicate balancing act when they learnt to stand upright – and it’s a trick achieved by a cart-and-pole obeying the ‘maximum causal entropy’ law.
Weirder things become possible too. Wissner-Gross and Freer looked at a system composed of three disks in a box: a large one (I), a small one (II), and another small one (III) trapped inside a tube too large for I to enter. Suppose now that the movements of disk I are dictated by causal entropic ‘forcing’. In this case, the disk conspires to collide with II so that II can bounce into the tube and eject disk III. Liberating III means that the disks now have more ways to arrange themselves than when it was confined – they have more entropy. But to gain access to that entropy, disk I essentially uses II as a tool.
Similarly, two small disks governed by the causal entropic force showed a kind of social collaboration to collectively drag down a large disk into a space where they could ‘play’ with it, offering more possible states in total – another behaviour that looks strangely ‘intelligent’.
In these cases there is no real reason why the particles should be controlled by the causal entropic force – the researchers just imposed that property. But they suggest that, in a Darwinian evolving system, objects that are able this way to ‘capture’ a greater slice of the future might gain an adaptive advantage, so that such a force might be naturally selected. Not only could this offer clues about the emergence of intelligent, adaptive behaviour in the living world, but the general principle might also be useful for designing artificial intelligent systems and perhaps even for understanding problems in economics and cosmology.
Reference
A. D. Wissner-Gross & C. E. Freer, Physical Review Letters 110, 168702 (2013).
______________________________________________________________
Attempts to measure and define intelligence are always controversial and open to interpretation. But none, perhaps, is quite as recondite as that now proposed by two mathematical physicists. They say that there’s a kind of rudimentary intelligence that comes from acting in a way that maximizes your future options.
Alex Wissner-Gross of Harvard University in Cambridge, Massachusetts, and Cameron Freer of the University of Hawaii at Manoa have figured out a ‘law’ that enables inanimate objects to behave this way, in effect allowing them to glimpse their own future. If they follow this law, they can show behaviour reminiscent of some of the things humans do: for example, cooperating or using ‘tools’ to conduct a task.
The researchers think that their mathematical principle might help to provide a “physics of intelligence”: an explanation of smart actions rooted in the laws of thermodynamics.
Central to their claim is the concept of entropy. Popularly described as a measure of disorder, entropy more properly describes the number of different equivalent states a system can adopt. Think of a box full of gas molecules. There are lots more ways that they can disperse uniformly throughout the available space than there are ways they can all congregate in one corner. The former situation has greater entropy.
In principle, either arrangement could arise purely from the random motions of the molecules. But there are so many more configurations of the uniformly spread gas that it is much more likely, and in practice we never see all the gas shift into one corner. This illustrates the second law of thermodynamics, which states that the total entropy of the universe always increases – simply because that’s more probable than the alternatives.
Some scientists have generalized this idea to propose that all processes of change happen in a way that has the greatest rate of entropy production. Not only do things head for the highest-entropy state, but they do so along a route that produces entropy at the greatest rate. There’s no rigorous proof that all things must happen this way, but the hypothesis of maximum entropy production has been used to account for processes such as the appearance of life, and also to design artificial-intelligence strategies that allow computers to become adept at complex games such as Go.
Wissner-Gross and Freer wondered if this hint at a link between maximal entropy production and intelligence could be made more concrete. They hit on the idea that ‘true’ intelligence is not, as they put it, “just greedily maximizing instantaneous entropy production”, but involves foresight: looking for a path that maximizes its production between now and some distant time horizon. For example, a good computer algorithm for playing Go might seek a strategy that offers the player the greatest number of options at all points into the future, rather than playing itself into a corner.
But how would an inanimate particle find that strategy? The researchers show that it can be defined via a mathematical expression for what they call the ‘causal path entropy’: the entropy production for all possible paths the particle might take. How would a particle behave if governed by the law that it must, at every instant, maximize this casual path entropy – which means, in effect, planning ahead?
Objects whose motions are guided solely by the conventional laws of motion are doomed to a blind, dumb presentism – they just go where the prevailing forces take them. Think again of those gas molecules in a box: each particle wanders aimlessly in a random walk, exploring the confining space without prejudice.
Yet when Wissner-Gross and Freer impose on such a meandering particle the demand that it move in a way that maximizes the casual path entropy, its behaviour is quite different: it tends to hover around in the centre of the box, where it suffers the least constraints on its future motion. They then explored the consequences of their new law for a so-called ‘cart and pole’ – a pendulum attached to a mobile cart, which can be stabilized in an inverted, head-up position by moving the cart back and forth, like balancing a stick on your palm. Early hominids are thought to have mastered such a delicate balancing act when they learnt to stand upright – and it’s a trick achieved by a cart-and-pole obeying the ‘maximum causal entropy’ law.
Weirder things become possible too. Wissner-Gross and Freer looked at a system composed of three disks in a box: a large one (I), a small one (II), and another small one (III) trapped inside a tube too large for I to enter. Suppose now that the movements of disk I are dictated by causal entropic ‘forcing’. In this case, the disk conspires to collide with II so that II can bounce into the tube and eject disk III. Liberating III means that the disks now have more ways to arrange themselves than when it was confined – they have more entropy. But to gain access to that entropy, disk I essentially uses II as a tool.
Similarly, two small disks governed by the causal entropic force showed a kind of social collaboration to collectively drag down a large disk into a space where they could ‘play’ with it, offering more possible states in total – another behaviour that looks strangely ‘intelligent’.
In these cases there is no real reason why the particles should be controlled by the causal entropic force – the researchers just imposed that property. But they suggest that, in a Darwinian evolving system, objects that are able this way to ‘capture’ a greater slice of the future might gain an adaptive advantage, so that such a force might be naturally selected. Not only could this offer clues about the emergence of intelligent, adaptive behaviour in the living world, but the general principle might also be useful for designing artificial intelligent systems and perhaps even for understanding problems in economics and cosmology.
Reference
A. D. Wissner-Gross & C. E. Freer, Physical Review Letters 110, 168702 (2013).
Sunday, April 21, 2013
Burning issues
Nice piece in the Observer to day by Will Hutton on the absurdity of valuing fossil-fuel reserves on the assumption that they will all be burned, which will doom us to a probable degree of global warming that you just don’t want to think about.
Shame he trips up here though:
“Galileo had to take on the Catholic church to prove the world was round, today's scientists have to take on the right to prove that climate change is man-made.”
Um, Galileo did what, exactly? Well, y'know, he did something or other really sciency and the church just hit him with the Bible until he said sorry. Sometimes I worry that the popular view of Galileo is going to get ever more mangled until one can suggest without fear of contradiction that he was burned at the stake for proving that the universe began with a Big Bang.
However, it is as depressing as ever to read some of the feedback on the Guardian’s Comment is Free, including remarks like this:
“The planet will do absolutely fine. To think humanity has any influence on climate takes human arrogance to the extreme. The planet was here long before we were, and it will remain long after the human race has destroyed itself by other means.”
It would be tempting just to roll one’s eyes at this kind of head-in-sand, defiant ignorance if it were not so widespread. One can’t help suspecting that some of those oil magnates take this same view.
Shame he trips up here though:
“Galileo had to take on the Catholic church to prove the world was round, today's scientists have to take on the right to prove that climate change is man-made.”
Um, Galileo did what, exactly? Well, y'know, he did something or other really sciency and the church just hit him with the Bible until he said sorry. Sometimes I worry that the popular view of Galileo is going to get ever more mangled until one can suggest without fear of contradiction that he was burned at the stake for proving that the universe began with a Big Bang.
However, it is as depressing as ever to read some of the feedback on the Guardian’s Comment is Free, including remarks like this:
“The planet will do absolutely fine. To think humanity has any influence on climate takes human arrogance to the extreme. The planet was here long before we were, and it will remain long after the human race has destroyed itself by other means.”
It would be tempting just to roll one’s eyes at this kind of head-in-sand, defiant ignorance if it were not so widespread. One can’t help suspecting that some of those oil magnates take this same view.
Wednesday, April 17, 2013
Lest we forget
Before my weekly game of 5-a-side football it was proposed that the team in white would be the Thatcherites and those in black the Scargillites. How fitting, then, that the blacks never looked like winning, but struggled valiantly while constantly undermining their efforts with poor tactics.
I guess I was never going to be so interested in demonstrating at a funeral, though I understand the motives of those who did. I was in the NUJ in the late 1980s and will never forget the contempt and glee that was palpable behind its de-recognition in the publishing industry.
As I stepped off the plane from China last Tuesday, I picked up a copy of the FT and was soon enough spluttering like a retired colonel over the pathetic tributes it ran from the likes of Niall Ferguson. At least the FT has published my letter in response to those pieces. Here is the original – and while I understand the need for shortening, it was her legacy of arms dealing (remember Jonathan Aitken?) that sticks most in my craw.
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Sir, It is astonishing that none of your fawning tributes to Margaret Thatcher is able to connect the current economic crisis to the deregulatory, venal, credit-buoyed Thatcherite 1980s – unless the remark in your leader that their “impact has been lasting” is supposed to be ironic. (Certainly your remark that “deregulation and liberalisation are no longer in fashion” suggests that you might after all have some satirical intent.) You, Niall Ferguson and Janan Ganesh seem under the impression that Thatcher’s economic nous bequeathed a solid and continued legacy of prosperity. Yet whatever improvement in Britain’s standard of living that manages to survive today’s crisis stems from a trend that has been both steady for at least four decades and common throughout Europe.
Your writers betray the same breed of fantastical thinking that led President Obama to praise a “great champion of freedom” who befriended and defended Augusto Pinochet, called Nelson Mandela a terrorist, brokered lucrative arms deals with some of the most repressive regimes in the world, and severely and sometimes brutally curtailed civil liberties at home.
Ganesh suggests that to call Thatcher divisive is feeble and mealy-mouthed. He can rest assured that many of us who lived through her incumbency will not be so coy.
I guess I was never going to be so interested in demonstrating at a funeral, though I understand the motives of those who did. I was in the NUJ in the late 1980s and will never forget the contempt and glee that was palpable behind its de-recognition in the publishing industry.
As I stepped off the plane from China last Tuesday, I picked up a copy of the FT and was soon enough spluttering like a retired colonel over the pathetic tributes it ran from the likes of Niall Ferguson. At least the FT has published my letter in response to those pieces. Here is the original – and while I understand the need for shortening, it was her legacy of arms dealing (remember Jonathan Aitken?) that sticks most in my craw.
______________________________________________________________________
Sir, It is astonishing that none of your fawning tributes to Margaret Thatcher is able to connect the current economic crisis to the deregulatory, venal, credit-buoyed Thatcherite 1980s – unless the remark in your leader that their “impact has been lasting” is supposed to be ironic. (Certainly your remark that “deregulation and liberalisation are no longer in fashion” suggests that you might after all have some satirical intent.) You, Niall Ferguson and Janan Ganesh seem under the impression that Thatcher’s economic nous bequeathed a solid and continued legacy of prosperity. Yet whatever improvement in Britain’s standard of living that manages to survive today’s crisis stems from a trend that has been both steady for at least four decades and common throughout Europe.
Your writers betray the same breed of fantastical thinking that led President Obama to praise a “great champion of freedom” who befriended and defended Augusto Pinochet, called Nelson Mandela a terrorist, brokered lucrative arms deals with some of the most repressive regimes in the world, and severely and sometimes brutally curtailed civil liberties at home.
Ganesh suggests that to call Thatcher divisive is feeble and mealy-mouthed. He can rest assured that many of us who lived through her incumbency will not be so coy.
Friday, April 12, 2013
Mystical atoms
Here is my Crucible column in the latest issue of Chemistry World.
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A strong contender for the strangest book about chemistry ever written is Occult Chemistry (1909) by Annie Besant and Charles Leadbeater. It offers an element-by-element account of what atoms really look like, and the answer is that they are astonishingly rich in substructure and detail – some like ornate frozen splashes, others resembling the rose windows of Gothic cathedrals. Far from being unsplittable – this was 8 years before Ernest Rutherford astonished the world by “splitting the atom” – these atoms are composites of more fundamental particles, of which hydrogen is composed of 18 and nitrogen of no fewer than 290.
