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Sex Differences or Sexism? On the Long Wait for a Female President

photograph of oval office

In her recent New York Times piece, “Britain 3, America 0,” Gail Collins laments the failure of the United States to elect a female president. Meanwhile, traditional old Britain has recently acquired its third (Conservative) female prime minister, Liz Truss.

Collins’ frustration will strike many readers as obviously correct, perhaps even boringly correct. If, counterfactually, we lived in a society without sexism, then surely we would have had at least one female president by now. If that’s right, then sexist stereotyping plays some role in explaining the fact that we haven’t. But are there other explanations than sexism?

According to the Center for American Women in Politics’ Debbie Walsh, the problem is “that women are seen as good at getting along with other people, but not necessarily at running things.” In other words, inaccurate sexist stereotypes explain the nation’s failure to elect a female president.

The trouble with this explanation is that psychological research partly confirms certain clichés about men and women.

While both sexes have near-identical average scores for some traits, e.g., openness/intellect (the ability and interest in attending to and processing complex stimuli), studies repeatedly find significant differences between the sexes for other traits. For instance, on average, women are more “agreeable” than men, meaning they have a higher tendency toward “cooperation, maintenance of social harmony, and consideration of the concerns of others.” But men are, on average, more assertive, which many – rightly or wrongly – consider a key leadership trait.

There are competing explanations for these sex differences. Some think they are explained by human biology. Others contend that they are cultural artifacts, ways of being that men and women learn from society as they grow up. But most psychologists now think that a complex mix of nature and nurture explains these average differences between men and women. But whatever the cause(s), there is little dispute that these measurable differences exist. On this basis, some have concluded that our society is not sexist because “Women really are different from men!” And they think that this fact – and not sexism – explains things like why we’ve not had a female president.

But this conclusion would be premature. There’s still plenty of opportunity for sexism to be doing some explanatory work.

First, it might be that our assumptions about what makes a good leader are sexist. We might tend to overvalue the “masculine” traits and undervalue “feminine” traits. Perhaps women’s greater tendency to agreeableness (“cooperation, maintenance of social harmony, and consideration of others”) is precisely what we need in a leader in these divisive times, but we keep electing less suitable but more assertive “strong men.” If we systematically overvalue the traits more common in men and undervalue those more common in women, we would be putting the pool of female candidates at an unfair disadvantage. This is one way in which sexism can operate even if there are sex differences.

Second, and I think far more significantly, individual men and women are not the averages of their sex. An average is just an average, and nothing more. Within any group as large as half the population, there is obviously a huge amount of individual variation. There are many highly agreeable and unassertive men and many highly assertive and disagreeable women. Think about it — you probably know people who fall at all different points on this scale.

Even if, hypothetically, traits more common in men did make them more suitable for the role of president, then, given great individual variation, we should still expect some presidents to have been women, even if not half.

This brings me to another way that sexism can operate on top of sex differences. Imagine a voter who sincerely thinks that assertiveness is a key trait for a president. After all, a president must make difficult and important decisions each day, often under terrible pressure. Imagine this person could never vote for someone who they didn’t think was highly assertive. That seems like a reasonable view.

But sexism could still be at play. If the average woman is less assertive than the average man, then we might tend to overlook the leadership potential of highly assertive women because we assume, given their sex, that they are less assertive than they actually are.

Given that female politicians have, presumably, had to overcome certain challenges their male counterparts have not, you might even expect female politicians to be particularly assertive, perhaps even more than their male counterparts. Britain’s controversial first female Prime Minister, Margaret Thatcher, certainly lends some credence to that possibility.

To explain why we’ve not had a female president, then, we can’t simply appeal to either sexism or sex differences. The relationship between sexism, sex differences, and political outcomes is more nuanced. We don’t need to dispute the psychological evidence of sex differences in order to maintain that sexism is a real problem with damaging political consequences. It might be that our assumptions about the traits needed for leadership are sexist and biased. Or it might be that our awareness of group averages blinds us to individual differences, preventing us from fairly judging the merit of individual female political candidates. Yes, there is significant psychological evidence for sex differences in traits that are commonly regarded as important for leadership. But sexism could still be unjustly distorting political outcomes. As is so often the case, the partial explanations of political events and outcomes that we are so often provided are excellent at getting us riled up and reinforcing our loyalty to our political tribe, but they’re much worse at helping us to understand the society of which we are a part.

