January 4, 2021 | Jerry Bergman

Darwinists Still Attempting to Prove Criminality is Genetic

 

The idea that criminality represents a throwback to our
pre-modern stage of human evolution, (i.e., to the innate
aggressiveness of our survival-of-the-fittest animal ancestry)
was disproved over a century ago. Shamefully, it’s back
.

by Jerry Bergman, PhD.

Introduction

Phrenology, the art of divining personality by evaluating bumps on the human head, is one of the many past blunders of evolutionism.[1] In the late 19th century, it was considered a scientific measurement of evolution. A practitioner of phrenology essentially evaluated bumps (called peaks) on the skull surface. These were interpreted as brain areas that are more evolutionarily developed. Indentations (called valleys), by contrast, were considered to be brain areas that were evolutionarily less developed. Phrenology influenced Charles Darwin himself as well as the co-founder of natural selection, Alfred Russel Wallace.

The enormously popular phrenology movement diverted attention from other causes of behavior. It also fostered racism, and indirectly supported the rise of materialism, naturalism and Darwinism. Phrenology has been rejected by solid scientific evidence.[2] It is not only baseless, but irresponsible, because it misled many people to rely on its erroneous conclusions instead of on solid evidence-supported science. It was firmly empirically discredited in 2018 by the largest, most carefully designed study ever completed on the phrenology claims. The study used MRI neuroimaging on 5,724 subjects, producing 40,962 vertex measures per subject which were compared with a set of lifestyle measures obtained from the same subjects.[3] In short, no evidence was found that phrenology could successfully determine the traits it claimed it could predict. It failed the test miserably.

Although documented as of little use to read personality, remnants of the idea are still swimming around in the larger world of ideas. Professor Catherine Stinson writes that phrenology

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 skulls is a practice that’s well behind us. However, phrenology is once again rearing its lumpy head, this time under the guise of technology.[4]

Staring at Criminality in the Face

The worst employment of phrenology was an attempt to prove that a person’s genetic constitution could predict whether they had criminal tendencies. This idea was developed by Cesare Lombroso (1835-1909) and others. Lombroso believed that criminality was a heritable genetic trait, and that criminals could be identified by physical traits. According to this discredited view, certain physical traits identified individuals as being atavistic, meaning throwbacks to less-evolved states of humanity. A thief could be identified, for instance, by traits such as an apelike face or body and small, wandering eyes. Lombroso’s ideas of atavistic crime culminated in the “increasing popularity of eugenics and the use of biological theories of crime by the Nazis to justify the murder of millions of people.”[5] Lombroso and his followers concluded that

incorrigible offenders are “born criminals,” apelike throwbacks to a more primitive evolutionary stage. Born criminals differ so radically from lawful people that scientists can identify them by their physical and mental abnormalities, just as physical anthropologists can identify members of different races by their physical characteristics.[6]

The Late Harvard University professor Stephen Jay Gould connected Lombroso’s theory of atavisms to Charles Darwin. The idea was not just a

vague proclamation that crime is hereditary … but a specific evolutionary theory based upon anthropometric data. Criminals are evolutionary throwbacks in our midst. Germs of an ancestral past lie dormant in our heredity. In some unfortunate individuals, the past comes to life again. These people are innately driven to act as a normal ape or savage would, but such behavior is deemed criminal in our civilized society.[7]

This belief system made it very easy to “identify born criminals because they bear anatomical signs of their apishness.”[8] This turned out to be not only a foolish, but a dangerous, idea.

The New Algorithmic Phrenology

Machine-learning algorithms have recently experienced an explosion of uses, some legitimate and others problematic. Still others are downright racist. Several recent examples promise governments and private companies the ability to glean private information from people’s appearances alone. Stanford University researchers have constructed a “gaydar” algorithm that they claim can differentiate straight and gay faces far more accurately than people can.