You’re wondering, no doubt, how on earth the authors knew all this in the days before X-ray diffraction, electron microscopy and high-energy particle physics. The answer is that they saw it for themselves. Besant was President of the Theosophical Society, the Eastern-tinged mystical group founded by the Russian medium Madame Blavatsky, and Leadbeater was a Spiritualist medium. Their occult powers enabled the duo to shrink their perceptive faculties to atomic dimensions, whereupon they could perceive the shapes of atoms directly.
So far, so deluded. But that was a very strange time, and one can’t quite just dismiss Besant and Leadbeater as mad fantasists. They were connected with, and in a wider sense in tune with, several leading scientists of their age, some of whom read the book (with varying degrees of scepticism). Like it or not, Occult Chemistry is a part – a bizarre, even unsettling part – of chemical history.
While Blavatsky was little more than a wily, self-promoting fraud, Besant warrants more consideration. Born in 1847, she was a fearless social campaigner, arguing for women’s rights and birth control, better conditions for workers, free school meals, educational reform, and home rule for India, her spiritual home. Her conversion to Blavatsky’s pseudo-religion in 1889 dismayed many of her progressive friends, including George Bernard Shaw, but it didn’t in itself mark her out as odd in an age when mystical inclinations were shared by many scientists, most notoriously the Spiritualist sympathizers Oliver Lodge and William Crookes.
Crookes, the chemist and entrepreneur who was President of the Royal Society from 1913 to 1915, was himself a member of the Theosophical Society, and was convinced that Spiritualism offered glimpses into an invisible world populated by spirit beings. He was flattered and courted by the Theosophists – Blavatsky referred to his work on an alleged new form of ‘radiant matter’ – and Besant sent him an initial account of her ‘occult chemistry’ published in the Theosophical magazine Lucifer in 1895. Since Crookes had suggested in 1887 that elements might be sub-divided further into a basic ingredient called protyle, he was somewhat sympathetic to Besant and Leadbeater’s assertions, and he seems to have replied politely, telling Besant that the book might encourage chemists to search for the missing elements in Mendeleyev’s periodic table1.
Besant and Leadbeater claimed they had used mediation techniques to gaze on atoms with ‘etheric eyes’. This revealed atoms with elaborate, lobed shapes that fall into distinct classes: ‘spikes’, ‘dumbbells’ and arrangements like the Platonic solids. Closer inspection showed a substructure made up of units they call anu, the Sanskrit word for atoms. The anu are themselves “atoms of ether”, the medium still then considered the matrix of electromagnetic waves, and here identified with Crookes’ protyle. That the ether was a particulate material was not in itself an outrageous suggestion – Mendeleyev believed this too. Some scientists, including Crookes, suspected the ether was a bridge between the physical and spiritual worlds.
Most of Occult Chemistry in taken up with descriptions and diagrams of these elemental substructures. The images are mesmerizing, elaborated in meticulous and often beautiful detail. With their ‘sciency’ appearance, bedded down amidst numerical calculations, it’s easy to see how – especially at a time when the discoveries of X-rays, electrons, radioactivity and atomic structure were making atomic physics a veritable phantasmagoria where anything seemed possible – contemporary readers might have found this stuff impossible to distinguish from real science. But the allure goes deeper, for you can’t look at these images today without experiencing some frisson. The triplets of fundamental particles at the atom’s core must put you in mind of the quark structure of nucleons – and indeed it’s been argued that the revelations of Occult Chemistry bear uncanny resonances with the discoveries of particle physics2. What’s more, the lobes and dumbbells speak immediately to the chemist of the electron orbitals shortly to emerge from quantum chemistry. It’s sheer coincidence – has to be, right? – but it’s eerie all the same.
What most of Crookes’ contemporaries made of all this is unknown. But I bet they were intrigued. J. J. Thomson, the discoverer of the electron, went to séances, as did Pierre Curie. George Johnstone Stoney, who named the electron, was convinced that the universe was an infinite series of worlds within worlds. Francis Aston, the discoverer of isotopes, read the book and borrowed from it the term “meta-neon” to refer to his newly discovered neon-22 (ref. 3).
Occult Chemistry is, then, pretentious and outrageous – but curiously compelling.
References
1. W. H. Brock, William Crookes (1832-1919) and the Commercialization of Science. Ashgate, Aldershot, 2008.
2. S. M. Phillips, Extra-Sensory Perception of Quarks. Theosophical Publishing House, London, 1980.
3. J. Hughes, Physics World September, 31-35 (2003).
Thursday, April 11, 2013
A demon-haunted theory
Here is a piece I’ve just published in the April issue of Physics World, in pre-edited form (sort of).
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James Clerk Maxwell originally devised his demon as a thought experiment to evade the second law of thermodynamics. But some of the physicist’s contemporaries actually believed it was an intelligent being that could bridge hidden worlds and provide a scientific route to immortality of the human soul.
Maxwell’s demon represents one of the great “thought experiments” of physics. Just like Einstein riding a light wave or Schrödinger’s cat facing quantum extermination, it poses a ‘what if’ question that illuminates a deep property of nature. The Scottish physicist James Clerk Maxwell proposed his little being as a way of picking a hole in the second law of thermodynamics by enabling heat to flow from cold to hot and resisting entropy’s disruptive influence. He had no idea that he was actually posing a riddle for the theory of information, which would lead ultimately to the recent demonstration that information and energy can be interconverted.
But the popularity that Maxwell’s demon has enjoyed thanks to the current burgeoning interest in the thermodynamics of information overlooks the way this little being was regarded by Maxwell and his contemporaries. Placed in its historical context, Maxwell’s demon played a rather different role – one that is surprising and in some respects shocking. For one thing, this wasn’t exactly a thought experiment at all. Some of Maxwell’s contemporaries saw in the demon a link between science and religion, a solution to the problem of free will, a bridge to hidden worlds, even a scientific route to immortality of the human soul. In some ways, Maxwell’s original demon seems more closely linked to ancient demonology than to the future of computing and information science.
Picking holes
Maxwell’s idea was a response to the gloomy prediction of a ‘cosmic heat death’ of the universe. In 1850 the German physicist Rudolph Clausius formulated the first and second laws of thermodynamics: the conservation of energy and the irreversibility of heat flow from hot to cold. A year later William Thomson (later Lord Kelvin) pointed out that the flow of heat involves ‘dissipation’ of mechanical energy: it flows into random motions of molecules and can never be recovered. This process, he said, must eventually create a universe of uniform temperature, from which no useful work can be extracted, and in which nothing really happens.
Maxwell realised that this inexorable slide into an inert state challenged human free will. If, as the second law says, there is only one way for things to happen, we would seem to be locked into rigid determinism, with human freedom just an illusion. As a devout Christian, he could not accept that God would arrange things this way. But how could free will be rescued without violating thermodynamics?
Maxwell’s seminal work on the microscopic theory of gases gave him an escape clause. He was convinced that the second law is simply statistical. Gases contain molecules with a bell-shaped statistical distribution of speeds, the faster ones being in a sense ‘hotter’. Temperature gradients get dissipated because it is far more likely that the faster molecules will mingle with the slower, rather than by chance congregating into a ‘hot’ patch. There’s nothing in the laws of mechanics to forbid the latter; it’s just very unlikely.
But what if we could arrange for that to happen? Then the second law would be undone. We can’t manage it in practice, Maxwell recognized, because we can’t possibly find out about the velocities of all the individual molecules. But what if there were, as Maxwell put it, a “finite being”, small enough to ‘see’ each molecule and able to keep track of it, who could open and shut a trapdoor in a wall dividing a gas-filled vessel? This being could let through fast-moving molecules in one direction so as to congregate the heat in one compartment, separating hot from cold and creating a temperature gradient that could be tapped to do work.
Maxwell laid out this idea in December 1867 in response to a letter from his friend, the physicist Peter Guthrie Tait, who was drafting a book on the history of thermodynamics. Maxwell told Tait that his aim was explicitly to “pick a hole” in the second law – to show that it was “only a statistical certainty”. The thought experiment offered a loophole that might rescue free will.
Exorcising the demon
It took over a century for the problem with Maxwell’s demon to be identified. In 1929 the Hungarian physicist Leo Szilárd believed he saw a flaw: to measure the speed of molecules the demon would have to expend energy, which would dissipate enough heat – produce enough entropy – to compensate for the demon’s manipulations. But in 1961 the German-American physicist Rolf Landauer, drawing on the relationship between information processing and thermodynamics developed by Claude Shannon in the 1940s, pointed out that measurements can in principle be conducted without increasing entropy.
That may be done, however, only by retaining all the information that the demon acquires. But, said Landauer, if he is a ‘finite being’ with a finite memory, this accumulation of data can’t go on forever: eventually some information will have to be erased to make room for more. And Landauer showed that while measurement can be free of an entropic cost, erasing data can’t be. Resetting a binary digit (from 1 to 0, say) must inevitably dissipate energy of at least kTln2, where k is Boltzmann’s constant. So in effect the demon generates entropy by forgetting. Charles Bennett of IBM’s research centre in Yorktown Heights later showed that this act of ‘forgetting’ is unavoidable, since it is equivalent to resetting the measuring equipment ready for the next measurement.
Landauer’s discovery has profound implications for the theory of computation. The digital circuits in today’s computers – which are inevitably reset from one calculation to the next – will always dissipate a certain minimum amount of heat during processing, although at present they still create far more heat than this lower limit because of other sources of dissipation. The existence of this unavoidable heat output in computing was proved experimentally last year by a team at the University of Augsburg in Germany, who were able to measure the amount of energy dissipated when a microscopic silica bead was moved between two optical traps to encode a binary digit. They found that as a cycle of switching and resetting the bead’s position was made ever slower, the amount of energy dissipated fell to a minimum of kTln2: for infinitely slow switching, all of this was due solely to the resetting operation [1].
In effect Landauer’s principle implies an equivalence between information and heat: information itself can be converted to heat. This too has recently been confirmed experimentally. In 2010 a team of physicists at the University of Tokyo led by Shoichi Toyabe moved a nanoscale polystyrene bead in a particular direction, doing useful work, not by using any energy as such but by taking advantage of the information gathered about the bead’s position [2]. They put the bead on a spiral staircase of sorts, on which the bead could hop up or down one step at a time using thermal energy. Left to its own devices, the ball would, on average, move down the staircase. But if a demon knew the position of the ball, it could place a barrier to prevent any downhill motion, so that the ball only moves uphill. In the experiment, the physicists took on the role of the demon: if the bead was measured to have moved uphill by one step, the barrier was moved upwards by one step too. By taking advantage of information gathered about the bead’s position, the physicists – using no energy as such – ensured the bead’s net uphill movement and thereby caused the bead to gain potential energy. This demonstrated experimentally that information can be converted into energy.
These studies reveal that Maxwell’s thought experiment is now accessible to direct experimental probing, and that such efforts are at the forefront of information science and technology. Moreover, even if Landauer’s principle currently represents the standard doctrine, some commentators feel that it may still be too early to be sure that the demon is dead, and that ultimately it will prove to have ramifications for the foundations of quantum information theory [3,4].
Little helpers
Maxwell didn’t intend his creature to be called a demon. That label was applied by Thomson in an 1874 paper in Nature, where he defined it as “an intelligent being endowed with free will, and fine enough tactile and perceptive organization to give him the faculty of observing and influencing individual molecules of matter.” Whether he meant it or not, this seemingly trivial change connected Maxwell’s being to a long genealogy of tiny or invisible spirits acting as agents and familiars with special powers, dating back to the demon that allegedly advised Socrates. Maxwell was not pleased. “Call him no more a demon but a valve”, he grumbled to Tait.
"Who gave them this name? Thomson." Maxwell grumbles to Tait in this letter.
Maxwell’s apparent victory over the second law in the nineteenth century might seem decidedly Pyrrhic, since as he admitted, we can’t possibly do what the demon does anyway. Maxwell presumably could have argued that we might one day have the technological means, but he didn’t seem to hold out much prospect of that. There is, however, another way that his thought experiment could work: the demons might be real. Maxwell seems to have entertained this idea, for he took seriously the possibility that free will depended on it.
