Science

The Finnish capital has announced plans to transform its existing public transport network into a comprehensive, point-to-point “mobility on demand” system by 2025 – one that, in theory, would be so good nobody would have any reason to own a car.

Helsinki aims to transcend conventional public transport by allowing people to purchase mobility in real time, straight from their smartphones. The hope is to furnish riders with an array of options so cheap, flexible and well-coordinated that it becomes competitive with private car ownership not merely on cost, but on convenience and ease of use.

Subscribers would specify an origin and a destination, and perhaps a few preferences. The app would then function as both journey planner and universal payment platform, knitting everything from driverless cars and nimble little buses to shared bikes and ferries into a single, supple mesh of mobility. Imagine the popular transit planner Citymapper fused to a cycle hire service and a taxi app such as Uber, with only one payment required, and the whole thing run as a public utility, and you begin to understand the scale of ambition here.

The story is here, via s.  Here is a further and very different installment in The Culture that is Finland, nice visual on the igloos.  Or try this Finland Bitcoin link, blockchain-by-air.

The editors are Dow James and Glen Whitman and the subtitle is Zombies, Vampires, and the Dismal Science.  Authors include Steven Horwitz, Sarah Skwire, Ilya Somin, and also Hollis Robbins, “Killing Time, Dracula and Social Coordination”, among others.

From Jason Mitchell at Harvard:

Recent hand-wringing over failed replications in social psychology is largely pointless, because unsuccessful experiments have no meaningful scientific value.

Because experiments can be undermined by a vast number of practical mistakes, the likeliest explanation for any failed replication will always be that the replicator bungled something along the way. Unless direct replications are conducted by flawless experimenters, nothing interesting can be learned from them.

Three standard rejoinders to this critique are considered and rejected. Despite claims to the contrary, failed replications do not provide meaningful information if they closely follow original methodology; they do not necessarily identify effects that may be too small or flimsy to be worth studying; and they cannot contribute to a cumulative understanding of scientific phenomena.

Replication efforts appear to reflect strong prior expectations that published findings are not reliable, and as such, do not constitute scientific output.

The field of social psychology can be improved, but not by the publication of negative findings.   Experimenters should be encouraged to restrict their “degrees of freedom,” for example, by specifying designs in advance.

Whether they mean to or not, authors and editors of failed replications are publicly impugning the scientific integrity of their colleagues. Targets of failed replications are justifiably upset, particularly given the inadequate basis for replicators’ extraordinary claims.

The full piece is here, I don’t quite buy it but a useful counter-tonic to a lot of current rhetoric.  I found this in my Twitter feed, but I forget whom to thank, sorry!

Addendum: An MR reader sends along this related argument.

People, and especially men, hate being alone with their thoughts so much that they’d rather be in pain. In a study published in Science  Thursday on the ability of people to let their minds “wander” — that is, for them to sit and do nothing but think — researchers found that about a quarter of women and two-thirds of men chose electric shocks over their own company.

“We went into this thinking that mind wandering wouldn’t be that hard,” said Timothy Wilson, University of Virginia professor of psychology and lead author of the study. “People usually think of mind wandering as being a bad thing, because it interrupts when you’re trying to pay attention. But we wanted to see what happens when mind wandering is the goal.”

Wilson didn’t think his subjects would struggle with the task. “We have this big brain full of pleasant memories, and we’re able to tell ourselves stories and make up fantasies. But despite that, we kept finding that people didn’t like it much and found it hard.”

The full story is here.  Among other issues, I believe this has implications for how Principles of Economics should be taught.

For the pointer I thank Samir Varma.

That is a new paper by Henrik Cronqvist and Stephan Siegel, here is the abstract:

For a long list of investment “biases,” including lack of diversification, excessive trading, and the disposition effect, we find that genetic differences explain up to 45% of the remaining variation across individual investors, after controlling for observable individual characteristics. The evidence is consistent with a view that investment biases are manifestations of innate and evolutionary ancient features of human behavior. We find that work experience with finance reduces genetic predispositions to investment biases. Finally, we find that even genetically identical investors, who grew up in the same family environment, often differ substantially in their investment behaviors due to individual-specific experiences or events.