Losing Ourselves in Others

illustration of Marley's ghost in A Christmas Carol

The end of the year is a time when people often come together in love and gratitude. Regardless of religion, many gather to share food and drink or perhaps just to enjoy one another’s company. It’s a time to celebrate the fact that, though life is hard and dangerous, we made it through one more year with the help of kindness and support from one another.

Of course, this is why the end of the year can also be really hard. Many people didn’t survive the pandemic and have left enormous voids in their wake. Even for families and friend groups who were lucky enough to avoid death, many relationships didn’t survive.

Deep differences of opinion about the pandemic, race, and government have created chasms of frustration, distrust, and misunderstanding. If this is an accurate description of relationships between those who cared deeply for one another, it’s even less likely to be resolvable for casual acquaintances and members of our communities we only come to know as a result of our attempts to create social policy. This time of year can amplify our already significant sense of grief, loss, and loneliness — the comfort of community is gone. We feel what is missing acutely. How ought we to deal with these differences? Can we deal with them without incurring significant changes to our identities?

Moral philosophy throughout the course of human history has consistently advised us to love our neighbors. Utilitarianism tells us to treat both the suffering and the happiness of others impartially — to recognize that each sentient being’s suffering and happiness deserves to be taken seriously. Deontology advises us to recognize the inherent worth and dignity of other people. Care ethics teaches us that our moral obligations to others are grounded in care and in the care relationships into which we enter with them. Enlightenment moral philosophers like Adam Smith have argued that our moral judgments are grounded in sympathy and empathy toward others. We are capable of imaginatively projecting ourselves into the lives and experiences of other beings, and that provides the grounding for our sense of concern for them.

Moral philosophers have made fellow-feeling a key component in their discussions of how to live our moral lives, yet we struggle (and have always struggled) to actually empathize with fellow creatures. At least one challenge is that there can be no imaginative projection into someone else’s experiences and worldview if doing so is in conflict with everything a person cares about and with the most fundamental things with which they identify.

“Ought implies can” is a contentious but common expression in moral philosophy. It suggests that any binding moral obligation must be achievable; if we ought to do something, then we realistically can do the thing in question. If you tell me that I ought to have done more to end world hunger, for instance, that implies that it was possible for me to have done more to end world hunger (or, at least, that you believe that it was possible for me to have done so).

But there are different senses of “can.” One sense is that I “can” do something only if it is logically possible. Or, perhaps, I “can” do something only if it is metaphysically possible. Or, in many of the instances that I have in mind here, a person “can” do something only if it is psychologically possible. It may be the case that empathizing with one’s neighbor, even in light of all of the advice offered by wise people, may be psychologically impossible to do, or close to it. The explanation for this has to do with the ways in which we construct and maintain our identities over time.

Fundamental commitments make us who we are and make life worth living (when it is). In fact, the fragility of those commitments, and thus the fragility of our very identities, causes some philosophers to argue that immortality is undesirable. In Bernard Williams’ now famous paper The Makropulos Case: Reflections on the Tedium of Immortality he describes a scene from The Makropulos Affair, an opera by Czech composer Leoš Janáček. The main character, Elina, is given the opportunity to live forever — she just needs to keep taking a potion to extend her life. After many, many years of living, she decides to stop taking the potion, even though she knows that if she does so she will cease to exist. Williams argues that anyone who takes such a potion — anyone who chooses to extend their life indefinitely — would either inevitably become bored or would change so much that they lose their identity — they would, though they continue to live, cease to be who they once were.

One of the linchpins of Williams’ view is that, if a person puts themselves in countless different circumstances, they will take on desires, preferences, and characteristics that are so unlike the “self” that started out on the path that they would become someone they no longer recognize. One doesn’t need to be offered a vial of magical elixir to take on the potential for radical change — one has simply to take a chance on opening oneself up to new ideas and possibilities. To do so, however, is to risk becoming unmoored from one’s own identity — to become someone that an earlier version of you wouldn’t recognize. While it may frustrate us when our friends and loved ones are not willing to entertain the evidence that we think should change their minds, perhaps this shouldn’t come as a surprise — we sometimes see change as an existential threat.