The notion of invisible, perhaps demonic, beings that intervene in the world was widely shared among philosophers of the Middle Ages and the Renaissance. But surely such ideas were banished by Victorian times? Not at all. Maxwell himself seems never to have stated whether he regarded his ‘demon’ as a being – his references to a “valve” and a “self-acting” device suggest he may have preferred the image of a machine, as physicists do today – albeit a ‘machine’ with intelligence and autonomy, as he once put it “a doorkeeper, very intelligent and exceedingly quick.” Yet his touchiness about Thomson’s quip seems rather puritanical even for a religious man until one realises that Maxwell might have entertained a belief in evil spirits.
Demons performing useful work for humans in a sixteenth-century illustration.
Several of his contemporaries had little doubt that these ‘demons’ were to be taken literally. Thomson himself took pains to stress that the demon was plausible, calling it “a being with no preternatural qualities, [which] differs from real animals only in extreme smallness and agility.” Tait evidently believed they might exist, and he enlisted them for an extraordinary cause. In 1875 Tait and the Scottish physicist Balfour Stewart, an expert on the theory of heat, published a book called The Unseen Universe in which they attempted to show that “the presumed incompatibility of Science and Religion does not exist.” There must be, they wrote, “an invisible order of things which will remain and possess energy when the present system has passed away.” They believed that this “invisible” or “spiritual” domain must be capable of interacting energetically with the familiar physical world, perhaps bridged by the pervasive ether that was then thought to carry Maxwell’s electromagnetic waves. Thus energy might be transferred from the physical to the invisible realm to sustain our souls after death: through living, we store up immortality.
Tait and Stewart were aware of the apparent conflict between the Christian doctrine of the immortality of the soul and the second law of thermodynamics, which seemed to enforce an eventual universe of insensate stasis. “The dissipation of energy must hold true”, they admitted, “and although the process of decay may be delayed by the storing up of energy in the invisible universe, it cannot be permanently arrested.” Maxwell’s demon gave them a way out. “Clerk-Maxwell’s demons”, they wrote, “could be made to restore energy in the present universe without spending work” – and as a result, “immortality is possible.”
Today these speculations, coming from two highly respected scientists who Maxwell esteemed, look bizarre. But in the late nineteenth century such ideas were widely held. Spiritualism interested many scientists, including William Crookes, Oliver Lodge, J. J. Thomson and Pierre Curie. Even though some, like Tait and Stewart, were sceptical of the claims of mediums, they did not object to the basic concept.
Scientific spirit
Not only did these scientists believe in a spiritual world, but they felt that science was on the threshold of proving its existence. Many regarded the ether as a mediator. Cromwell Varley, a pioneer in transatlantic telegraphy, drew analogies between the use of electromagnetic signals for long-distance communication and the invisible messages that were alleged to pass from spirits to the living. The distinguished English physicist William Barrett wrote in 1917 that “it is not a very incredible thing to suppose that in the luminiferous ether life of some kind exists.” He speculated about “four-dimensional beings” and “human-like intelligences – good or bad daimonia” that might be responsible for events at séances. The Irish physicist Edmund Fournier d’Albe proposed in 1907 that there might exist “infra-men” on the scale of atoms, and drew on the discoveries of radioactivity and the electron to present a “physical theory of immortality.”
Indeed, the discoveries of new ‘invisible rays’, such as X-rays and radioactivity (“Roentgen rays”) bolstered beliefs in unseen universes. William Crookes – one of the most notorious sympathizers of the Spiritualists, mediums and Theosophists of the age – felt that vibrations beyond X-rays might account for telepathy. He too found a striking role for Maxwell’s demon, arguing that it might in effect explain the mystery of radioactive uranium’s seemingly inexhaustible supply of energy. He suggested that uranium atoms might be like demons themselves, mining energy from the surrounding atmosphere by sifting hot gas molecules from cold. “Let uranium or polonium”, he said at the annual meeting of the British Association in 1898, “have a structure that enables them to throw off the slow moving molecules of the atmosphere, while the quick moving molecules, smashing on to the surface, have their energy reduced and that of the target correspondingly increased.” It’s not clear that Crookes thought any intelligent agency was involved here, although he certainly believed in the possibility of invisible beings that have “intelligence, thought, and will, existing without form or matter” – and Maxwell had made clear that intelligence was needed to make the selection among gas molecules.
All this reveals that Maxwell’s demons had a much more ambiguous ontological status than imaginary ‘thought-creatures’. As well as reminding us that even apparently ‘modern’ historical scientists didn’t necessarily see things was we do, it shows how sometimes science doesn’t banish mystical beliefs but offers ‘rational’ justifications for them.
References
1. A. Bérut et al. Nature 483, 187–189 (2012).
2. S. Toyabe, T. Sagawa, M. Ueda, E. Muneyuki & M. Sano, Nat. Phys. 6, 988-992 (2010).
3. J. Earman & J. D. Norton, Stud. Hist. Phil. Mod. Phys. 29, 435-471 (1998) & 30, 1-40 (1999).
4. K. Maruyama, F. Nori & V. Vedral, Rev. Mod. Phys. 81, 1-23 (2009).
Further reading
B. Stewart & P. G. Tait, The Unseen Universe. Macmillan, London, 1875.
R. H. Harman, The Natural Philosophy of James Clerk Maxwell. Cambridge University Press, 1998.
W. H. Brock, William Crookes (1832-1919) and the Commercialization of Science. Ashgate, Aldershot, 2008.
J. Canales & M Krajewski, Interdisciplinary Science Reviews 37, 314-331 (2012).
______________________________________________________________
James Clerk Maxwell originally devised his demon as a thought experiment to evade the second law of thermodynamics. But some of the physicist’s contemporaries actually believed it was an intelligent being that could bridge hidden worlds and provide a scientific route to immortality of the human soul.
Maxwell’s demon represents one of the great “thought experiments” of physics. Just like Einstein riding a light wave or Schrödinger’s cat facing quantum extermination, it poses a ‘what if’ question that illuminates a deep property of nature. The Scottish physicist James Clerk Maxwell proposed his little being as a way of picking a hole in the second law of thermodynamics by enabling heat to flow from cold to hot and resisting entropy’s disruptive influence. He had no idea that he was actually posing a riddle for the theory of information, which would lead ultimately to the recent demonstration that information and energy can be interconverted.
But the popularity that Maxwell’s demon has enjoyed thanks to the current burgeoning interest in the thermodynamics of information overlooks the way this little being was regarded by Maxwell and his contemporaries. Placed in its historical context, Maxwell’s demon played a rather different role – one that is surprising and in some respects shocking. For one thing, this wasn’t exactly a thought experiment at all. Some of Maxwell’s contemporaries saw in the demon a link between science and religion, a solution to the problem of free will, a bridge to hidden worlds, even a scientific route to immortality of the human soul. In some ways, Maxwell’s original demon seems more closely linked to ancient demonology than to the future of computing and information science.
Picking holes
Maxwell’s idea was a response to the gloomy prediction of a ‘cosmic heat death’ of the universe. In 1850 the German physicist Rudolph Clausius formulated the first and second laws of thermodynamics: the conservation of energy and the irreversibility of heat flow from hot to cold. A year later William Thomson (later Lord Kelvin) pointed out that the flow of heat involves ‘dissipation’ of mechanical energy: it flows into random motions of molecules and can never be recovered. This process, he said, must eventually create a universe of uniform temperature, from which no useful work can be extracted, and in which nothing really happens.
Maxwell realised that this inexorable slide into an inert state challenged human free will. If, as the second law says, there is only one way for things to happen, we would seem to be locked into rigid determinism, with human freedom just an illusion. As a devout Christian, he could not accept that God would arrange things this way. But how could free will be rescued without violating thermodynamics?
Maxwell’s seminal work on the microscopic theory of gases gave him an escape clause. He was convinced that the second law is simply statistical. Gases contain molecules with a bell-shaped statistical distribution of speeds, the faster ones being in a sense ‘hotter’. Temperature gradients get dissipated because it is far more likely that the faster molecules will mingle with the slower, rather than by chance congregating into a ‘hot’ patch. There’s nothing in the laws of mechanics to forbid the latter; it’s just very unlikely.
But what if we could arrange for that to happen? Then the second law would be undone. We can’t manage it in practice, Maxwell recognized, because we can’t possibly find out about the velocities of all the individual molecules. But what if there were, as Maxwell put it, a “finite being”, small enough to ‘see’ each molecule and able to keep track of it, who could open and shut a trapdoor in a wall dividing a gas-filled vessel? This being could let through fast-moving molecules in one direction so as to congregate the heat in one compartment, separating hot from cold and creating a temperature gradient that could be tapped to do work.
Maxwell laid out this idea in December 1867 in response to a letter from his friend, the physicist Peter Guthrie Tait, who was drafting a book on the history of thermodynamics. Maxwell told Tait that his aim was explicitly to “pick a hole” in the second law – to show that it was “only a statistical certainty”. The thought experiment offered a loophole that might rescue free will.
Exorcising the demon
It took over a century for the problem with Maxwell’s demon to be identified. In 1929 the Hungarian physicist Leo Szilárd believed he saw a flaw: to measure the speed of molecules the demon would have to expend energy, which would dissipate enough heat – produce enough entropy – to compensate for the demon’s manipulations. But in 1961 the German-American physicist Rolf Landauer, drawing on the relationship between information processing and thermodynamics developed by Claude Shannon in the 1940s, pointed out that measurements can in principle be conducted without increasing entropy.
That may be done, however, only by retaining all the information that the demon acquires. But, said Landauer, if he is a ‘finite being’ with a finite memory, this accumulation of data can’t go on forever: eventually some information will have to be erased to make room for more. And Landauer showed that while measurement can be free of an entropic cost, erasing data can’t be. Resetting a binary digit (from 1 to 0, say) must inevitably dissipate energy of at least kTln2, where k is Boltzmann’s constant. So in effect the demon generates entropy by forgetting. Charles Bennett of IBM’s research centre in Yorktown Heights later showed that this act of ‘forgetting’ is unavoidable, since it is equivalent to resetting the measuring equipment ready for the next measurement.
Landauer’s discovery has profound implications for the theory of computation. The digital circuits in today’s computers – which are inevitably reset from one calculation to the next – will always dissipate a certain minimum amount of heat during processing, although at present they still create far more heat than this lower limit because of other sources of dissipation. The existence of this unavoidable heat output in computing was proved experimentally last year by a team at the University of Augsburg in Germany, who were able to measure the amount of energy dissipated when a microscopic silica bead was moved between two optical traps to encode a binary digit. They found that as a cycle of switching and resetting the bead’s position was made ever slower, the amount of energy dissipated fell to a minimum of kTln2: for infinitely slow switching, all of this was due solely to the resetting operation [1].
In effect Landauer’s principle implies an equivalence between information and heat: information itself can be converted to heat. This too has recently been confirmed experimentally. In 2010 a team of physicists at the University of Tokyo led by Shoichi Toyabe moved a nanoscale polystyrene bead in a particular direction, doing useful work, not by using any energy as such but by taking advantage of the information gathered about the bead’s position [2]. They put the bead on a spiral staircase of sorts, on which the bead could hop up or down one step at a time using thermal energy. Left to its own devices, the ball would, on average, move down the staircase. But if a demon knew the position of the ball, it could place a barrier to prevent any downhill motion, so that the ball only moves uphill. In the experiment, the physicists took on the role of the demon: if the bead was measured to have moved uphill by one step, the barrier was moved upwards by one step too. By taking advantage of information gathered about the bead’s position, the physicists – using no energy as such – ensured the bead’s net uphill movement and thereby caused the bead to gain potential energy. This demonstrated experimentally that information can be converted into energy.
These studies reveal that Maxwell’s thought experiment is now accessible to direct experimental probing, and that such efforts are at the forefront of information science and technology. Moreover, even if Landauer’s principle currently represents the standard doctrine, some commentators feel that it may still be too early to be sure that the demon is dead, and that ultimately it will prove to have ramifications for the foundations of quantum information theory [3,4].