The researchers claim that their results are consistent with the “prenatal hormone theory” – an idea supposing that fetal exposure to high levels of male sex hormones called androgens helps to determine sexual orientation. Why they assumed high levels of male hormones would determine homosexuality was not clear. The researchers cite this “much-contested claim” that these hormone exposures also result in gender-atypical faces.[9] The problem is, rather than producing objective insights, artificial intelligence (AI) programs often reinforce human biases. These biases, if trusted in practice, can harm already marginalized populations.[10]

An example is in China University where students taking online exams are monitored by proctoring algorithms. They not only have to answer the questions, but also maintain the appearance of a student who is not cheating. Unfortunately for the students, these algorithms reportedly often make false accusations against minority students, such as those with disabilities who move their faces and hands in atypical ways. Black or dark-skinned students have been required to work under bright lights to have their relevant features more detectable.[11] The most egregious example is the attempt to read faces to identify “criminal types.”

Shanghai Jiao Tong University artificial intelligence researchers Xiaolin Wu and Xi Zhang claimed to have developed an algorithm to identify criminals based on their face traits achieving what they claim is an amazingly 89.5 percent accuracy.[12] The researchers did not openly endorse the idea that criminality is genetic and can be detected by physiognomy studies. They did acknowledge that “Given the high social sensitivities and repercussions of our topic and skeptics on physiognomy, we try[tried] to excise maximum caution before publishing our results.[13] Nonetheless, their data provide support for the 19th-century ideas of the now debunked Italian criminologist Cesare Lombroso. He concluded that “criminals are under-evolved, subhuman beasts, recognizable from their sloping foreheads and hawklike noses (see Figure 1).[14] Like Lombroso, Wu and Zhang collected an enormous amount of data that was mathematically analyzed giving the impression of rigorous results that produced valid conclusions.[15] Furthermore, a critic of the study correctly observed that the Wu and Xi research’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.[16]

Figure 1. An example of the hooked nose stereotype. From Wiki-Commons.

The Hooked Nose Fiasco

The alleged hawk-like nose trait was exploited by the Nazis, who pinned this trait on Jews and pictured it in Nazi propaganda (see Figures 1. and 2.). A 1911 study of 4,000 Jewish noses found no significant difference between the size and shape of Jewish noses as compared to those of the general population.[17]

The research study’s high-tech attempt to identify facial features associated with criminality analyzes photographs by comparing the faces of multiple people to identify features indicative of traits such as criminality. The photographic composite method was developed by eugenic founder Francis Galton who was inspired (and his work approved by) his cousin Charles Darwin. The problem is facial recognition can be exploited as a modern form of  phrenology. Specifically,

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.’) [18]

Furthermore, a major issue is this technology may be used in China’s suppression of ethnic minorities, such as Uyghurs, is a concern.[19] Another concern is the large number of false positives: “the average classification accuracy is found to be only 48%, false negative rate about 51% and false positive rate about 50%.”[20] The high number of false positives for marginalized people could lead to the denial of their rights, opportunities, and even their freedom.[21] The use of physical traits to identify putative inferior humans has a long history, and its problems have been well-documented during its long history:

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.[22]

Figure 2. A German teacher teaching the hooked nose and other Darwinian myths to indoctrinate students. This is an example of the harmful consequences of trying to judge criminality from facial traits. From Wiki-Commons

The “new” phrenology efforts are also just as problematic.[23] The recent AI criminality study utilized ID photos of convicts provided by police and professional photos of non-convicts from the internet.[24] Pictures that people willingly post on the internet tend to show them in the best light, but police photos tend to show people in their worst circumstances, and their faces show it. Obviously, the algorithm could detect a difference between the two groups and, I assume, most observers could as well. Figure 3, below, shows photos of women, illustrating how subjective the criminology judgment can be when all of the pictures are very similar in most traits except the face.