Consider the case of a person who takes being patriotic as a fundamental part of their identity. They view people who go into professions that they deem as protective of the country — police officers and military members — to be heroes. If they belong to a family which has long held the same values, they may have been habituated to have these beliefs from an early age. Many of their family members may be members of such professions. If this person were asked to entertain the idea that racism is endemic in the police force, even in the face of significant evidence, they may be unwilling and actually incapable of doing so. Merely considering such evidence might be thought of, consciously or not, as a threat to their very identity.

The challenge that we face here is more significant than might be suggested by the word “bias.” Many of these beliefs are reflective of people’s categorical commitments and they’d rather die than give them up.

None of this is to say that significant changes to fundamental beliefs are impossible — such occurrences are often what philosophers call transformative experiences. That language is telling. When we are able to entertain new beliefs and attitudes, we express a willingness to become new people. This is a rare enough experience to count as a major plot point in a person’s life.

This leaves us with room for hope, but not, perhaps, for optimism. Events of recent years have laid bare the fundamental, identity-marking commitments of friends, family, and members of our community. Reconciling these disparate commitments, beliefs, and worldviews will require nothing less than transformation.

On Objectivity in Journalism

blurred image of crowd and streetlights

Over the past few years, a number of left-leaning journalists have publicly questioned the notion of objectivity as an ideal for journalists and journalistic practice. The discussions that ensued have generated a lot of heat, but for the most part not too much light. That’s why I was delighted by the latest episode of Noah Feldman’s podcast, Deep Background, which featured a lengthy interview with journalist Nikole Hannah-Jones, who is perhaps best known as the creator of The New York Times’s The 1619 Project. In that interview, Hannah-Jones and Feldman develop a nuanced account of the place of objectivity in journalism. I will discuss this account in due course. Before I do, I would like to unpack the multiple meanings of “objectivity” as it is used to describe journalists and their art.

The word “objectivity” is normally applied to two things: persons and facts or truths. An objective person is one who has three attributes: neutrality, even-handedness, and disinterestedness. A neutral person has no prior or preconceived views about a particular subject; an even-handed person is disposed to give due weight to both sides in a factual dispute; and a disinterested person has no strong interests in one side or the other being the correct one. Thus, objectivity as an attribute of persons involves (the lack of) both beliefs and desires. It is in the name of promoting the appearance of this kind of objectivity that some journalists think it is improper for them to engage in political activity, or even to vote.

When applied to facts or truths, as in the oft-repeated phrase “objective truth,” the word is generally taken to mean something about either empirical verifiability or “mind-independence.” Take empirical verifiability first. In this sense, “objective” truths are truths that can be directly verified by the senses, and so are part of a public world which we share with other sentient creatures. In this sense, “objective” truths contrast with both truths about our mental states, such as that I like the taste of chocolate ice cream, and “metaphysical” truths, such as that God is all-powerful. Mind-independence is a slippery concept, but the basic idea is that mind-independent truths are truths which don’t depend on anyone’s beliefs about what is true. That it is raining in Durham, North Carolina would be true even if everyone believed it false. In this sense, “objective” truths contrast with conventional truths, such as truths about grammar rules, since such rules depend for their very existence on the attitudes, and in particular the beliefs, of writers and speakers. In this sense, however, “objective” truths include both metaphysical truths and truths about mental states. To see the latter point, consider that the fact that I like chocolate ice cream would be true even if no one, including I myself, believed it to be true. Thus, truths about personal taste can count as subjective in one sense, but objective in another.