Little helpers
Maxwell didn’t intend his creature to be called a demon. That label was applied by Thomson in an 1874 paper in Nature, where he defined it as “an intelligent being endowed with free will, and fine enough tactile and perceptive organization to give him the faculty of observing and influencing individual molecules of matter.” Whether he meant it or not, this seemingly trivial change connected Maxwell’s being to a long genealogy of tiny or invisible spirits acting as agents and familiars with special powers, dating back to the demon that allegedly advised Socrates. Maxwell was not pleased. “Call him no more a demon but a valve”, he grumbled to Tait.
"Who gave them this name? Thomson." Maxwell grumbles to Tait in this letter.
Maxwell’s apparent victory over the second law in the nineteenth century might seem decidedly Pyrrhic, since as he admitted, we can’t possibly do what the demon does anyway. Maxwell presumably could have argued that we might one day have the technological means, but he didn’t seem to hold out much prospect of that. There is, however, another way that his thought experiment could work: the demons might be real. Maxwell seems to have entertained this idea, for he took seriously the possibility that free will depended on it.
The notion of invisible, perhaps demonic, beings that intervene in the world was widely shared among philosophers of the Middle Ages and the Renaissance. But surely such ideas were banished by Victorian times? Not at all. Maxwell himself seems never to have stated whether he regarded his ‘demon’ as a being – his references to a “valve” and a “self-acting” device suggest he may have preferred the image of a machine, as physicists do today – albeit a ‘machine’ with intelligence and autonomy, as he once put it “a doorkeeper, very intelligent and exceedingly quick.” Yet his touchiness about Thomson’s quip seems rather puritanical even for a religious man until one realises that Maxwell might have entertained a belief in evil spirits.
Demons performing useful work for humans in a sixteenth-century illustration.
Several of his contemporaries had little doubt that these ‘demons’ were to be taken literally. Thomson himself took pains to stress that the demon was plausible, calling it “a being with no preternatural qualities, [which] differs from real animals only in extreme smallness and agility.” Tait evidently believed they might exist, and he enlisted them for an extraordinary cause. In 1875 Tait and the Scottish physicist Balfour Stewart, an expert on the theory of heat, published a book called The Unseen Universe in which they attempted to show that “the presumed incompatibility of Science and Religion does not exist.” There must be, they wrote, “an invisible order of things which will remain and possess energy when the present system has passed away.” They believed that this “invisible” or “spiritual” domain must be capable of interacting energetically with the familiar physical world, perhaps bridged by the pervasive ether that was then thought to carry Maxwell’s electromagnetic waves. Thus energy might be transferred from the physical to the invisible realm to sustain our souls after death: through living, we store up immortality.
Tait and Stewart were aware of the apparent conflict between the Christian doctrine of the immortality of the soul and the second law of thermodynamics, which seemed to enforce an eventual universe of insensate stasis. “The dissipation of energy must hold true”, they admitted, “and although the process of decay may be delayed by the storing up of energy in the invisible universe, it cannot be permanently arrested.” Maxwell’s demon gave them a way out. “Clerk-Maxwell’s demons”, they wrote, “could be made to restore energy in the present universe without spending work” – and as a result, “immortality is possible.”
Today these speculations, coming from two highly respected scientists who Maxwell esteemed, look bizarre. But in the late nineteenth century such ideas were widely held. Spiritualism interested many scientists, including William Crookes, Oliver Lodge, J. J. Thomson and Pierre Curie. Even though some, like Tait and Stewart, were sceptical of the claims of mediums, they did not object to the basic concept.
Scientific spirit
Not only did these scientists believe in a spiritual world, but they felt that science was on the threshold of proving its existence. Many regarded the ether as a mediator. Cromwell Varley, a pioneer in transatlantic telegraphy, drew analogies between the use of electromagnetic signals for long-distance communication and the invisible messages that were alleged to pass from spirits to the living. The distinguished English physicist William Barrett wrote in 1917 that “it is not a very incredible thing to suppose that in the luminiferous ether life of some kind exists.” He speculated about “four-dimensional beings” and “human-like intelligences – good or bad daimonia” that might be responsible for events at séances. The Irish physicist Edmund Fournier d’Albe proposed in 1907 that there might exist “infra-men” on the scale of atoms, and drew on the discoveries of radioactivity and the electron to present a “physical theory of immortality.”
Indeed, the discoveries of new ‘invisible rays’, such as X-rays and radioactivity (“Roentgen rays”) bolstered beliefs in unseen universes. William Crookes – one of the most notorious sympathizers of the Spiritualists, mediums and Theosophists of the age – felt that vibrations beyond X-rays might account for telepathy. He too found a striking role for Maxwell’s demon, arguing that it might in effect explain the mystery of radioactive uranium’s seemingly inexhaustible supply of energy. He suggested that uranium atoms might be like demons themselves, mining energy from the surrounding atmosphere by sifting hot gas molecules from cold. “Let uranium or polonium”, he said at the annual meeting of the British Association in 1898, “have a structure that enables them to throw off the slow moving molecules of the atmosphere, while the quick moving molecules, smashing on to the surface, have their energy reduced and that of the target correspondingly increased.” It’s not clear that Crookes thought any intelligent agency was involved here, although he certainly believed in the possibility of invisible beings that have “intelligence, thought, and will, existing without form or matter” – and Maxwell had made clear that intelligence was needed to make the selection among gas molecules.
All this reveals that Maxwell’s demons had a much more ambiguous ontological status than imaginary ‘thought-creatures’. As well as reminding us that even apparently ‘modern’ historical scientists didn’t necessarily see things was we do, it shows how sometimes science doesn’t banish mystical beliefs but offers ‘rational’ justifications for them.
References
1. A. Bérut et al. Nature 483, 187–189 (2012).
2. S. Toyabe, T. Sagawa, M. Ueda, E. Muneyuki & M. Sano, Nat. Phys. 6, 988-992 (2010).
3. J. Earman & J. D. Norton, Stud. Hist. Phil. Mod. Phys. 29, 435-471 (1998) & 30, 1-40 (1999).
4. K. Maruyama, F. Nori & V. Vedral, Rev. Mod. Phys. 81, 1-23 (2009).
Further reading
B. Stewart & P. G. Tait, The Unseen Universe. Macmillan, London, 1875.
R. H. Harman, The Natural Philosophy of James Clerk Maxwell. Cambridge University Press, 1998.
W. H. Brock, William Crookes (1832-1919) and the Commercialization of Science. Ashgate, Aldershot, 2008.
J. Canales & M Krajewski, Interdisciplinary Science Reviews 37, 314-331 (2012).
Monday, March 25, 2013
I'm not a neuroscientist, but I know what I like
Here’s my latest Muse comment for Nature news. I recommend also taking a look at this nice piece by Steven Poole on neuropseudoscience.
__________________________________________________________________
Can brain scans ever tell us why we like art?
No one with even a passing interest in scientific trends will have failed to notice that the brain is the next big thing. That’s been said for at least a decade, but now it’s getting serious, for example with the recent European award of €1 bn to the Human Brain Project to “build a new infrastructure for future neuroscience” and a $1 bn US initiative endorsed by President Obama. Having failed to ‘find ourselves’ in our genome, we’re going looking in the grey matter.
It’s a reasonable objective, but only if we have a clear idea of what we hope and expect to find. Some neuroscientists have grand visions, such as that adduced by Semir Zeki of University College London: “It is only by understanding the neural laws that dictate human activity in all spheres – in law, morality, religion and even economics and politics, no less than in art – that we can ever hope to achieve a more proper understanding of the nature of man [sic].”
Zeki heads the UCL Institute of Neuroesthetics – one of many fields that attaches ‘neuro’ to some human trait with the implication that the techniques of neuroscience, such as functional MRI, will explain it. We have neurotheology, neuroethics, neurocriminology and so on – or in popular media, a rash of books and articles proclaiming (in a profoundly ugly trope) that “this is your brain on drugs/music/religion/sport”.
If anyone is going to pursue neuroaesthetics (my brain refers that spelling), I’d be glad for it to be Zeki, who has a deep and sincere appreciation of art and an awareness of the limits of a scientific approach to the way we experience it. But some of the pitfalls of neuroaesthetics are perceptively expressed by neuroscientist Bevil Conway of Wellesley College, Massachusetts, and musicologist Alexander Rehding of Harvard University in an article in PLoS Biology [1]. They point out that “it is an open question whether an analysis of artworks, no matter how celebrated, will yield universal principles of beauty”, and that “rational reductionist approaches to the neural basis for beauty… may well distill out the very thing one wants to understand.”
For one thing, to suggest that the human brain responds in a particular way to art risks creating criteria of right or wrong, either in the art itself or individual reactions to it. Although it’s a risk most researchers are likely to recognize, experience suggests that scientists studying art find it hard to resist drawing up rules for critical judgements. The Nobel laureate chemist Wilhelm Ostwald, a competent amateur painter, devised an influential theory of colour in the early twentieth century that led him to declare Titian had once used the ‘wrong’ blue. Paul Klee, whose intuitive handling of colour was impeccable, spoke for many artists in his response to such hubris:
"That which most artists have in common, an aversion to colour as a science, became understandable to me when a short time ago I read Ostwald’s theory of colours… Scientists often find art to be childish, but in this case the position is inverted… To hold that the possibility of creating harmony using a tone of equal value should become a general rule means renouncing the wealth of the soul. Thanks but no thanks."
Even if neuroaestheticists refrain from making similar value judgements, they are already close to falling prey to one. Conway and Rehding discuss this field primarily as an attempt to understand how the brain responds to beauty. As they point out, beauty is not a scientific concept – in which case it’s not clear even which questions neuroaesthetics is examining. But the problem is deeper, for equating an appreciation of art with an appreciation of beauty is misleading. A concept of beauty (not necessarily ours today) was certainly important for, say, Renaissance artists, but until recently it had almost vanished from the discourse of contemporary art. Those who like the works of Marcel Duchamp, Joseph Beuys or Robert Rauschenberg generally don’t do so for their beauty. Scientists as a whole have always had conservative artistic tastes; a quest for beauty betrays that little has changed.
Even the narrower matter of aesthetics is not just about beauty. It has traditionally also concerned taste and judgement. Egalitarian scientists have a healthy scepticism of such potentially elitist notions, and it’s true that arbiters of taste may be blinkered and dogmatic: witness the blanket dismissal of jazz by Theodor Adorno, a champion of modernism. But the point is not whether aesthetes are right or wrong, but whether they can offer us stimulating and original ways of seeing, listening, and experiencing. In this regard aesthetics is partly a question of culture and circumstance, not a fundamental quality of the brain. Reducing it to what is shared and general recalls exercises in producing the ‘perfect’ picture or song from poll averages, the results of which are (intentionally) hideous and banal.
And what will a neuroaesthetic ‘explanation’ consist of anyway? Indications so far are that it may be along these lines: “Listening to music activates reward and pleasure circuits in brain regions such as the nucleus accumbens, ventral tegmental area and amygdala”. Thanks but no thanks. And while it is worth knowing that musical ‘chills’ are neurologically akin to the responses invoked by sex or drugs, an approach that cannot distinguish Bach from barbiturates is surely limited.
There surely are generalities in art and our response to it, and they can inform our artistic understanding and experience. But they will never wholly define or explain it.
Reference
1. Conway, B. R. & Rehding, A. PLoS Biology 11, e1001504 (2013).
__________________________________________________________________
Can brain scans ever tell us why we like art?
No one with even a passing interest in scientific trends will have failed to notice that the brain is the next big thing. That’s been said for at least a decade, but now it’s getting serious, for example with the recent European award of €1 bn to the Human Brain Project to “build a new infrastructure for future neuroscience” and a $1 bn US initiative endorsed by President Obama. Having failed to ‘find ourselves’ in our genome, we’re going looking in the grey matter.
It’s a reasonable objective, but only if we have a clear idea of what we hope and expect to find. Some neuroscientists have grand visions, such as that adduced by Semir Zeki of University College London: “It is only by understanding the neural laws that dictate human activity in all spheres – in law, morality, religion and even economics and politics, no less than in art – that we can ever hope to achieve a more proper understanding of the nature of man [sic].”
Zeki heads the UCL Institute of Neuroesthetics – one of many fields that attaches ‘neuro’ to some human trait with the implication that the techniques of neuroscience, such as functional MRI, will explain it. We have neurotheology, neuroethics, neurocriminology and so on – or in popular media, a rash of books and articles proclaiming (in a profoundly ugly trope) that “this is your brain on drugs/music/religion/sport”.