Hat tip goes to Kevin Lewis.  There is an ungated copy here.

There is a new NBER working paper with that title, by S. Borağan Aruoba and Jesus Fernandez-Villaverde. Here is the abstract:

We solve the stochastic neoclassical growth model, the workhorse of modern macroeconomics, using C++11, Fortran 2008, Java, Julia, Python, Matlab, Mathematica, and R. We implement the same algorithm, value function iteration with grid search, in each of the languages. We report the execution times of the codes in a Mac and in a Windows computer and comment on the strength and weakness of each language.

Here are their results:

1. C++ and Fortran are still considerably faster than any other alternative, although one needs to be careful with the choice of compiler.

2. C++ compilers have advanced enough that, contrary to the situation in the 1990s and some folk wisdom, C++ code runs slightly faster (5-7 percent) than Fortran code.

3. Julia, with its just-in-time compiler, delivers outstanding per formance. Execution speed is only between 2.64 and 2.70 times the execution speed of the best C++ compiler.

4. Baseline Python was slow. Using the Pypy implementation, it runs around 44 times slower than in C++. Using the default CPython interpreter, the code runs between 155 and 269 times slower than in C++.

5. However, a relatively small rewriting of the code and the use of Numba (a just-in-time compiler for Python that uses decorators) dramatically improves Python ’s performance: the decorated code runs only between 1.57 and 1.62 times slower than the best C++ executable.

6.Matlab is between 9 to 11 times slower than the best C++ executable. When combined with Mex files, though, the difference is only 1.24 to 1.64 times.

7. R runs between 500 to 700 times slower than C++ . If the code is compiled, the code is between 240 to 340 times slower.

8. Mathematica can deliver excellent speed, about four times slower than C++, but only after a considerable rewriting of the code to take advantage of the peculiarities of the language. The baseline version our algorithm in Mathematica is much slower, even after taking advantage of Mathematica compilation.

There are ungated copies and some discussion here.

Facebook manipulated the emotions of hundreds of thousands of its users, and found that they would pass on happy or sad emotions, it has said. The experiment, for which researchers did not gain specific consent, has provoked criticism from users with privacy and ethical concerns.

For one week in 2012, Facebook skewed nearly 700,000 users’ news feeds to either be happier or sadder than normal. The experiment found that after the experiment was over users’ tended to post positive or negative comments according to the skew that was given to their newsfeed.

The research has provoked distress because of the manipulation involved.

Clearly plenty of ads try to manipulative us with positive emotions, and without telling us.  There are also plenty of sad songs, or for that matter sad movies and sad advertisements, again running an agenda for their own manipulative purposes.  Is the problem with Facebook its market power?  Or is the the sheer and unavoidable transparency of the notion that Facebook is inducing us to pass along similar emotions to our network of contacts, thus making us manipulators too, and in a way which is hard to us to avoid thinking about?  What would Robin Hanson say?

Note by the way that “The effect the study documents is very small, as little as one-tenth of a percent of an observed change.”  How much that eventually dwindles, explodes, or dampens out in the longer run I would say is still not known to us.  My intuition however is that we see a lot of longer-run dampening and also intertemporal substitution of emotions, meaning this is pretty close to a non-event.

The initial link is here.  The underlying study is here.  Other readings on the topic are here.

I hope you’re not too sad about this post [smiley face]!

How Not to Bet

by on June 26, 2014 at 7:10 am in Economics, Science | Permalink

Tim Harford writes of bets:

Pundits who make wagers may look grubby but at least they are accepting a cost for failure. A more subtle advantage is that betting encourages forecasts that are specific and quantifiable.

