from the world's big
Algorithms associating appearance and criminality have a dark past
We'd like to think that judging people's worth based on the shape of their head is a practice that's behind us.
'Phrenology' has an old-fashioned ring to it. It sounds like it belongs in a history book, filed somewhere between bloodletting and velocipedes.
We'd like to think that judging people's worth based on the size and shape of their skull is a practice that's well behind us. However, phrenology is once again rearing its lumpy head.
In recent years, machine-learning algorithms have promised governments and private companies the power to glean all sorts of information from people's appearance. Several startups now claim to be able to use artificial intelligence (AI) to help employers detect the personality traits of job candidates based on their facial expressions. In China, the government has pioneered the use of surveillance cameras that identify and track ethnic minorities. Meanwhile, reports have emerged of schools installing camera systems that automatically sanction children for not paying attention, based on facial movements and microexpressions such as eyebrow twitches.
Perhaps most notoriously, a few years ago, AI researchers Xiaolin Wu and Xi Zhang claimed to have trained an algorithm to identify criminals based on the shape of their faces, with an accuracy of 89.5 per cent. They didn't go so far as to endorse some of the ideas about physiognomy and character that circulated in the 19th century, notably from the work of the Italian criminologist Cesare Lombroso: that criminals are underevolved, subhuman beasts, recognisable from their sloping foreheads and hawk-like noses. However, the recent study's seemingly high-tech attempt to pick out facial features associated with criminality borrows directly from the 'photographic composite method' developed by the Victorian jack-of-all-trades Francis Galton – which involved overlaying the faces of multiple people in a certain category to find the features indicative of qualities like health, disease, beauty and criminality.
Technology commentators have panned these facial-recognition technologies as 'literal phrenology'; they've also linked it to eugenics, the pseudoscience of improving the human race by encouraging people deemed the fittest to reproduce. (Galton himself coined the term 'eugenics', describing it in 1883 as 'all influences that tend in however remote a degree to give to the more suitable races or strains of blood a better chance of prevailing speedily over the less suitable than they otherwise would have had'.)
In some cases, the explicit goal of these technologies is to deny opportunities to those deemed unfit; in others, it might not be the goal, but it's a predictable result. Yet when we dismiss algorithms by labelling them as phrenology, what exactly is the problem we're trying to point out? Are we saying that these methods are scientifically flawed and that they don't really work – or are we saying that it's morally wrong to use them regardless?
There is a long and tangled history to the way 'phrenology' has been used as a withering insult. Philosophical and scientific criticisms of the endeavour have always been intertwined, though their entanglement has changed over time. In the 19th century, phrenology's detractors objected to the fact that phrenology attempted to pinpoint the location of different mental functions in different parts of the brain – a move that was seen as heretical, since it called into question Christian ideas about the unity of the soul. Interestingly, though, trying to discover a person's character and intellect based on the size and shape of their head wasn't perceived as a serious moral issue. Today, by contrast, the idea of localising mental functions is fairly uncontroversial. Scientists might no longer think that destructiveness is seated above the right ear, but the notion that cognitive functions can be localised in particular brain circuits is a standard assumption in mainstream neuroscience.
Phrenology had its share of empirical criticism in the 19th century, too. Debates raged about which functions resided where, and whether skull measurements were a reliable way of determining what's going on in the brain. The most influential empirical criticism of old phrenology, though, came from the French physician Jean Pierre Flourens's studies based on damaging the brains of rabbits and pigeons – from which he concluded that mental functions are distributed, rather than localised. (These results were later discredited.) The fact that phrenology was rejected for reasons that most contemporary observers would no longer accept makes it only more difficult to figure out what we're targeting when we use 'phrenology' as a slur today.