If anyone is going to pursue neuroaesthetics (my brain refers that spelling), I’d be glad for it to be Zeki, who has a deep and sincere appreciation of art and an awareness of the limits of a scientific approach to the way we experience it. But some of the pitfalls of neuroaesthetics are perceptively expressed by neuroscientist Bevil Conway of Wellesley College, Massachusetts, and musicologist Alexander Rehding of Harvard University in an article in PLoS Biology [1]. They point out that “it is an open question whether an analysis of artworks, no matter how celebrated, will yield universal principles of beauty”, and that “rational reductionist approaches to the neural basis for beauty… may well distill out the very thing one wants to understand.”
For one thing, to suggest that the human brain responds in a particular way to art risks creating criteria of right or wrong, either in the art itself or individual reactions to it. Although it’s a risk most researchers are likely to recognize, experience suggests that scientists studying art find it hard to resist drawing up rules for critical judgements. The Nobel laureate chemist Wilhelm Ostwald, a competent amateur painter, devised an influential theory of colour in the early twentieth century that led him to declare Titian had once used the ‘wrong’ blue. Paul Klee, whose intuitive handling of colour was impeccable, spoke for many artists in his response to such hubris:
"That which most artists have in common, an aversion to colour as a science, became understandable to me when a short time ago I read Ostwald’s theory of colours… Scientists often find art to be childish, but in this case the position is inverted… To hold that the possibility of creating harmony using a tone of equal value should become a general rule means renouncing the wealth of the soul. Thanks but no thanks."
Even if neuroaestheticists refrain from making similar value judgements, they are already close to falling prey to one. Conway and Rehding discuss this field primarily as an attempt to understand how the brain responds to beauty. As they point out, beauty is not a scientific concept – in which case it’s not clear even which questions neuroaesthetics is examining. But the problem is deeper, for equating an appreciation of art with an appreciation of beauty is misleading. A concept of beauty (not necessarily ours today) was certainly important for, say, Renaissance artists, but until recently it had almost vanished from the discourse of contemporary art. Those who like the works of Marcel Duchamp, Joseph Beuys or Robert Rauschenberg generally don’t do so for their beauty. Scientists as a whole have always had conservative artistic tastes; a quest for beauty betrays that little has changed.
Even the narrower matter of aesthetics is not just about beauty. It has traditionally also concerned taste and judgement. Egalitarian scientists have a healthy scepticism of such potentially elitist notions, and it’s true that arbiters of taste may be blinkered and dogmatic: witness the blanket dismissal of jazz by Theodor Adorno, a champion of modernism. But the point is not whether aesthetes are right or wrong, but whether they can offer us stimulating and original ways of seeing, listening, and experiencing. In this regard aesthetics is partly a question of culture and circumstance, not a fundamental quality of the brain. Reducing it to what is shared and general recalls exercises in producing the ‘perfect’ picture or song from poll averages, the results of which are (intentionally) hideous and banal.
And what will a neuroaesthetic ‘explanation’ consist of anyway? Indications so far are that it may be along these lines: “Listening to music activates reward and pleasure circuits in brain regions such as the nucleus accumbens, ventral tegmental area and amygdala”. Thanks but no thanks. And while it is worth knowing that musical ‘chills’ are neurologically akin to the responses invoked by sex or drugs, an approach that cannot distinguish Bach from barbiturates is surely limited.
There surely are generalities in art and our response to it, and they can inform our artistic understanding and experience. But they will never wholly define or explain it.
Reference
1. Conway, B. R. & Rehding, A. PLoS Biology 11, e1001504 (2013).
Thursday, March 21, 2013
Buried emotions
One more, this time from the curious world of culturomics, which is also on Nature news.
_________________________________________________________________
Changes in expressions of sentiment can be discerned from Google Books
There’s nothing like having stereotypes confirmed. If you associate contemporary British fiction with the cool, detached tones of Martin Amis and Julian Barnes, and American fiction with the emotional inner worlds explored by Jonathan Franzen or the sentimentality of John Irving, it seems you’ve good reason. An analysis of the digitized texts of English-language books over the past century books concludes that, since the 1980s, emotion terms have become significantly more common in American than British books.
The study [1], by anthropologist Alberto Acerbi of the University of Bristol in England and coworkers, takes advantage of Google’s database of over 5 million digitally scanned books from the past several centuries. This resource has previously been used to examine the evolution of literary styles [2] and trends in literary expressions of individualism [3].
Such mining of the cultural information made available by new technologies has been called ‘culturomics’ [4]. Its advocates believe that these approaches can unearth trends in social opinions and norms that are otherwise concealed within vast swathes of data. “Language use in books reflects what people are talking about and thinking about during a particular time, so Google Books provides a fascinating window into the past”, says psychologist Jean Twenge of San Diego State University, author of Generation Me.
The new results certainly seem to show that familiar narratives about social mood are reflected in the literature (both fiction and non-fiction) of the twentieth century. Acerbi and colleagues find that, while words connoting happy emotions show peaks of usage in the ‘roaring twenties’ and the ‘swinging sixties’, sad words come to the fore during the years of the Second World War.
But there are surprises too: the First World War doesn’t seem to register on this happy-sad index, for example. By this measure, happiness seems to be rising since the 1990s, although it is too early to see whether the global recession will reverse that.
“The relationship between historical events and collective mood is complicated”, Acerbi admits, “but just by doing a somewhat crude analysis of emotion words it is possible to find trends that resonate with what we know about history.” He hopes that further analysis might reveal, for example, whether literature is ahead of its time or only slowly reflect other changes.
“This is a fascinating look at how two cultures have changed over time, especially how world events influence the expression of emotion in media”, says Twenge.
Overall, the use of emotion-related words in English-language books declined over the twentieth century. But when the researchers distinguished books in American and British English (about 1 million and 230,000 respectively), they found that, despite the overall decline, emotion words have become relatively more frequent in the former since about 1980, whereas previously the differences were minor. Such changes were not seen for a random selection of words. “Our results support the popular notion that American authors express more emotions than the British”, they say.
A similar change is seen in the usage of ‘content-free’ words such as pronouns and prepositions (you, us, about, within). Acerbi and colleagues interpret this as indicating that the shift in emotionality is coupled to a general shift in literary style, according to which American texts are increasingly prolix. “The correlation with mood terms is not altogether surprising, as these longer constructions provide increased opportunity for expressing sentiments”, explains biologist David Krakauer of the University of Wisconsin, who has mined Google Books for changes in literary style [2].
“Authors tend to read their contemporaries and their competitors largely within their respective cultures”, he adds, “and so we might expect British English and American English to diverge somewhat”.
Do these shifts imply that the US population in general expresses more emotion than the British? Although that doesn’t necessarily follow – literary norms may sometimes invert rather than mirror tendencies in everyday life – Acerbi feels that these new findings “may reflect a genuine cultural change, because of the size of the sample, and because Google Books is not explicitly biased towards successful or influent books.”
But Krakauer cautions that differences in literary expression don’t necessarily represent differences in the emotional mindscapes behind them. “It is a rather intriguing and open question why different cultures express the same level of feeling with different numbers of words”, he says.
References
1. Acerbi, A, Lampos, V., Garnett, P. & Bentley, R. A. PLoS ONE 8, e59030 (2013).
2. Hughes, J. M.. Foti, N. J., Krakauer, D. C. & Rockmore, D. N. Proc. Natl Acad. Sci. USA 109, 7682-7686 (2012).
3. Twenge, J., Campbell, K. W. & Gentile B. PLoS ONE 7, e40181 (2012).
4. Michel, J.-P. et al., Science 331, 176-182 (2011).
_________________________________________________________________
Changes in expressions of sentiment can be discerned from Google Books
There’s nothing like having stereotypes confirmed. If you associate contemporary British fiction with the cool, detached tones of Martin Amis and Julian Barnes, and American fiction with the emotional inner worlds explored by Jonathan Franzen or the sentimentality of John Irving, it seems you’ve good reason. An analysis of the digitized texts of English-language books over the past century books concludes that, since the 1980s, emotion terms have become significantly more common in American than British books.
The study [1], by anthropologist Alberto Acerbi of the University of Bristol in England and coworkers, takes advantage of Google’s database of over 5 million digitally scanned books from the past several centuries. This resource has previously been used to examine the evolution of literary styles [2] and trends in literary expressions of individualism [3].
Such mining of the cultural information made available by new technologies has been called ‘culturomics’ [4]. Its advocates believe that these approaches can unearth trends in social opinions and norms that are otherwise concealed within vast swathes of data. “Language use in books reflects what people are talking about and thinking about during a particular time, so Google Books provides a fascinating window into the past”, says psychologist Jean Twenge of San Diego State University, author of Generation Me.
The new results certainly seem to show that familiar narratives about social mood are reflected in the literature (both fiction and non-fiction) of the twentieth century. Acerbi and colleagues find that, while words connoting happy emotions show peaks of usage in the ‘roaring twenties’ and the ‘swinging sixties’, sad words come to the fore during the years of the Second World War.
But there are surprises too: the First World War doesn’t seem to register on this happy-sad index, for example. By this measure, happiness seems to be rising since the 1990s, although it is too early to see whether the global recession will reverse that.
“The relationship between historical events and collective mood is complicated”, Acerbi admits, “but just by doing a somewhat crude analysis of emotion words it is possible to find trends that resonate with what we know about history.” He hopes that further analysis might reveal, for example, whether literature is ahead of its time or only slowly reflect other changes.
“This is a fascinating look at how two cultures have changed over time, especially how world events influence the expression of emotion in media”, says Twenge.
Overall, the use of emotion-related words in English-language books declined over the twentieth century. But when the researchers distinguished books in American and British English (about 1 million and 230,000 respectively), they found that, despite the overall decline, emotion words have become relatively more frequent in the former since about 1980, whereas previously the differences were minor. Such changes were not seen for a random selection of words. “Our results support the popular notion that American authors express more emotions than the British”, they say.
A similar change is seen in the usage of ‘content-free’ words such as pronouns and prepositions (you, us, about, within). Acerbi and colleagues interpret this as indicating that the shift in emotionality is coupled to a general shift in literary style, according to which American texts are increasingly prolix. “The correlation with mood terms is not altogether surprising, as these longer constructions provide increased opportunity for expressing sentiments”, explains biologist David Krakauer of the University of Wisconsin, who has mined Google Books for changes in literary style [2].
“Authors tend to read their contemporaries and their competitors largely within their respective cultures”, he adds, “and so we might expect British English and American English to diverge somewhat”.
Do these shifts imply that the US population in general expresses more emotion than the British? Although that doesn’t necessarily follow – literary norms may sometimes invert rather than mirror tendencies in everyday life – Acerbi feels that these new findings “may reflect a genuine cultural change, because of the size of the sample, and because Google Books is not explicitly biased towards successful or influent books.”
But Krakauer cautions that differences in literary expression don’t necessarily represent differences in the emotional mindscapes behind them. “It is a rather intriguing and open question why different cultures express the same level of feeling with different numbers of words”, he says.
References
1. Acerbi, A, Lampos, V., Garnett, P. & Bentley, R. A. PLoS ONE 8, e59030 (2013).
2. Hughes, J. M.. Foti, N. J., Krakauer, D. C. & Rockmore, D. N. Proc. Natl Acad. Sci. USA 109, 7682-7686 (2012).
3. Twenge, J., Campbell, K. W. & Gentile B. PLoS ONE 7, e40181 (2012).
4. Michel, J.-P. et al., Science 331, 176-182 (2011).
Weil to go (OK, so you have to know the pronunciation)
Here’s the initial draft (sort of) of my story for Nature news on the Abel Prize. I blanched when I read the award citation, but in the end this was fun.
_________________________________________________________________
Proof of a deep conjecture about algebra and geometry nets Abel Prize
It has been four decades since Belgian mathematician Pierre Deligne completed the work for which he became celebrated, but that fertile contribution to number theory has now earned him the Abel Prize, one of the most prestigious awards in mathematics.
Given annually by the Norwegian Academy of Science and Letters and named after the famous Norwegian mathematician Niels Henrik Abel, the prize is worth 6 million Norwegian krone, or about US$ 1m.