Exactly, but not all bets are well considered. Consider the following from Christopher Keating:

I have heard global warming skeptics make all sorts of statements about how the science doesn’t support claims of man-made climate change. I have found all of those statements to be empty and without any kind of supporting evidence. I have, in turn, stated that it is not possible for the skeptics to prove their claims. And, I’m willing to put my money where my mouth is.

I am announcing the start of the $10,000 Global Warming Skeptic Challenge. The rules are easy:

1. I will award $10,000 of my own money to anyone that can prove, via the scientific method, that man-made global climate change is not occurring;

…5. I am the final judge of all entries but will provide my comments on why any entry fails to prove the point.

This is a poorly constructed bet. Notice first that the preamble, “empty”, “without any kind of supporting evidence”, “prove,” is simply unscientific bluster. Scientific thinking is Bayesian. (Appropriately, I first saw Keating’s bet flagged on the blog Prior Probability.) In contrast, this talk is suggestive of someone who doesn’t weigh evidence, a point of some importance given that he writes “I am the final judge of all entries…”. Keating is really betting that no one will change his mind and that’s not a bet that I would want to take.

Second, what counts as proof? And what does it mean to say that man-made global climate change is not occurring. How much is man made? How fast is it occurring? What are the costs? What are the benefits? Keating’s challenge is vague and poorly worded.

For an example of a much better bet consider the Caplan-Bauman bet on temperature change over the next 15 years. Caplan has agreed to pay Bauman $333.33 if the average temperature over the period 2015-2029 is more than .05C greater than the average temperature over 2000-2014 as measured by the National Climatic Data Center. If the average temperature increase over that time frame is less than .05c then Bauman will pay Caplan $1000. 

The Caplan-Bauman bet is quantifiable and specific and it contains odds, as it should since Bauman expresses much greater certainty in his belief than Caplan.

Keating seems even more certain in his beliefs than Bauman. But how certain? Will he accept my offer of the same bet at 5:1 odds?

Mr. Econotarian wrote:

Actual science is that your brain can be gendered during development in a different fashion than your sex chromosomes. And that gender is not something that hormones alone can “fix”.

For example, the forceps minor (part of the corpus callosum, a mass of fibers that connect the brain’s two hemispheres) – among nontranssexuals, the forceps minor of males contains parallel nerve fibers of higher density than in females. But the density in female-to-male transsexuals is equivalent to that in typical males.

As another example, the hypothalamus, a hormone-producing part of the brain, is activated in nontranssexual men by the scent of estrogen, but in women—and male-to-female transsexuals—by the scent of androgens, male-associated hormones.

I would stress a social point.  If it turns out you are born “different” in these ways (I’m not even sure what are the right words to use to cover all the relevant cases), what is the chance that your social structure will be supportive?  Or will you feel tortured, mocked, and out of place?  Might you even face forced institutionalization, as McCloskey was threatened with?  Most likely things will not go so well for you, even in an America of 2014 which is far more tolerant overall than in times past, including on gay issues.  Current attitudes toward transsexuals and other related groups remain a great shame.  A simple question is how many teenagers have been miserable or even committed suicide or have had parts of their lives ruined because they were born different in these ways and did not find the right support structures early on or perhaps ever.  And if you are mocking individuals for their differences in this regard, as some of you did in the comments thread, I will agree with Barkley Rosser’s response: “Some of you people really need to rethink who you are.  Seriously.”

Some of you people really need to rethink who you are. Seriously. – See more at: http://marginalrevolution.com/marginalrevolution/2014/06/what-do-i-think-of-david-brat.html#comments

It’s not just the libertarian argument that you have — to put it bluntly — the “right to cut off your dick” (though you do).  It’s that there are some very particular circles of humanity, revolving around transsexuality, cross-gender, and related notions, which deserve a culture of respect, above and beyond mere legal tolerance.

India is not the paradise for cross- and multiple-gender individuals that it is sometimes made out to be, but still we could learn a good deal from them on these issues.  If nothing else, the argument from ignorance ought to weigh heavily here: there is plenty about these categories which we as a scientific community do not understand, and which you and I as individuals probably understand even less.  So in the meantime should we not extend maximum tolerance for individuals whose lives are in some manner different?