In the “gaydar” algorithm test, an obvious explanation for the differences is that the study used pictures of self-identified gay and straight people from dating sites. But each group was attempting to appeal to different populations. Even the lighting differences and the angle from which the picture was taken can account for face-trait differences.[25]

Inner vs Outer Human Traits

Even more problematic is that the Wu and Zhang research “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.”[26]

One of the strongest moral objections to using facial recognition to detect criminality is that it stigmatizes innocent people. An even worse problem with the Wu and Zhang paper is the fact that the authors never mention that their technique should not be used in law-enforcement, even though they cite statistical arguments that are reason enough to conclude that it ought not to be deployed. For example, 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 marginalized communities.[27]

Another question is whether repackaging a long proven-wrong and harmful idea, phrenology, is a viable solution to the long standing problem of crime.  Eugenicists, including the founder of the field of eugenics Francis Galton and the main supporter, Cesare Lombroso,[28] ultimately failed to find facial features that accurately predisposed a person to criminality.[29]

And artificial intelligence algorithms have even more power than math to impress the average person. The fact is, crime is a complex behavior related to social, environmental, and psychology factors that are not reflected in facial traits. The connection of crime to physical traits to Darwinism has been well-documented. The  physical origin of crime

speculation intensified with the 1859 publication of The Origin of Species, in which Darwin ….  ideas seemed to be congruent with the notion of the criminal as an animalistic holdover from the primitive past.  Passages in which Darwin remarks on “rudimentary, atrophied, or aborted organs,” moreover, could easily be read as confirmations of Lombroso’s reports of the criminal’s snakelike teeth and other animalistic anomalies.[30]

A False Facade of Science

Wu and Zhang try to justify their work by claiming that we should look at the evidence even when it could have serious adverse effects on people. This rationale was pioneered by prominent eugenicist and statistician, Karl Pearson who was one of the leading founders of the field of statistics. Mathematician Aubrey Clayton argues that statistical significance testing was developed to give a “mathematical sheen to eugenic claims that only flawed methods could prop up: ‘By slathering it in a thick coating of statistics, Pearson gave eugenics an appearance of mathematical fact that would be hard to refute.”[31] Using statistical methods, Wu and Zhang have similarly produced results that may look statistically significant, but are highly misleading.[32] AI algorithms have even more power than math to give the impression of scientific credibility.[33] Stinson concluded that using new technology to achieve eugenic goals cannot be justified: “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 labeled “phrenology” will hopefully have more of an impact than simply throwing the name around as an insult.”[34]

Figure 3. A set of pictures intended to identify criminal traits in women. From The Female Offender by Cesare Lombroso, New York, NY: D. Appleton, 1909.

Conclusion

It seems that even bad evolutionary ideas tend to be recycled, and this one is just one more example.

References

[1] Bergman, Jerry. 2020. Phrenology: A Myth Behind Darwinism. Journal of Creation 34(1):115-122.

[2] Bergman, 2020.

[3] Parker, J.O., F. Alfaro-Almagro, and S. Jbabdi. 2018. An Empirical, 21st Century Evaluation of Phrenology. Cortex 106:26–35.

[4] Stinson, Catherine. 2021. The Dark Past of Algorithms that Associate Appearance and Criminality. American Scientist 109(1):26-29, p. 26.

[5] Bretherick, Diana. 2015. The ‘Born Criminal’? Lombroso and the Origins of Modern Criminology. https://www.historyextra.com/period/victorian/the-born-criminal-lombroso-and-the-origins-of-modern-criminology/.

[6] Rafter, Nicole Hahn. 1997. Creating Born Criminals. Urbana and Chicago, IL: University of Illinois Press, p. 110.

[7] Gould, Stephen Jay. 1996. The Mismeasure of Man.  New York, NY: W.W. Norton & Co., p. 153.

[8] Gould, 1996, p. 153.

[9] Stinson, 2021, p. 26.

[10] Stinson, 2021, p. 26.

[11] Stinson, 2021, p. 26.