The Academy has rewarded Deligne, who works at the Institute for Advanced Study in Princeton, New Jersey, “for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields.”
Speaking via webcast on Wednesday, Deligne said he was surprised to learn that he had won the prize. Despite having won major prizes before, he said, he did not spend much time wondering about when the next one would come. “The nice thing about mathematics is doing mathematics,” Deligne said. “The prizes come in addition.”
Deligne has made “many different contributions that have had a huge impact on mathematics for the past 40-50 years”, says Cambridge mathematician Timothy Gowers, who delivered the award address in Olso.
“Usually mathematicians are either theory builders, who develop tools, or problem-solvers, who use those tools to find solutions”, says Peter Sarnak, also at the IAS in Princeton. “Deligne is unusual in being both. He’s got a very special mind.”
Algebraic geometry explores the links between geometric objects and the algebraic equations that describe them – for example, the expression for a circle of radius r, x2+y2=r2. It has proved to have deep connections to many areas of mathematics, particularly the properties of pure integers (number theory).
This last connection is evident in the analogy between the Riemann hypothesis, which describes a relationship between prime numbers, and the so-called Weil conjectures, which were proposed by mathematician André Weil in 1949 – the subject of Deligne’s most famous result.
The Weil conjectures concern objects in algebraic geometry called algebraic varieties, which are the set of solutions of algebraic equations. The number of such solutions can be found from a function called the zeta function. While Riemann’s hypothesis concerns the nature of the Riemann zeta function, which determines how prime numbers are distributed among all the integers, the Weil conjectures specify some of the properties of zeta functions derived from algebraic varieties.
There are four of these conjectures. The first three were proved to be true in the 1960s, but the fourth and hardest – and the direct analogue of the Riemann hypothesis – was proved by Deligne in 1974. The Riemann hypothesis itself remains “the most famous unsolved problems in mathematics”, says Gowers – which is in itself an indication of the significance of Deligne’s proof.
Gowers adds that this proof “completed a long-standing programme” in mathematics. “By solving that”, says Sarnak, “he solved a whole lot of things at once”. For example, the solution also proved a long-standing, recalcitrant conjecture by the famous Indian mathematician Srinivasa Ramanujan.
In finding his proof, Deligne built on the work of his mentor, the German-born mathematician Alexander Grothendieck, who proved the second Weil conjecture in 1965. That work introduced a crucial concept called l-adic cohomology.
The general notion of cohomology, which concerns the topological properties of spaces described by algebraic equations, was itself first developed in the 1920s and 30s, and Weil recognized that it would be needed to prove his hypotheses. Grothendieck laid the foundations for finding the right cohomology, but his student Deligne found the final proof alone – and in a different way from what Grothendieck had imagined.
Deligne’s proof won him the Fields Medal, the “other maths Nobel” besides the Abel Prize, in 1978, and in 1988 he shared the Crafoord Prize with Grothendieck – making him an obvious candidate for the Abel. Since completing the work that secured his reputation, he has applied tools such as l-adic cohomology to extend algebraic geometry and to relate it to other areas of maths. For example, because much of his work is concerned with so-called finite fields – basically modulo arithmetic – it can be applied to the kind of digital logic used in computing. “People in computer science are using his results without even knowing it”, says Sarnak.
“Even if you took away his most famous result on the Weil conjectures”, says Gowers, “you would still be left with a great mathematician.”
Deligne said he had not thought yet about how he would spend the money that came with his Abel Prize, but that he would like to find a way to make it useful for mathematics. “To some extent, I feel that this money belongs to mathematics, not to me.”
_________________________________________________________________
Proof of a deep conjecture about algebra and geometry nets Abel Prize
It has been four decades since Belgian mathematician Pierre Deligne completed the work for which he became celebrated, but that fertile contribution to number theory has now earned him the Abel Prize, one of the most prestigious awards in mathematics.
Given annually by the Norwegian Academy of Science and Letters and named after the famous Norwegian mathematician Niels Henrik Abel, the prize is worth 6 million Norwegian krone, or about US$ 1m.
The Academy has rewarded Deligne, who works at the Institute for Advanced Study in Princeton, New Jersey, “for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields.”
Speaking via webcast on Wednesday, Deligne said he was surprised to learn that he had won the prize. Despite having won major prizes before, he said, he did not spend much time wondering about when the next one would come. “The nice thing about mathematics is doing mathematics,” Deligne said. “The prizes come in addition.”
Deligne has made “many different contributions that have had a huge impact on mathematics for the past 40-50 years”, says Cambridge mathematician Timothy Gowers, who delivered the award address in Olso.
“Usually mathematicians are either theory builders, who develop tools, or problem-solvers, who use those tools to find solutions”, says Peter Sarnak, also at the IAS in Princeton. “Deligne is unusual in being both. He’s got a very special mind.”
Algebraic geometry explores the links between geometric objects and the algebraic equations that describe them – for example, the expression for a circle of radius r, x2+y2=r2. It has proved to have deep connections to many areas of mathematics, particularly the properties of pure integers (number theory).
This last connection is evident in the analogy between the Riemann hypothesis, which describes a relationship between prime numbers, and the so-called Weil conjectures, which were proposed by mathematician André Weil in 1949 – the subject of Deligne’s most famous result.
The Weil conjectures concern objects in algebraic geometry called algebraic varieties, which are the set of solutions of algebraic equations. The number of such solutions can be found from a function called the zeta function. While Riemann’s hypothesis concerns the nature of the Riemann zeta function, which determines how prime numbers are distributed among all the integers, the Weil conjectures specify some of the properties of zeta functions derived from algebraic varieties.
There are four of these conjectures. The first three were proved to be true in the 1960s, but the fourth and hardest – and the direct analogue of the Riemann hypothesis – was proved by Deligne in 1974. The Riemann hypothesis itself remains “the most famous unsolved problems in mathematics”, says Gowers – which is in itself an indication of the significance of Deligne’s proof.
Gowers adds that this proof “completed a long-standing programme” in mathematics. “By solving that”, says Sarnak, “he solved a whole lot of things at once”. For example, the solution also proved a long-standing, recalcitrant conjecture by the famous Indian mathematician Srinivasa Ramanujan.
In finding his proof, Deligne built on the work of his mentor, the German-born mathematician Alexander Grothendieck, who proved the second Weil conjecture in 1965. That work introduced a crucial concept called l-adic cohomology.
The general notion of cohomology, which concerns the topological properties of spaces described by algebraic equations, was itself first developed in the 1920s and 30s, and Weil recognized that it would be needed to prove his hypotheses. Grothendieck laid the foundations for finding the right cohomology, but his student Deligne found the final proof alone – and in a different way from what Grothendieck had imagined.
Deligne’s proof won him the Fields Medal, the “other maths Nobel” besides the Abel Prize, in 1978, and in 1988 he shared the Crafoord Prize with Grothendieck – making him an obvious candidate for the Abel. Since completing the work that secured his reputation, he has applied tools such as l-adic cohomology to extend algebraic geometry and to relate it to other areas of maths. For example, because much of his work is concerned with so-called finite fields – basically modulo arithmetic – it can be applied to the kind of digital logic used in computing. “People in computer science are using his results without even knowing it”, says Sarnak.
“Even if you took away his most famous result on the Weil conjectures”, says Gowers, “you would still be left with a great mathematician.”
Deligne said he had not thought yet about how he would spend the money that came with his Abel Prize, but that he would like to find a way to make it useful for mathematics. “To some extent, I feel that this money belongs to mathematics, not to me.”
Listen up
Here are a couple of podcasts I’ve been involved in recently. First, a programme for the BBC World Service all about black (it’s the 8 Feb episode). Second, a discussion about chemistry, atoms and art broadcast by the journal Leonardo in conjunction with an ebook called Art and Atoms, which is mostly a compilation of interesting papers on the intersections of art and the molecular sciences.
Monday, March 18, 2013
Chinese made easy(er)
Here’s my latest piece for BBC Future. Hmm, will Blogger permit Chinese characters? We’ll see. If you want to find out more about this interesting learning system, there’s some stuff here, but apparently more on the way as the authors figure out how to develop this tool.
________________________________________________________________
There’s no way round it: learning Chinese is tough. As far as reading goes, what most dismays native speakers of alphabetic languages is that Chinese characters offer so few clues. With virtually no Spanish, I can figure out in the right context that baño means bath, but that word in Chinese (洗澡) seems to offer no clues about pronunciation, let alone meaning.
There seems no alternative, then, but to slavishly learn the 3,500 or so characters that account for at least 99% of usage frequency in written Chinese. This is hard even for native Chinese speakers, usually demanding endless rote copying in school. And even then, it is far more common than is often admitted for Chinese people to forget even quite routine characters, such as 钥匙 (key).
Is there a better way? Jinshan Wu of Beijing Normal University, a specialist in the new mathematical science of network theory, and colleagues have investigated the relationships between these 3,500 most used characters to develop a strategy that makes optimal use of the connections to assist learning and memorization.
Chinese characters aren’t really as arbitrary and bewilderingly diverse as they seem at first encounter. For one thing, they are made up of a fairly limited number of sub-characters or radicals, which themselves are composed of a set of standard marks or ‘strokes’. What’s more, the radicals often contain clues about meaning or pronunciation, or both. In the Chinese for bath, for example (pronounced xizao in the pinyin Romanization system), both characters start with the same radical, which denotes ‘water’, and the righthand half of both indicates the pronunciation. There are general rules (called liu shu, 六书) for building characters from radicals.
These connections can be exploited in learning. Once you know that wood is 木 (mu), it’s not so hard to remember that forest is 林 (lin) – or even more pictorially, 森林 (senlin). Assisted by the liu shu rules, Wu and colleagues mapped out the structural relationships between all 3,500 of the common characters, to form a network with over 7,000 links. This shows that the roughly 224 radicals are combined in just 1,000 or so characters that form the basis of all the others.
This network is hierarchical, meaning that it is somewhat like a tree, with a few central nodes (trunks) branching into many branch tips. That’s very different from a web-like network such as a grid or street map, in which there are often many different ways to get to any particular node. The researchers figured that it could be most efficient to start learning at the lower levels of the hierarchy – the trunks, as it were – and to progress gradually out towards the branch tips.
But would that necessarily be better than a strategy which focuses on the most frequently used words first? How, indeed, can one assess the relative learning cost of different strategies? There’s no unique way to do this, but Wu and colleagues developed a logical, intuitive method of enumerating costs. They figured that it is easier to learn a multi-part character if all the components had been learnt previously. To take a simple case, it’s easier to learn 明 (ming: bright) if you have already learnt 日 (ri: sun, day) and 月 (yue: month, moon). The researchers assigned cost values to each ‘new learning’ task.
The ‘cheapest’ way to learn all the characters in the network is then to start with the ‘trunk’ characters that have the highest number of branches, and work up through the layers. But that could leave you knowing a lot of words you rarely need to use. If, on the other hand, you simply learn characters in order of use frequency (as some learning methods do), you fail to take advantage of the network connections that can aid recognition.
The idea approach is a compromise between the two. Wu and colleagues therefore adjust the relationship network by giving a certain weighting or priority to each character depending on its use frequency. Then the learning path spreads gradually through the network while picking up most of the common characters first. It’s rather like planning a shopping trip by seeking a short total path between shops while also contriving to pick up the heaviest items last.
The researchers compared the learning cost of their strategy with that for the most widely used textbook in Chinese primary schools (covering 2,475 characters) and a popular textbook for learning Chinese as a second language. For a given cost, their new strategy picked up both considerably more characters in total and a significantly greater total use frequency than the two alternatives.
What’s more, the researchers say that their approach would allow each student’s learning strategy to be tailored to his or her individual strengths – for example, to suit those who have already learnt some characters. This just isn’t possible with traditional approaches.
Of course, the ultimate test is whether students do actually learn faster. This remains to be seen. But with a debate already raging in China over whether current teaching methods are the most suitable, this new proposal shows that there may be rational ways to pursue the question.