Both 'old' and 'new' phrenology have been critiqued for their sloppy methods. In the recent AI study of criminality, the data were taken from two very different sources: mugshots of convicts, versus pictures from work websites for nonconvicts. That fact alone could account for the algorithm's ability to detect a difference between the groups. In a new preface to the paper, the researchers also admitted that taking court convictions as synonymous with criminality was a 'serious oversight'. Yet equating convictions with criminality seems to register with the authors mainly as an empirical flaw: using mugshots of convicted criminals, but not of the ones who got away introduces a statistical bias. They said they were 'deeply baffled' at the public outrage in reaction to a paper that was intended 'for pure academic discussions'.
From Wu and Zhang (2016)
Notably, the researchers don't comment on the fact that conviction itself depends on the impressions that police, judges and juries form of the suspect – making a person's 'criminal' appearance a confounding variable. They also fail to mention how the intense policing of particular communities, and inequality of access to legal representation, skews the dataset. In their response to criticism, the authors don't back down on the assumption that 'being a criminal requires a host of abnormal (outlier) personal traits'. Indeed, their framing suggests that criminality is an innate characteristic, rather than a response to social conditions such as poverty or abuse. Part of what makes their dataset questionable on empirical grounds is that who gets labelled 'criminal' is hardly value-neutral.
One of the strongest moral objections to using facial recognition to detect criminality is that it stigmatises people who are already overpoliced. The authors say that their tool should not be used in law-enforcement, but cite only statistical arguments about why it ought not to be deployed. They note that the false-positive rate (50 per cent) would be very high, but take no notice of what that means in human terms. Those false positives would be individuals whose faces resemble people who have been convicted in the past. Given the racial and other biases that exist in the criminal justice system, such algorithms would end up overestimating criminality among marginalised communities.
The most contentious question seems to be whether reinventing physiognomy is fair game for the purposes of 'pure academic discussion'. One could object on empirical grounds: eugenicists of the past such as Galton and Lombroso ultimately failed to find facial features that predisposed a person to criminality. That's because there are no such connections to be found. Likewise, psychologists studying the heritability of intelligence, such as Cyril Burt and Philippe Rushton, had to play fast and loose with their data to manufacture correlations between skull size, race and IQ. If there were anything to discover, presumably the many people who have tried over the years wouldn't have come up dry.
The problem with reinventing physiognomy is not merely that it has been tried without success before. Researchers who persist in looking for cold fusion after the scientific consensus has moved on also face criticism for chasing unicorns – but disapproval of cold fusion falls far short of opprobrium. At worst, they are seen as wasting their time. The difference is that the potential harms of cold fusion research are much more limited. In contrast, some commentators argue that facial recognition should be regulated as tightly as plutonium, because it has so few nonharmful uses. When the dead-end project you want to resurrect was invented for the purpose of propping up colonial and class structures – and when the only thing it's capable of measuring is the racism inherent in those structures – it's hard to justify trying it one more time, just for curiosity's sake.
However, calling facial-recognition research 'phrenology' without explaining what is at stake probably isn't the most effective strategy for communicating the force of the complaint. For scientists to take their moral responsibilities seriously, they need to be aware of the harms that might result from their research. Spelling out more clearly what's wrong with the work labelled 'phrenology' will hopefully have more of an impact than simply throwing the name around as an insult.
- The New Horizon of Neuroscience - Big Think ›
- The Shape of Your Face May Predict Your Sex Drive, Study Finds ... ›
Join Pulitzer Prize-winning reporter and best-selling author Charles Duhigg as he interviews Victoria Montgomery Brown, co-founder and CEO of Big Think, live at 1pm EDT tomorrow.
Richard Feynman once asked a silly question. Two MIT students just answered it.
Here's a fun experiment to try. Go to your pantry and see if you have a box of spaghetti. If you do, take out a noodle. Grab both ends of it and bend it until it breaks in half. How many pieces did it break into? If you got two large pieces and at least one small piece you're not alone.