[12] Wu, Xiaolin, and Xi Zhang. 2016. Automated Inference on Criminality using Face Images, p. 4 (of 11). https://emilkirkegaard.dk/en/wp-content/uploads/Automated-Inference-on-Criminality-using-Face-Images.pdf

[13] Wu and Zhang, 2016, p. 4.

[14] Press Bolt News. 2021. What facial recognition and the racist pseudoscience of phrenology have in common, March 12. https://pressboltnews.com/what-facial-recognition-and-the-racist-pseudoscience-of-phrenology-have-in-common/

[15] Bergman, Jerry. 2005. Darwinian Criminality Theory: A Tragic Chapter in History” Rivista di Biologia/ Biology Forum  98(1):47-70, January-April.

[16] Press Bolt News, 2021, p. 2.

[17] Ullmann, Jeremy. 2020. Understanding the Antisemitic History of the “Hooked Nose” Stereotype. https://www.media-diversity.org/understanding-the-antisemitic-history-of-the-hooked-nose-stereotype/

[18] Press Bolt News, 2021, p. 2.

[19] Roberts, Sean. 2020. The War on the Uyghurs: China’s Internal Campaign against a Muslim Minority. Princeton, NJ: Princeton University Press.

[20] Wu and Zhang, 2016, p. 4.

[21] Stinson, 2021, p. 27.

[22]Press Bolt News, 2021, p. 3.

[23] Bergman, Jerry. 2020. Phrenology: A Myth Behind Darwinism. Journal of Creation 34(1):115-122.

[24] Wu, Xiaolin, and Xi Zhang. 2016. Responses to Critiques on Machine Learning of Criminality Perceptions. (Addendum of arXiv:1611.04135); Wu, Xiaolin, and Xi Zhang. 2016. Automated Inference on Criminality using Face Images. arXiv:1611.04135v1.

[25] Agüera y Arcas, B., M. Mitchell, and A. Todorov. 2017. Physiognomy’s New Clothes. Medium, May 6; Agüera y Arcas, B., A. Todorov, and M. Mitchell. 2018. Do Algorithms Reveal Sexual Orientation or Just Expose Our Stereotypes? Medium, January 11.

[26] Stinson, 2021, p. 28.

[27] Stinson, 2021. Algorithms Associating Appearance and Criminality Have a Dark Past. https://aeon.co/ideas/algorithms-associating-appearance-and-criminality-have-a-dark-past

[28] Lombroso, Cesare, and William Ferrero. 1915. The Female Offender. New York, NY:  D. Appleton.

[29] Bergman, 2005; See also Gould, Stephen Jay. 2008. The Mismeasure of Man. New York, NY: W.W. Norton & Co.

[30] Rafter, Nicole Hahn. 1997. Creating Born Criminals. Urbana and Chicago, IL: University of Illinois Press, p. 126.

[31] Clayton, Aubrey. 2020. How Eugenics Shaped Statistics. Nautilus, October 28.

[32] Van Noorden, R. 2020. The Ethical Questions that Haunt Facial-Recognition Research. Nature 587:354–358.

[33] Clayton, 2020.

[34] Stinson, 2021, p. 29.


Dr. Jerry Bergman has taught biology, genetics, chemistry, biochemistry, anthropology, geology, and microbiology for over 40 years at several colleges and universities including Bowling Green State University, Medical College of Ohio where he was a research associate in experimental pathology, and The University of Toledo. He is a graduate of the Medical College of Ohio, Wayne State University in Detroit, the University of Toledo, and Bowling Green State University. He has over 1,300 publications in 12 languages and 40 books and monographs. His books and textbooks that include chapters that he authored are in over 1,500 college libraries in 27 countries. So far over 80,000 copies of the 40 books and monographs that he has authored or co-authored are in print. For more articles by Dr Bergman, see his Author Profile.

 

Additional Resource

In this book, Jonathan Wells gives more examples of discredited Darwinian icons that keep rising from the dead.

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