No, I do not know what are the appropriate set of public policies for when children should receive treatment, if they consistently express a desire to change, and what are the relative limits of family and state in these matters.  But if we start with tolerance and acceptance, and encourage a culture of respect for transsexualism, we are more likely to come up with the right policy answers, and also to minimize the damage if in the meantime we cannot quite figure out when to do what.

All hail Khan!

by on June 14, 2014 at 10:58 am in Current Affairs, Law, Religion, Science | Permalink

Congratulations to Razib Khan, the noted genetics blogger, on the birth of his son. Born just last week, Razib’s son is already making the news:

An infant delivered last week in California appears to be the first healthy person ever born in the U.S. with his entire genetic makeup deciphered in advance.

Razib, a graduate student at a lab at UC Davis in California, had some genetic material from his in-womb son from a fairly standard CVS test.

When Khan got the DNA earlier this year, he could have ordered simple tests for specific genes he was curious about. But why not get all the data? “At that point, I realized it was just easier to do the whole genome,” he says. So Khan got a lab mate to place his son’s genetic material in a free slot in a high-speed sequencing machine used to study the DNA of various animal species. “It’s mostly metazoans, fish, and plants. He was just one of the samples in there,” he says.

The raw data occupied about 43 gigabytes of disk space, and Khan set to work organizing and interpreting it. He did so using free online software called Promethease, which crunches DNA data to build reports—noting genetic variants of interest and their medical meaning. “I popped him through Promethease and got 7,000 results,” says Khan.

Promethease is part of an emerging do-it-yourself toolkit for people eager to explore DNA without a prescription. It’s not easy to use, but it’s become an alternative since the FDA cracked down on 23andMe.

Craig Venter was the first person to have his genome sequenced, that was in 2007. Now, just seven years later, costs have fallen by a factor of 10,000.  Personal genome sequencing is going to become routine regardless of the FDA.

NASA has a call for research in the economics of space exploration:

This NRA seeks empirical economic research projects, historical analog research, concepts for
encouraging further economic activity in space, and unique stimulatory activities that promote
novel private/commercial uses of space, new private/commercial space opportunities, and
emerging private/commercial capabilities in suborbital, orbital or deep space environments that
enable discoveries, development and applications from these environments.

Specific topics of interest include:

  • Historical Economic Studies in the following areas:
  1. Economic history of NASA programs;
  2. Long term historical impact of the space program;
  3. Economic and business histories of American private sector space enterprises (including companies, societies, and projects);
  4. Economic histories of historical analog activities for space exploration (including detailed investigations into the financing of historical expeditions, settlements, and transportation infrastructure projects).
  • Current and Near-Term Trends, Analyses and Concepts for accelerating American space development, in the following areas:
  1. Utilizing market mechanisms, private sector partnerships, and expanding markets to serve non-traditional commercial entities;
  2. Promoting broader uses of space for public and/or economic benefit, including job creation and/or workforce development, and maintaining American leadership in the global space marketplace;
  3. Encouraging engagement on space activities from citizen makers, crowd-funders, citizen explorers, and participation of innovators from non-traditional sectors that can have a transformative effect on future private/commercial space developments;
  4. Identifying and evaluating economic applications of space systems design to earth-scale economic analysis, including integrated modeling of globalized economic systems and earth systems science;
  5. Examining competitive stresses, potentials for public benefit, and issues affecting NASA or the nation in the commercial space arena;
  6. Monitoring, investigating and reporting on opportunities enabled by the rapidly growing national and international entrepreneurial space communities;
  7. Assessing the adequacy of economic assessment and evaluation tools and methods for space architectures;
  8. Conducting case studies of space development projects that can be used to inform NASA on the opportunities and impediments to economic development in space.
  • Economics, Systems Analysis, and Projections, in orbital and deep space development; lunar development, asteroid development, and Mars development.