But science loves a good challenge<p>The mystery remained unsolved until 2005, when French scientists <a href="http://www.lmm.jussieu.fr/~audoly/" target="_blank">Basile Audoly</a> and <a href="http://www.lmm.jussieu.fr/~neukirch/" target="_blank">Sebastien Neukirch </a>won an <a href="https://www.improbable.com/ig/" target="_blank">Ig Nobel Prize</a>, an award given to scientists for real work which is of a less serious nature than the discoveries that win Nobel prizes, for finally determining why this happens. <a href="http://www.lmm.jussieu.fr/spaghetti/audoly_neukirch_fragmentation.pdf" target="_blank">Their paper describing the effect is wonderfully funny to read</a>, as it takes such a banal issue so seriously. </p><p>They demonstrated that when a rod is bent past a certain point, such as when spaghetti is snapped in half by bending it at the ends, a "snapback effect" is created. This causes energy to reverberate from the initial break to other parts of the rod, often leading to a second break elsewhere.</p><p>While this settled the issue of <em>why </em>spaghetti noodles break into three or more pieces, it didn't establish if they always had to break this way. The question of if the snapback could be regulated remained unsettled.</p>
Physicists, being themselves, immediately wanted to try and break pasta into two pieces using this info<p><a href="https://roheiss.wordpress.com/fun/" target="_blank">Ronald Heisser</a> and <a href="https://math.mit.edu/directory/profile.php?pid=1787" target="_blank">Vishal Patil</a>, two graduate students currently at Cornell and MIT respectively, read about Feynman's night of noodle snapping in class and were inspired to try and find what could be done to make sure the pasta always broke in two.</p><p><a href="http://news.mit.edu/2018/mit-mathematicians-solve-age-old-spaghetti-mystery-0813" target="_blank">By placing the noodles in a special machine</a> built for the task and recording the bending with a high-powered camera, the young scientists were able to observe in extreme detail exactly what each change in their snapping method did to the pasta. After breaking more than 500 noodles, they found the solution.</p>
The apparatus the MIT researchers built specifically for the task of snapping hundreds of spaghetti sticks.
(Courtesy of the researchers)
What possible application could this have?<p>The snapback effect is not limited to uncooked pasta noodles and can be applied to rods of all sorts. The discovery of how to cleanly break them in two could be applied to future engineering projects.</p><p>Likewise, knowing how things fragment and fail is always handy to know when you're trying to build things. Carbon Nanotubes, <a href="https://bigthink.com/ideafeed/carbon-nanotube-space-elevator" target="_self">super strong cylinders often hailed as the building material of the future</a>, are also rods which can be better understood thanks to this odd experiment.</p><p>Sometimes big discoveries can be inspired by silly questions. If it hadn't been for Richard Feynman bending noodles seventy years ago, we wouldn't know what we know now about how energy is dispersed through rods and how to control their fracturing. While not all silly questions will lead to such a significant discovery, they can all help us learn.</p>
A study looks at the performance benefits delivered by asthma drugs when they're taken by athletes who don't have asthma.
- One on hand, the most common health condition among Olympic athletes is asthma. On the other, asthmatic athletes regularly outperform their non-asthmatic counterparts.
- A new study assesses the performance-enhancement effects of asthma medication for non-asthmatics.
- The analysis looks at the effects of both allowed and banned asthma medications.
