This long new article in Science, one of the world’s premier science journals (or should I call it a “magazine”?), not only assumes that implicit (unconscious bias) is a real and pervasive thing, that it’s ubiquitous and has led to “structural racism” within institutions, that it can be assessed with a test (IAT: the “implicit association test”) that it diagnoses the severity of your bias correctly, and that making people aware of their hidden bigotry through “implicit bias training” will make them stop being bigots.
Every one of these assertions (particularly the last three) has been contested by psychologists, but you wouldn’t know that from reading the piece, which you can do by clicking below. Note that the point of this post is not to say that bias and bigotry don’t exist—you’d be a fool to claim that—but that there are grounds for questioning whether these biases are unconscious, can be diagnosed correctly with tests, and can be eliminated through training.
I’m not an expert on this topic, but I am aware that the notion of testing for and effacing unconscious bias has largely been dropped by experts—but not by “progressives”. For a documentation of the problems, with plenty of references, read this 2022 piece by Lee Jussim in Psychology Today (click on the screenshot). I’ll give his list of issues below, but note that even Scientific American has been allowed by an editor to publish a 2020 piece called “The problem with implicit bias training“, which contends that yes, implicit bias exists, but training doesn’t seem to get rid of it.
Here are Jussim’s reasons, each documented with references in the original article. The indented words and bolding are his (my comments flush left).
1. The peer-reviewed scientific literature has witnessed a great walking back of many of the most dramatic claims made on the basis of the IAT and about implicit social cognition more generally.
2. There is no consensually-accepted scientific definition of implicit bias.
3. The IAT measures reaction times, not things that most people think of as bias.
If you want to see what the IAT is all about, you can take a test here.
4. At best, the IAT measures the strength of association of concepts in memory.
5. The IAT may capture prejudice, stereotypes, or attitudes to some degree, but, if so, it is not a clean measure.
6. The IAT, as used and reported, has a potpourri of additional methodological and statistical oddities.
7. Many of the studies that use IAT scores to predict behavior find little or no anti-Black discrimination specifically.
8. Whether IAT scores predict behavioral manifestations of bias beyond self-report prejudice scales is unclear, with some studies finding they do and others finding they do not.
9. Procedures that change IAT scores have failed to produce changes in discriminatory behavior.
10. There is currently no clear evidence that implicit bias trainings accomplish anything other than teaching people about the research on implicit bias.
11. There is no evidence that IAT scores are “unconscious.”
This last one, which claims that people are very good at predicting their IAT scores, suggests that while people may be biased, it’s not unconscious (this is the main point of the “implicit” trope: that people may think they’re unbiased but they’re not, and therefore act out their racism constantly).
12. Critiques and discussions of its limitations or weaknesses are often not presented when the IAT is taught to introductory psychology students.
This is the main flaw with the Science article above. The only caveats it offers are that people’s scores aren’t often replicable, and that “simple interventions can dampen biases. . . but the changes are usually modest and don’t persist.” Well, that’s an admission of sorts, but the rest of the article is predicated on the existence of these biases and on the need for new ways to find them and eliminate them.
Here is my advice to you: Take an IAT or two (which you can here) if you have not already, just to see what the buzz is about. But now you are armed with enough information to reject any simple-minded proclamations about unconscious racism or the supposed power of implicit biases.
Again, Jussim gives copious references for his claims.
Now the one thing I’m not sure about is whether there really is a psychological trait of “implicit” bias that people aren’t aware of. It may be possible to have prejudices that linger in your unconscious (as opposed to prejudices you’re aware of but won’t admit). When I saw the first claim below in the Science piece, for example—a study that’s gotten tons of press—I wondered if there really might be some unconscious bias leading to the effect, for the white doctors would surely assert that they don’t treat patients differently because of their race:
A 2020 study by Rachel Hardeman, a reproductive health equity researcher at the University of Minnesota’s Center for Antiracism Research for Health Equity, and colleagues showed Black newborns are twice as likely to die in the care of a white physician than a Black doctor, for instance. Another study from 2022 found women and people of color with chest pain wait longer to be treated in the emergency room compared with white men.
Of course there are competing explanations: the chest pain difference could be due to triaging of symptoms not based on race (I haven’t read the article). But I have read the other article, and the difference in death rate of black babies cared for by white versus black doctors really is a cause of deep concern: it’s a huge difference! Is it possible that it’s due to unconscious racism affecting treatment of infants? But before we go accusing white pediatricians of wholesale and strong racism that kills babies, however, we should immediately begin to pose questions about controls and the like. It turns out, though these results haven’t yet been published, that there apparently were no proper controls in this study, and there were several unassessed non-bias factors that could explain the results. We should withhold judgment about the infant-death study—and not tout it as an example of egregious racism—until other statisticians and physicians have weighted in in the literature.
The Science paper documents other inequities (disproportional representation) in science and medicine, but, as always, we have to ask whether there are other explanations for them and not just bias, much less implicit bias. At times, as in the paragraph below documenting new ways to find implicit bias, there’s a telling assumption that it’s always there but sometimes hard to sniff out. This is, after all, science journalism (bolding is mine):
Others using computer software to research implicit bias in medicine are also struggling to give physicians meaningful feedback. Nao Hagiwara, a social and health psychologist at Virginia Commonwealth University, and her team are analyzing dozens of nonverbal and verbal communication behaviors, such as facial expressions and voice changes, in recordings of primary care physicians’ interactions with people who have type 2 diabetes. Their software hasn’t yet identified behaviors that could clearly be linked to bias or had an adverse effect in the patient’s outcome. One reason for this murkiness, Hagiwara suggests, is that multiple different cues likely interact to influence patient outcomes whereas studies so far tend to analyze the impact of only one behavior at a time.
Note that the failure of the test to detect “implicitly biased behaviors” doesn’t even mention that such behavior might not exist, but assumes that the researchers haven’t yet hit on the right metric or combination of behaviors (of course, that could lead to p-hacking). That paragraph itself is biased towards the existence of biased behaviors.
Finally, here’s Science‘s pronouncement (through at the end that implicit bias exists, that it’s strong and pervasive, has resulted from “centuries of white supremacy”, and it’s structural.
Sustained implicit bias training for physicians should instead be the norm, some emphasize. Hospitals also need to monitor and collect data on health care outcomes for different groups in order to monitor equity, Sabin says. “You have to know where the disparities lie and then begin to work backwards from that.”
It won’t be easy, Hardeman says, noting that, at least in the United States, centuries of white supremacy and other forms of bigotry have resulted in deep-rooted stereotypes and other implicit biases. “Every single person should be thinking about doing this work,” she says. “But if they’re doing it within a system that hasn’t addressed its own biases and racism, then it’s not going to be fully effective.”
Among the many things to worry about in this article, including some of its disturbing assertions about racism that do bear investigating (e.g., the infant-death research), is the lack of balanced coverage of this topic and an almost complete neglect of the points Jussim notes above (his name isn’t mentioned in the piece). Such science journalism is, well, unscientific.
Here’s Jussim giving a remote Merton Seminar on the problems with implicit bias.
As always, read the article, Jussim’s piece and the literature he cites, dig further into the topic, and draw your own conclusions.