Reference
X. Yan, Y. Fan, Z. Di, S. Havlin & J. Wu, preprint.
________________________________________________________________
There’s no way round it: learning Chinese is tough. As far as reading goes, what most dismays native speakers of alphabetic languages is that Chinese characters offer so few clues. With virtually no Spanish, I can figure out in the right context that baño means bath, but that word in Chinese (洗澡) seems to offer no clues about pronunciation, let alone meaning.
There seems no alternative, then, but to slavishly learn the 3,500 or so characters that account for at least 99% of usage frequency in written Chinese. This is hard even for native Chinese speakers, usually demanding endless rote copying in school. And even then, it is far more common than is often admitted for Chinese people to forget even quite routine characters, such as 钥匙 (key).
Is there a better way? Jinshan Wu of Beijing Normal University, a specialist in the new mathematical science of network theory, and colleagues have investigated the relationships between these 3,500 most used characters to develop a strategy that makes optimal use of the connections to assist learning and memorization.
Chinese characters aren’t really as arbitrary and bewilderingly diverse as they seem at first encounter. For one thing, they are made up of a fairly limited number of sub-characters or radicals, which themselves are composed of a set of standard marks or ‘strokes’. What’s more, the radicals often contain clues about meaning or pronunciation, or both. In the Chinese for bath, for example (pronounced xizao in the pinyin Romanization system), both characters start with the same radical, which denotes ‘water’, and the righthand half of both indicates the pronunciation. There are general rules (called liu shu, 六书) for building characters from radicals.
These connections can be exploited in learning. Once you know that wood is 木 (mu), it’s not so hard to remember that forest is 林 (lin) – or even more pictorially, 森林 (senlin). Assisted by the liu shu rules, Wu and colleagues mapped out the structural relationships between all 3,500 of the common characters, to form a network with over 7,000 links. This shows that the roughly 224 radicals are combined in just 1,000 or so characters that form the basis of all the others.
This network is hierarchical, meaning that it is somewhat like a tree, with a few central nodes (trunks) branching into many branch tips. That’s very different from a web-like network such as a grid or street map, in which there are often many different ways to get to any particular node. The researchers figured that it could be most efficient to start learning at the lower levels of the hierarchy – the trunks, as it were – and to progress gradually out towards the branch tips.
But would that necessarily be better than a strategy which focuses on the most frequently used words first? How, indeed, can one assess the relative learning cost of different strategies? There’s no unique way to do this, but Wu and colleagues developed a logical, intuitive method of enumerating costs. They figured that it is easier to learn a multi-part character if all the components had been learnt previously. To take a simple case, it’s easier to learn 明 (ming: bright) if you have already learnt 日 (ri: sun, day) and 月 (yue: month, moon). The researchers assigned cost values to each ‘new learning’ task.
The ‘cheapest’ way to learn all the characters in the network is then to start with the ‘trunk’ characters that have the highest number of branches, and work up through the layers. But that could leave you knowing a lot of words you rarely need to use. If, on the other hand, you simply learn characters in order of use frequency (as some learning methods do), you fail to take advantage of the network connections that can aid recognition.
The idea approach is a compromise between the two. Wu and colleagues therefore adjust the relationship network by giving a certain weighting or priority to each character depending on its use frequency. Then the learning path spreads gradually through the network while picking up most of the common characters first. It’s rather like planning a shopping trip by seeking a short total path between shops while also contriving to pick up the heaviest items last.
The researchers compared the learning cost of their strategy with that for the most widely used textbook in Chinese primary schools (covering 2,475 characters) and a popular textbook for learning Chinese as a second language. For a given cost, their new strategy picked up both considerably more characters in total and a significantly greater total use frequency than the two alternatives.
What’s more, the researchers say that their approach would allow each student’s learning strategy to be tailored to his or her individual strengths – for example, to suit those who have already learnt some characters. This just isn’t possible with traditional approaches.
Of course, the ultimate test is whether students do actually learn faster. This remains to be seen. But with a debate already raging in China over whether current teaching methods are the most suitable, this new proposal shows that there may be rational ways to pursue the question.
Reference
X. Yan, Y. Fan, Z. Di, S. Havlin & J. Wu, preprint.
Thursday, March 14, 2013
Smoke signals
Ah, there is after all a route to BBC Future from the UK, in which case you can read here a piece I wrote for it yesterday on ‘papal smoke’. It’s now gone white, of course. The main difference in the version below, my original draft, is in the final paragraph, which understandably was a bit near the knuckle for the BBC.
_____________________________________________________________________
There’s something almost poignant in the way the Vatican has had to resort to chemistry to get its archaic method of communicating the papal election results to work properly: science helping to sustain a bizarre tradition from a distant age. Before this week, “fumata nera” and “fumata bianca” meant little to most people outside Italy. But now all eyes are on the copper chimney of the Sistine Chapel, from which the release of black smoke signalled today that the 115 cardinals voting to choose the new pope have not yet reached the two-thirds majority needed to secure a decision. When they do, the smoke will turn white.
The smoke comes partly from the burning of ballot papers in a special stove in the chapel. But to colour it white or black, this smoke is mixed with that from chemical additives burnt in a second stove. Traditionally the Vatican produced the different colours by burning wet straw for white and tarry pitch for black.
Anyone who has ever made a bonfire knows that damp grass will work for the former; the less responsible of you will know that chucking old tyres or roofing felt into the flames will turn the smoke black – and what’s more, noxious, because it is then full of sooty carbon particles that can clog the lungs and are potentially carcinogenic.
It’s not concern for the environment that has led the Vatican to change its ways, however. Rather, the smoke in some previous elections came out an ambiguous grey, prompting the decision for the last conclave in 2005 to use a more reliable method based on chemical ingredients.
The Vatican has now revealed what these are. For black, it uses a mixture of potassium perchlorate, anthracene and sulphur; white comes from potassium chlorate, lactose and the conifer resin called rosin, also used to rub violin strings to give the bow purchase.
We needn’t imagine a team of Vatican chemists labouring like alchemists to devise these magic recipes, because what they really show is that the Vatican is making plain old smoke bombs. A smoke bomb – as well as fireworks designed to be particularly smoky – works by combining an easily burnt carbon-rich compound such as sugar with a so-called oxidizing agent, which provides the oxygen for the combustion reaction. Potassium perchlorate and chlorate (which differ only in precisely how much oxygen they contain) are the most common oxidizers in these applications. Lactose (milk sugar), rosin and anthracene are the sources of carbon – anthracene, found in coal tar, is particularly good for producing big black sooty particles, although it is no longer used in pyrotechnic displays because it is carcinogenic. Sulphur also burns well, and was a traditional component of gunpowder: indeed, the Vatican’s ‘fumata nera’ mix is basically that, with the traditional oxidizer of saltpetre replaced by another.
White smoke for pyrotechnics is more commonly – and reliably – made by burning zinc dust with the organic solvent hexachloroethane and zinc oxide added. It is widely used for military training exercises. But the solvent is poisonous, and the smoke itself can cause liver damage and respiratory problems – so it’s no surprise that the Vatican chose a safer recipe.
In any event, the smoke system now leaves little to chance. Electrical heating of the flue, and backup air fans make sure that the smoke will come pumping out, and the process will surely have been tested to ensure that the black smoke doesn’t turn white as its big sooty flakes break up into smaller particles – an effect sometimes to be seen as bonfire smoke rises.
But aren’t the Vatican being a bit unimaginative and literally monotone here? Why stop at a mere two-colour signalling system? The lurid rainbow smokes used in aerial displays like those of the Red Arrows are tinted with pigments and dyes such as indigo and rhodamine. Couldn’t we have beige smoke to denote a coffee break, pink smoke to tell the world that Cardinals Monteiro de Castro and Sandoval are arguing over homosexuality, or red to indicate that Cardinal Calcagno is threatening to get out his extensive collection of firearms?
Monday, March 11, 2013
Moore's law is not just for computers
Here is my latest news story for Nature.
_______________________________________________________
Mathematical laws make industrial growth and productivity predictable
Predicting the future of technology has often seemed a fool’s game: no one forgets IBM founder Thomas J. Watson’s (possibly apocryphal) prediction that the world would need five computers. But a team of researchers in the USA now says that technological progress really is predictable, and backs up the claim with evidence from 62 different technologies.
It’s not a new claim. But a group of researchers at the Santa Fe Institute in New Mexico and the Massachusetts Institute of Technology in Cambridge, Massachusetts have put to the test several hypothetical mathematical laws describing how the costs of technologies evolve. They find that one proposed as early as 1936 supplies the best fit to the data [1].
That proposal was made by aeronautical engineer Theodore Wright, who pointed out that the cost of airplanes decreased as the total number of planes manufactured (the cumulative production) increased [2]. Specifically, this cost was proportional to the inverse of the cumulative production raised to some power. This has since been put forward as a more general law governing costs of technological products, and is often explained on the basis that, the more we make, the better and more efficient we get at making.
But it’s not the only contender. Much more famous than Wright’s law is the relationship proposed in 1965 by Gordon Moore, cofounder of the microelectronics company Intel. He pointed out that the computer power was increasing exponentially over time [3] – which means, in effect, that the cost per transistor was falling exponentially.
So who is right: Wright or Moore? Perhaps neither, for several other hypothetical relationships between scale and cost of production have been suggested – that, for example, costs fall purely due to economies of scale. All of these ‘laws’ predict that costs tend to fall over time, but at slightly different rates.
“The predictive ability of these hypotheses hadn't been tested against a large dataset before,” says Trancik. She and her colleagues tested six of them by collecting data on 62 technologies, ranging from chemicals production to energy technologies (such as photovoltaic cells) and information technologies, spanning periods of between 10 and 39 years. “Assembling a large enough data set was a big challenge”, says Trancik.
The researchers evaluated the performance of each ‘law’ with hindcasts: using earlier data to make predictions about later costs, and then seeing how these compared with the actual figures. They used statistical methods to figure out which law produced the smallest predictive errors.
And the winner was… Well, in fact there wasn’t a huge difference between any of the laws. The best was Wright’s law, but Moore’s law was close behind, at least for a relatively modest time horizon of a few decades. In fact, their predictions were so similar that the researchers suspected the two laws might be related.
This seems quite likely. In 1979 political scientist Devendra Sahal pointed out that if cumulative production of an item grows exponentially, then Wright’s law and Moore’s law are equivalent [4]. The new data confirm that production does show such growth for a wide range of products. “You wouldn’t necessarily expect that”, says Trancik.
That Moore’s law applies at all to so many different industries is a surprise, since computing has often been regarded as a special case. “It’s a much more general thing”, says coauthor Doyne Farmer, currently at the University of Oxford.
Economist William Nordhaus of Yale University warns that these laws will only work for technologies that survive – which is not itself easy to predict. “History is written only about the victors”, he says. “Those technologies that didn’t make it in the market don't make it into the data set. This is one reason why it is so difficult to forecast which of many nascent energy technologies will survive.”
The future of some technologies will depend crucially on governmental policies, not just conventional market forces. For example, in climate-change technologies, in which Nordhaus specializes, he says that the evolution will depend on the future pricing policies of carbon emissions. “Some technologies, such as carbon capture and storage, won’t even get off the ground with a zero carbon price”, he says.
Estimating the potential costs of climate-change mitigation technologies is one of the prime applications the researchers envisage for their findings. A key question is whether costs will fall just as a matter of time, as Moore’s law implies, or whether stimulating growth by public policies (such as subsidies or taxes) that boost production might accelerate the fall, as Wright’s law implies.
The results seem to imply the latter, which is good news. “We have more control over these things than we might think”, says Farmer.
References
1. Nagy, B., Farmer, J. D., Bui, Q. M. & Trancik, J. E. PLoS ONE 8, e52669 (2013). [doi:10.1371/journal.pone.0052669]
2. Wright, T. P. J. Aeronaut. Sci. 10, 302-328 (1936).
3. Moore, G. E. Electr. Mag. 38 (1965).
4. Sahal, D. AIIE Trans. 11, 23-29 (1979).
_______________________________________________________
Mathematical laws make industrial growth and productivity predictable
Predicting the future of technology has often seemed a fool’s game: no one forgets IBM founder Thomas J. Watson’s (possibly apocryphal) prediction that the world would need five computers. But a team of researchers in the USA now says that technological progress really is predictable, and backs up the claim with evidence from 62 different technologies.
