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I had previously written a critique of this article, for a different forum. I'm reproducing it here, slightly edited for this venue: With concerns of systemic
by CWuestefeld 6y ago
I had previously written a critique of this article, for a different forum. I'm reproducing it here, slightly edited for this venue:
With concerns of systemic racial bias such a hot topic today, the subject of hidden bias in machine learning systems driven by "big data" has been a frequent question. An article "The Dark Past of Algorithms That Associate Appearance and Criminality", by Catherine Stinson, appearing in the January-February 2021 issue of American Scientist, attempts to make the point that "Machine learning that links personality and physical traits warrants critical review", and largely succeeds at this task. However, most of the piece attempts to provide that critical review, and at this task it fails.
The article starts off offering phrenology as a close cousin to contemporary efforts to use facial recognition to identify criminals, or as "gaydar". A series of examples of it (mis)use in Chinese surveillance, or to monitor schoolchildren to ensure they pay attention in class, capping this off with the claim that Black students have had to endure bright lights pointed at their faces to enable such systems to work. Such applications do seem unfair, and potentially so disruptive as to be counterproductive. So in this way the author is successful in showing a need for critical review.
Stinson goes on to discuss how some of the derided foundations of phrenology - the idea that particular cognitive functions can each be seated in a particular locale within the brain - has now become "a standard assumption in mainstream neuroscience". However, she then claims that despite this, the science has suffered from sloppy methods. One example study is cited that looked for criminality based on photographic input had biased training data by using police photos to represent the convicts, versus professional photos scraped from the web for nonconvicts. It's easy to see how this would skew the results.
The author first claims, "using pictures of convicted criminals, but not of the ones who were cleared, introduces a statistical bias that skews the results", and that seems a fair point. She also says, "the researchers also admitted that taking court convictions as synonymous with criminality was a 'serious oversight'", but offers no explanation for why that should be. My best guess is that we should be able to assume that a "guilty" verdict is the best judgment we can get as to whether someone is guilty of a given crime; but that other people who are guilty of a crime but never caught will be left out of the data set, so our training would bias the system to give a pass to people who don't get caught. I suppose that's fair, too.
It's at this point that I think things start to derail. Stinson goes on to say,
their framing suggests that criminality is an innate characteristic, rather than a response to social conditions such as poverty or abuse, or a label applied to exert social control. […] Part of what makes the data set questionable on empirical grounds is that who gets labeled “criminal” is hardly value-neutral.
That's largely a philosophical question that she doesn't attempt to back up. But the fact that she does make this point, about extrinsic forces being an important contributor, actually defeats her later argument.
Along the way, she feels the need to throw in the standard anti-HBD argument that "psychologists who studied the heritability of intelligence, such as Cyril Burt and Philippe Rushton, had to play fast and loose with their data to make it look like they had found genuine connections between skull size, race, and IQ." I don't intend to debate that here, there's ample material out there showing the correlation between race and IQ (although I don't know about skull size). Either way, it doesn't seem to be relevant to her actual argument about revelations of criminality from facial characteristics.
Her main argument starts
Complex personal traits such as a tendency to commit crimes are exceedingly unlikely to be genetically linked to appearance in such a way as to be readable from photographs. First, criminality would have to be determined to a significant extent by genes rather than environment. There may be some very weak genetic influences, but any that exist would be washed out by the much larger influence of environment.
This is just wrong. Genes do not need to be the determinant here. There are any number of external factors that can point to someone's criminality:
+ A person's age is a strong clue to criminality, and we can judge age based on facial appearance quite readily
"more than half of all homicides in 2014 were committed by 15-to-29-year olds, who only made up 20 percent of the population" [1]
"The relationship between age and crime is one of the most robust relationships in all of criminology. This relationship shows that crime increases in early adolescence, around the age of 14, peaks in the early to mid 20s, and then declines thereafter." [2]
+ Probably the best clue as to criminality is past criminal history. Jailhouse tattoos (like the tear thing) are probably excellent hints here. There are even studies that claim to relate tattoo type and location to the type of crime that an inmate is incarcerated for
"The effect is even more pronounced for those with tattoos on the head or face, who are around 30% less likely to be murderers. Similar associations can be found for perpetrators of domestic crimes." [3]
+ Property crimes correlates with poverty, and poverty leaves its marks on a person's visage as well. (this is where her previous point about criminality not being an intrinsic trait actually undermines the argument). See, e.g., [4]
She continues:
Second, the genetic markers relevant to criminality would need to be linked in a regular way to genes that determine appearance. This link could happen if genes relevant to criminality were clustered in one section of the genome that happens to be near genes relevant to face shape. For a complex social trait such as criminality, this clustering is extremely unlikely. A much more likely hypothesis is that any association that exists between appearance and criminality works in the opposite direction: A person’s appearance influences how other people treat them, and these social influences are what drives some people to commit crimes (or to be found guilty of them).
She's doubling down on the social influence thing, but see my rebuttal about poverty just above.
But more importantly, her argument is again false. As improbable as it may seem to her, we know for sure that at least some important factors linked to criminality are, indeed, found relatively localized in the genome. It's established that genes on the Y chromosome lead to greater criminality: in other words, it's well documented that men are more likely to be criminals than are women.
Males were convicted of the vast majority of homicides in the United States, representing 89.5% of the total number of offenders. [5]
Her conclusion compares these technologies to cold fusion, saying that continued work on these questions is worse than useless because it's not just wasted, it also serves in "propping up colonial and class structures" - bringing non-scientific politicization into the argument. The trouble is, while she's shown that - like any tool - this facial recognition technology can be misused, she hasn't even tried to look into how it might be used for good.
I've been a subscriber to American Scientist for many years, ever since Scientific American became so overtly political. Over the past few issues, American Scientist has been debating with itself about whether it should go in this direction. The editor's note in the previous issue made me worry that it would be going in this direction, and this article solidifies that. Anybody know of a good outlet for scientific information, a couple notches more in-depth than Discover or Popular Science, but still approachable to a well-educated generalist?
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[1] https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781118519639.wbecpx275 https://onlinelibrary.wiley.com/doi/pdf/10.1002/978111851963...
[2] https://www.sagepub.com/sites/default/files/upm-binaries/60294_Chapter_23.pdf https://www.sagepub.com/sites/default/files/upm-binaries/602...
[3] https://webcache.googleusercontent.com/search?q=cache:https%3A%2F%2Fwww.economist.com%2Fchristmas-specials%2F2016%2F12%2F24%2Fa-statistical-analysis-of-the-art-on-convicts-bodies https://webcache.googleusercontent.com/search?q=cache:https%...
[4] https://www.researchgate.net/publication/221674142_The_dynamics_of_poverty_and_crime https://www.researchgate.net/publication/221674142_The_dynam...
[5] https://en.wikipedia.org/wiki/Sex_differences_in_crime#Statistics https://en.wikipedia.org/wiki/Sex_differences_in_crime#Stati...