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How Smartphones Could Keep Psychology From Getting Too WEIRD

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In 2004, I was a lab rat for about 15 minutes. A psychology professor at Juniata College, where I spent my freshman year, was conducting an experiment. I don’t remember what exactly he was studying, but it involved video games. He put up posters around campus and gathered a bunch of volunteers in a campus building basement to frag each other in several rounds of Unreal Tournament. I lost pretty quickly, but did my part. I think I got a game store gift card for my time.

Now ideally, if you want to learn anything useful about human brains and behavior, you try to get a large and diverse group of people to draw your conclusions from. But as Canadian psychologist Joseph Henrich and colleagues revealed in a 2010 paper in Behavioral Brain Sciences, a lot of psych studies are done the same way as the one I participated in.

That is, they test ideas by looking at small and homogeneous groups of volunteers brought to college campuses and research facilities, usually drawing those volunteers from the school’s student body or the local population. (The rest of the guys in my study were, like me, all white male undergrads who liked playing first person shooters.)

WEIRD Science

Henrich’s team looked at hundreds of studies in leading psychology journals, and found that 68 percent of the research subjects came from the United States, and 67 percent of those were undergraduate psychology students. Overall, 96 percent of the subjects came from Western industrialized countries that, together, make up only 12 percent of the world's population. Frequently, studies that claim to reveal something universal about the human brain or our behavior are really just extrapolating results from the same (relatively) small groups.

This kind of study-building method results in the overrepresentation of a population that the authors dub WEIRD: Western, Educated, Industrialized, Rich, and Democratic. Sure, we’re all human. We’re all working with more or less the same software in our skulls. But, the researchers say, culture and environment play a role in shaping how we use that software. There are important differences in the way my brain works versus, say, a rural farmer in China, versus a member of a hunter-gatherer tribe on an island in the South Pacific, when it comes to areas like “visual perception, fairness, cooperation, spatial reasoning, categorization and inferential induction, moral reasoning, reasoning styles, self-concepts and related motivations, and the heritability of IQ.”

“The findings suggest that members of WEIRD societies, including young children, are among the least representative populations one could find for generalizing about humans,” the paper continues. We, the WEIRD ones, are actually  “highly unrepresentative of the species,” but form the basis for so much of what we think we know about ourselves.

Henrich and his colleagues call for their fellow scientists to collect comparative data across culturally and geographically diverse populations before drawing conclusions about our species as a whole. But how do you do that? With shrinking funding and small staffs, it’s not always feasible, to conduct a study in your own lab and then go elsewhere to get a different sample, or even to try to attract a diverse sample to you. Researchers have tried to get volunteers from the far reaches of the globe to participate in web-based studies, but found that mice and keyboards and web page interfaces couldn’t provide the precision necessary for understanding the subtle details and changes of cognitive processes and behavioral responses.

Pick up the Phone

But now there’s a new way to bring non-WEIRD volunteers right to the researchers. The number of smartphone users worldwide is expected to top one billion by next year. The technology has found a home in almost every social group in every part of the world, Western and Eastern, educated and not, industrialized and agrarian, rich and poor, democratic, autocratic and theocratic. Not only are they everywhere, but they’re well suited to collecting scientific data. They can transmit and receive multiple types of media and commands, can transfer time- and location-coded data, and can time, down to the millisecond, stimuli display and touchscreen responses. They are, an international team of scientists suggested last year, ideally adapted to studying cognitive function and could be used as a “multi-dimensional scientific ‘instrument’ capable of experimentation on a previously unthought-of scale” that could reveal things about the human mind long hidden by smaller experiments.

Researchers could take advantage of smartphones to revolutionize research in cognitive science, the paper argues, but the studies and the technology have to come together in a way that makes it work. To see if smartphones could live up to their promise in a real-world study, Stephane Dufau, the lead author, and her team took their idea for a road-test, without ever leaving the lab.

An App for That

The researchers developed an iPhone/iPad app that replicates the "lexical decision task,” a test used by generations of psychologists. By measuring response time and accuracy in deciding if a given string of letters is a word (e.g. “table”) or not (e.g. “tible”), researchers have gained insight into the cognitive processes involved in reading, as well as reading impairments like dyslexia. The app, called Science XL, was made free for the general public to download from the App Store in seven different languages in December 2010. By March, 2011, the team had collected results from over four thousand participants, a number they say would have taken several years, and considerably more money, to collect via more conventional means.


The results collected so far are similar to those obtained by running the test in laboratory conditions and match many of the known features of this type of data, indicating that an app-based study like this doesn’t introduce variables that affect the results.


Another team of American researchers launched a similar app-based study to look at age-related differences in cognition. They got 15,000 people to participate and their results replicated specific patterns and data found in lab experiments. This study did reveal some problems with the app-based data collection, though. One hindrance the researchers noted is the lack of ability they had to monitor the participants. Their app instructions recommended that users complete their tasks without distractions, but there’s no way they could tell if someone used the app while multitasking or in a noisy environment, which might affect their performance.

Since there’s no obligation or accountability for completing the tasks, there was also a higher participant dropout rate than in many lab studies. Still, the researchers say that the larger sample size that the app gave them access to compensated for the loss in data amount and quality.

These two studies suggest smartphones are a reliable way to collect culturally and geographically diverse data on an enormous scale. The smartphone, far from being just a gadget that lets you tweet from the bathroom, could be as important to scientific exploration as the microscope or the lunar lander. They could potentially allow for direct tests of the universality of cognitive theories and make our understanding of ourselves a little less WEIRD.

The Science XL study is ongoing, so if you want to take part, the app is free to download from iTunes AppStore.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Nick Briggs/Comic Relief
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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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