It’s not a new claim. But a group of researchers at the Santa Fe Institute in New Mexico and the Massachusetts Institute of Technology in Cambridge, Massachusetts have put to the test several hypothetical mathematical laws describing how the costs of technologies evolve. They find that one proposed as early as 1936 supplies the best fit to the data [1].
That proposal was made by aeronautical engineer Theodore Wright, who pointed out that the cost of airplanes decreased as the total number of planes manufactured (the cumulative production) increased [2]. Specifically, this cost was proportional to the inverse of the cumulative production raised to some power. This has since been put forward as a more general law governing costs of technological products, and is often explained on the basis that, the more we make, the better and more efficient we get at making.
But it’s not the only contender. Much more famous than Wright’s law is the relationship proposed in 1965 by Gordon Moore, cofounder of the microelectronics company Intel. He pointed out that the computer power was increasing exponentially over time [3] – which means, in effect, that the cost per transistor was falling exponentially.
So who is right: Wright or Moore? Perhaps neither, for several other hypothetical relationships between scale and cost of production have been suggested – that, for example, costs fall purely due to economies of scale. All of these ‘laws’ predict that costs tend to fall over time, but at slightly different rates.
“The predictive ability of these hypotheses hadn't been tested against a large dataset before,” says Trancik. She and her colleagues tested six of them by collecting data on 62 technologies, ranging from chemicals production to energy technologies (such as photovoltaic cells) and information technologies, spanning periods of between 10 and 39 years. “Assembling a large enough data set was a big challenge”, says Trancik.
The researchers evaluated the performance of each ‘law’ with hindcasts: using earlier data to make predictions about later costs, and then seeing how these compared with the actual figures. They used statistical methods to figure out which law produced the smallest predictive errors.
And the winner was… Well, in fact there wasn’t a huge difference between any of the laws. The best was Wright’s law, but Moore’s law was close behind, at least for a relatively modest time horizon of a few decades. In fact, their predictions were so similar that the researchers suspected the two laws might be related.
This seems quite likely. In 1979 political scientist Devendra Sahal pointed out that if cumulative production of an item grows exponentially, then Wright’s law and Moore’s law are equivalent [4]. The new data confirm that production does show such growth for a wide range of products. “You wouldn’t necessarily expect that”, says Trancik.
That Moore’s law applies at all to so many different industries is a surprise, since computing has often been regarded as a special case. “It’s a much more general thing”, says coauthor Doyne Farmer, currently at the University of Oxford.
Economist William Nordhaus of Yale University warns that these laws will only work for technologies that survive – which is not itself easy to predict. “History is written only about the victors”, he says. “Those technologies that didn’t make it in the market don't make it into the data set. This is one reason why it is so difficult to forecast which of many nascent energy technologies will survive.”
The future of some technologies will depend crucially on governmental policies, not just conventional market forces. For example, in climate-change technologies, in which Nordhaus specializes, he says that the evolution will depend on the future pricing policies of carbon emissions. “Some technologies, such as carbon capture and storage, won’t even get off the ground with a zero carbon price”, he says.
Estimating the potential costs of climate-change mitigation technologies is one of the prime applications the researchers envisage for their findings. A key question is whether costs will fall just as a matter of time, as Moore’s law implies, or whether stimulating growth by public policies (such as subsidies or taxes) that boost production might accelerate the fall, as Wright’s law implies.
The results seem to imply the latter, which is good news. “We have more control over these things than we might think”, says Farmer.
References
1. Nagy, B., Farmer, J. D., Bui, Q. M. & Trancik, J. E. PLoS ONE 8, e52669 (2013). [doi:10.1371/journal.pone.0052669]
2. Wright, T. P. J. Aeronaut. Sci. 10, 302-328 (1936).
3. Moore, G. E. Electr. Mag. 38 (1965).
4. Sahal, D. AIIE Trans. 11, 23-29 (1979).
Cloud control
Here’s my latest piece for BBC Future.
________________________________________________________________
It’s quite a promise. Using existing technology, we could engineer the clouds “to cancel the entire warming caused by human activity from pre-industrial times to present day”. But this, the latest of many ‘geo-engineering’ proposals to mitigate climate change, has a drawback. Get it only a bit wrong, and you make the problem worse.
That, however, has been the worry with such ‘techno-fixes’ all along. We could fire a fleet of little mirrors into an orbit around the Sun that locks them in place to deflect sunlight from the Earth. But if it goes wrong, we could be plunged into an ice age. Manipulating the clouds has been a popular idea with would-be geo-engineers, but these proposals face the fact that the climate effects of clouds are among the hardest parts of the climate system to understand and predict, so we can’t be too sure what the results will be.
The new suggestion examined by climate scientist Trude Storelvmo of Yale University and her coworkers targets one particular kind of cloud: the cirrus ice clouds that extend their wispy tendrils in the upper troposphere, at altitudes of about 5-15 kilometres. The researchers say that these thin clouds are known with confidence to have a net warming effect on our planet, since their ice crystals trap infrared radiation from the sun-warmed surface and re-emit it back down towards ground. So if we can make cirrus still thinner, we’ll let out more heat and cool the globe.
This idea was first suggested in 2009 by David Mitchell and William Finnegan of the Desert Research Institute in Nevada (D. Mitchell & W. Finnegan, Environmental Research Letters 4, 045102 (2009)). It relies on a rather counterintuitive effect: to reduce the warming influence of cirrus cloud, one should add to the upper troposphere tiny ‘seed’ particles that actually encourage the formation of the ice crystals from which the clouds are made.
So how does that work? The ice crystals of cirrus clouds generally form spontaneously in moist, cold air. But seed particles, if present in the right concentration in the air, could grab all the water vapour to produce a small number of large ice crystals, preventing the formation of lots of unseeded little ones. This would have two consequences. First, the resulting clouds would be more transparent, just as big blobs of water in oil create a more transparent mixture as salad dressing separates out, compared with the milky, opaque mixture you get when you shake it into lots of tiny droplets. The thinner clouds absorb less radiation from the warm ground, allowing more to escape into space.
Second, clouds made from larger ice particles have shorter lives, because the big crystals sink down through the atmosphere under gravity.
This wasn’t by any means the first proposal for geo-engineering climate by modifying the reflection or absorption of light in the atmosphere. For example, British meteorologist John Latham and coworkers have suggested that a fleet of solar-powered ships might spray sea salt into the air to seed the formation of stratocumulus clouds, which cool the planet by reflecting sunlight (J. Latham, Nature 347, 339 (1990)). And climate scientist Paul Crutzen has proposed injecting a sulphur-containing gas into the stratosphere, which would form a haze of sulphate particles to reflect sunlight – a process that happens naturally in volcanic eruptions and which is known to cool the earth (P. J. Crutzen, Climatic Change 77, 211 (2006)).
One of the advantages of climate engineering via clouds is that the effects are transient: if it doesn’t go to plan, the process can be stopped and all will return to normal in a matter of weeks. Mitchell and Finnegan suggested that seeding of cirrus cloud might be done by releasing the particles from aircraft. They suggested that the somewhat exotic (but not excessively costly) compound bismuth tri-iodide would be a good material for the seeds, as it is known to promote ice formation on its surface.
But will it work as planned? That’s what Storelvmo and colleagues have now studied by using a climate model that incorporates a description of cirrus cloud formation. They find that to get climate cooling, one has to use just the right concentration of seed particles. Too few, and cirrus clouds form just as they do normally. But if there are too many seeds, they generate more ice crystals than would have formed in their absence, and the clouds are actually thicker, trapping even more heat.
If we get the seed concentration right, the effect is dramatic: the cooling is enough to offset all global warming. But this ‘Goldilocks’ window is quite narrow. What’s more, the researchers say, finding the precise boundaries of the window requires more information than we have at present, for example about the ability of bismuth tri-iodide to seed ice formation and the rates at which the ice crystals will settle through the atmosphere. So attempting this sort of engineering prematurely could backfire – even if the effect would be quite short-lived, we should hold fire until we know more.
Reference
T. Storelvmo et al., Geophys. Res. Lett. 40, 178-182 (2013).
________________________________________________________________
It’s quite a promise. Using existing technology, we could engineer the clouds “to cancel the entire warming caused by human activity from pre-industrial times to present day”. But this, the latest of many ‘geo-engineering’ proposals to mitigate climate change, has a drawback. Get it only a bit wrong, and you make the problem worse.
That, however, has been the worry with such ‘techno-fixes’ all along. We could fire a fleet of little mirrors into an orbit around the Sun that locks them in place to deflect sunlight from the Earth. But if it goes wrong, we could be plunged into an ice age. Manipulating the clouds has been a popular idea with would-be geo-engineers, but these proposals face the fact that the climate effects of clouds are among the hardest parts of the climate system to understand and predict, so we can’t be too sure what the results will be.
The new suggestion examined by climate scientist Trude Storelvmo of Yale University and her coworkers targets one particular kind of cloud: the cirrus ice clouds that extend their wispy tendrils in the upper troposphere, at altitudes of about 5-15 kilometres. The researchers say that these thin clouds are known with confidence to have a net warming effect on our planet, since their ice crystals trap infrared radiation from the sun-warmed surface and re-emit it back down towards ground. So if we can make cirrus still thinner, we’ll let out more heat and cool the globe.
This idea was first suggested in 2009 by David Mitchell and William Finnegan of the Desert Research Institute in Nevada (D. Mitchell & W. Finnegan, Environmental Research Letters 4, 045102 (2009)). It relies on a rather counterintuitive effect: to reduce the warming influence of cirrus cloud, one should add to the upper troposphere tiny ‘seed’ particles that actually encourage the formation of the ice crystals from which the clouds are made.
So how does that work? The ice crystals of cirrus clouds generally form spontaneously in moist, cold air. But seed particles, if present in the right concentration in the air, could grab all the water vapour to produce a small number of large ice crystals, preventing the formation of lots of unseeded little ones. This would have two consequences. First, the resulting clouds would be more transparent, just as big blobs of water in oil create a more transparent mixture as salad dressing separates out, compared with the milky, opaque mixture you get when you shake it into lots of tiny droplets. The thinner clouds absorb less radiation from the warm ground, allowing more to escape into space.
Second, clouds made from larger ice particles have shorter lives, because the big crystals sink down through the atmosphere under gravity.
This wasn’t by any means the first proposal for geo-engineering climate by modifying the reflection or absorption of light in the atmosphere. For example, British meteorologist John Latham and coworkers have suggested that a fleet of solar-powered ships might spray sea salt into the air to seed the formation of stratocumulus clouds, which cool the planet by reflecting sunlight (J. Latham, Nature 347, 339 (1990)). And climate scientist Paul Crutzen has proposed injecting a sulphur-containing gas into the stratosphere, which would form a haze of sulphate particles to reflect sunlight – a process that happens naturally in volcanic eruptions and which is known to cool the earth (P. J. Crutzen, Climatic Change 77, 211 (2006)).
One of the advantages of climate engineering via clouds is that the effects are transient: if it doesn’t go to plan, the process can be stopped and all will return to normal in a matter of weeks. Mitchell and Finnegan suggested that seeding of cirrus cloud might be done by releasing the particles from aircraft. They suggested that the somewhat exotic (but not excessively costly) compound bismuth tri-iodide would be a good material for the seeds, as it is known to promote ice formation on its surface.
But will it work as planned? That’s what Storelvmo and colleagues have now studied by using a climate model that incorporates a description of cirrus cloud formation. They find that to get climate cooling, one has to use just the right concentration of seed particles. Too few, and cirrus clouds form just as they do normally. But if there are too many seeds, they generate more ice crystals than would have formed in their absence, and the clouds are actually thicker, trapping even more heat.
If we get the seed concentration right, the effect is dramatic: the cooling is enough to offset all global warming. But this ‘Goldilocks’ window is quite narrow. What’s more, the researchers say, finding the precise boundaries of the window requires more information than we have at present, for example about the ability of bismuth tri-iodide to seed ice formation and the rates at which the ice crystals will settle through the atmosphere. So attempting this sort of engineering prematurely could backfire – even if the effect would be quite short-lived, we should hold fire until we know more.
Reference
T. Storelvmo et al., Geophys. Res. Lett. 40, 178-182 (2013).
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