Upon testing, the system developed by Bartlett managed—in real time—to identify 20 of the 46 facial movements described in the FACS, according to a March report by Bartlett in Current Biology. And, even more impressive, the system not only identifies, but distinguishes authentic expressions from false expressions with an accuracy rate of 85 percent, at least in laboratory settings where the visual conditions are held constant. Humans weren’t nearly as skilled, logging an accuracy rate of about 55 percent.

Yes, Bartlett incorporated a lie detector into the facial recognition technology. This technology promises to catch in the act anyone who tries to fake a given emotion or feeling. Facial recognition is evolving into emotional recognition, but computers—not just people—are the ones deciding what’s real. ( If we add voice detection to face recognition, we end up with a complete lie detection package.)

…So we can begin to imagine a near future in which we’re equipped with glasses that not only recognize faces and voices, but also truths and lies—a scenario that would provoke a revolution in human interaction. It would also constitute a serious limitation on the individual’s autonomy.

Speculative, but we can expect these techniques to improve.

Do you ever say “Rats!” after making a mistake?  It now has a whole new meaning:

They [scientists] developed a task called Restaurant Row, in which rats decided how long they were willing to wait for different foods during a 60-minute run.

“It’s like waiting in line at the restaurant,” Prof Redish. “If the line is too long at the Chinese restaurant, then you give up and go to the Indian restaurant across the street.”

The rats waited longer for their preferred flavours, meaning the researchers could determine good and bad food options.

Occasionally the rats decided not to wait for a good option and moved on, only to find themselves facing a bad option – the scientists called this a regret-inducing situation.

In these cases the rats often paused and looked back at the reward they had passed over.

They also made changes in their subsequent decisions, being more likely to wait at the next zone and rushing to eat the reward that followed. The scientists say such behaviour is consistent with the expression of regret.

When experiments were carried out where the rats encountered bad options without making incorrect decisions, such behaviour was not present.

The article is here, the paper is here, all via Michelle Dawson.

A programme that convinced humans that it was a 13-year-old boy has become the first computer ever to pass the Turing Test. The test — which requires that computers are indistinguishable from humans — is considered a landmark in the development of artificial intelligence, but academics have warned that the technology could be used for cybercrime.

…Eugene Goostman, a computer programme made by a team based in Russia, succeeded in a test conducted at the Royal Society in London. It convinced 33 per cent of the judges that it was human, said academics at the University of Reading, which organised the test.

It is thought to be the first computer to pass the iconic test. Though there have claims other programmes have successes, those included set topics or question in advance.

A version of the computer programme, which was created in 2001, is hosted online for anyone talk to. (“I feel about beating the turing test in quite convenient way. Nothing original,” said Goostman, when asked how he felt after his success.)

The computer programme claims to be a 13-year-old boy from Odessa in Ukraine.

So far I am withholding judgment.  There is more here, lots of Twitter commentary here.  By the way, here is my 2009 paper with Michelle Dawson on what the Turing test really means (pdf).

He wrote:

[When] computers acquire the necessary capabilities…speeded-up data processing and interpretation will be necessary if professional services are to be rendered with any adequacy.  Once the computers are in operation, the need for additional professional people may be only moderate…

There will be a small, almost separate, society of people in rapport with the advanced computers.  These cyberneticians will have established a relationship with their machines that cannot be shared with the average man any more than the average man today can understand the problems of molecular biology, nuclear physics, or neuropsychiatry.  Indeed, many scholars will not have the capacity to share their knowledge or feeling about this new man-machine relationship.  Those with the talent for the work probably will have to develop it from childhood and will be trained as intensively as the classical ballerina.

Michael then discusses what will happen to those people who cannot work productively with the machines.  Some will still work in person-to-person interactions, but the others will end up in government-designed public tasks and work short hours and subsist on the public dole.  He also considers the possibility of sending some of these individuals to poorer countries where automation is not so far advanced.

Michael wrote all of that and more in his book Cybernation: The Silent Conquest in…1962.