WADA uncertainty<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU0OS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMDc4NjUwN30.fFTvRR0yJDLtFhaYiixh5Fa7NK1t1T4CzUM0Yh6KYiA/img.jpg?width=980" id="01b1b" class="rm-shortcode" data-rm-shortcode-id="2fd91a47d91e4d5083449b258a2fd63f" data-rm-shortcode-name="rebelmouse-image" alt="urine sample for drug test" />
Image source: joel bubble ben/Shutterstock<p>When inhaled β-agonists first came out just before the 1972 Olympics, they were immediately banned altogether by the WADA as possible doping substances. Over the years, the WADA has reexamined their use and refined the organization's stance, evidence of the thorniness of finding an equitable position regarding their use. As of January 2020, only three β-agonists are allowed — salbutamol, formoterol, and salmeterol —and only in inhaled form. Oral consumption appears to have a greater effect on performance.</p>
The study<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU0Ny9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY1MTIzMDQyMX0.Gk4v-7PCA7NohvJjw12L15p7SumPCY0tLdsSlMrLlGs/img.jpg?width=980" id="d3141" class="rm-shortcode" data-rm-shortcode-id="ebe7b30a315aeffcb4fe739095cf0767" data-rm-shortcode-name="rebelmouse-image" alt="runner at starting position on track" />
Image source: MinDof/Shutterstock<p>Of primary interest to the authors of the study is confirming and measuring the performance improvement to be gained from β-agonists when they're ingested by athletes who don't have asthma.</p><p>The researchers performed a meta-analysis of 34 existing studies documenting 44 randomized trials reporting on 472 participants. The pool of individuals included was broad, encompassing both untrained and elite athletes. In addition, lab tests, as opposed to actual competitions, tracked performance. The authors of the study therefore recommend taking its conclusions with just a grain of salt.</p><p>The effects of both WADA-banned and approved β-agonists were assessed.</p>
Approved β-agonists and non-asthmatic athletes<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU1MC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMzkxODk0M30.3RssFwk_tWkHRkEl_tIee02rdq2tLuAePifnngqcIr8/img.jpg?width=980" id="39a99" class="rm-shortcode" data-rm-shortcode-id="b1fe4a580c6d4f8a0fd021d7d6570e2a" data-rm-shortcode-name="rebelmouse-image" alt="vaulter clearing pole" />
Image source: Andrey Yurlov/Shutterstock<p>What the meta-analysis showed is that the currently approved β-agonists didn't significantly improve athletic performance among those without asthma — what very slight benefit they <em>may</em> produce is just enough to prompt the study's authors to write that "it is still uncertain whether approved doses improve anaerobic performance." They note that the tiny effect did increase slightly over multiple weeks of β-agonist intake.</p>
Banned β-agonist and non-asthmatic athletes<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yMzUzNzU1Mi9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYzNjI3ODU5Mn0.vyoxSE5EYjPGc2ZEbBN8d5F79nSEIiC6TUzTt0ycVqc/img.jpg?width=980" id="de095" class="rm-shortcode" data-rm-shortcode-id="02fdd42dfda8e3665a7b547bb88007ef" data-rm-shortcode-name="rebelmouse-image" alt="swimmer mid stroke" />
Image source: Nejron Photo/Shutterstock<p>The study found that for athletes without asthma, however, the use of currently banned β-agonists did indeed result in enhanced performance. The authors write, "Our meta-analysis shows that β2-agonists improve anaerobic performance by 5%, an improvement that would change the outcome of most athletic competitions."</p><p>That 5 percent is an average: 70-meter sprint performance was improved by 3 percent, while strength performance, MVC (maximal voluntary contraction), was improved by 6 percent.</p><p>The analysis also revealed that different results were produced by different methods of ingestion. The percentages cited above were seen when a β-agonist was ingested orally. The effect was less pronounced when the banned substances were inhaled.</p><p>Given the difference between the results for allowed and banned β-agonists, the study's conclusions suggest that the WADA has it about right, at least in terms of selection of allowable β-agonists, as well as the allowable dosage method.</p>
Takeaway<p>The study, say its authors, "should be of interest to WADA and anyone who is interested in equal opportunities in competitive sports." Its results clearly support vigilance, with the report concluding: "The use of β2-agonists in athletes should be regulated and limited to those with an asthma diagnosis documented with objective tests."</p>
Certain water beetles can escape from frogs after being consumed.
- A Japanese scientist shows that some beetles can wiggle out of frog's butts after being eaten whole.
- The research suggests the beetle can get out in as little as 7 minutes.
- Most of the beetles swallowed in the experiment survived with no complications after being excreted.