With some exceptions I will discuss shortly, criticisms of objectivity rarely cast doubt on the existence of objective truths. Instead, they target the ideal of the journalist as a neutral, even-handed, and disinterested observer. The criticisms are two-fold: first, that adopting the objective stance is impossible, since all journalists use their prior beliefs and interests to inform their decisions about what facts to include or highlight in a story, and if they have the discretion, even what stories to write. Second, since a perfectly objective stance is impossible, trying to adopt the stance constitutes a form of deception that causes people to invest journalists with a kind of epistemic authority they don’t and couldn’t possess. Better to be honest about the subjective (basically, the psychological) factors that play a role in journalistic practice than to deceive one’s readers.

In the interview with Feldman, Hannah-Jones echoed these criticisms of objectivity. She then distinguished between two activities every journalist engages in: fact-finding and interpretation. In the fact-finding phase, she said, journalists can and must practice “objectivity of method.” What she apparently means to pick out with this phrase are methods by which journalists can hope to access objective truth. Such methods might include interviewing multiple witnesses to an event or searching for documentary evidence or some other reliable corroboration of testimony; they might also include the institutional arrangements that newsrooms adopt — for example, using independent fact checkers. However, she and Feldman seemed to agree that interpretation — variously glossed as working out what facts “mean” or which are “important” — is a subjective process, inevitably informed by the journalist’s prior beliefs and desires.

Here are two observations about Hannah-Jones’s account. First, the methods used to access objective truth in the fact-finding stage tend to force journalists to at least act as if they are objective persons. For example, interviewing multiple witnesses and weighing the plausibility of all the testimony is the kind of thing an even-handed observer would do. Looking for corroborating evidence even when one wants a witness’s testimony to be true emulates disinterestedness. This doesn’t mean that one has to be objective in order to practice journalism well, but it does suggest a role for objectivity as a regulative ideal: when we want to know how to proceed in fact-finding, we ask how an objective person would proceed. And to the extent that we can emulate the objective person, to that extent is the epistemic authority of the journalist earned.

Second, it seems to me that “interpretation” involves trying to access objective truth, or doing something much like it. Feldman and Hannah-Jones used two examples to illustrate the kinds of truths that the process of interpretation is aimed at accessing: truths about people’s motives, or why they acted (as opposed to truths about their actions themselves, which are within the domain of fact-finding), and causal truths, like that such-and-such an event or process was the key factor in bringing about some state of affairs. But such truths are objective in at least one sense. Moreover, even truths about motives, while subjective in not belonging to the public world of the senses, can be indirectly verified using empirical methods very similar to those used to access directly empirically verifiable truths. These are methods lawyers use every day to prove or disprove that a defendant satisfied the mens rea element of a crime. Since interpretation involves accessing objective truths or using empirical methods to access subjective ones, and since the methods of accessing objective truths involve emulating an objective person, interpretation at least partly involves striving to be objective.

This can’t be all it involves, however: what’s important is not equivalent to what’s causally efficacious. Here is where Feldman and Hannah-Jones are undoubtedly correct that a journalist’s attitudes, and in particular her values, will inevitably shape how she interprets the facts. For example, a commitment to moral equality may cause a journalist to train their focus on the experience of marginalized groups, that value informing what the journalist takes to be important. A merely objective person would have no idea of what facts are important in this moral sense.

Thus, a journalist must and should approach her practice with a complicated set of attitudes: striving to be objective (to be like an objective person) about the facts, while at the same time inevitably making choices about which facts are important based at least in part on her values. This is part of what makes journalism a difficult thing to do well.

In-Groups, Out-Groups, and Why I Care about the Olympics

photograph of fans in crowded stadium holding one big American flag

We all, to some extent, walk around with an image of ourselves in our own heads. We have, let’s say, a self-conception. You see yourself as a certain kind of person, and I see myself as a certain kind of person.

I bring this up because my own self-conception gets punctured a little every time the Olympics roll around. I think of myself as a fairly rational, high-brow, cosmopolitan sort of person. I see myself as the sort of person who lives according to sensible motives; I don’t succumb to biased tribal loyalties.

In line with this self-conception, I don’t care about sporting events. What does it matter to me if my university wins or loses? I’m not on either team, I don’t gain anything if FSU wins a football game. So yes, I am indeed one of those obnoxious and self-righteous people who a) does not care about sports and b) has to fight feelings of smug superiority over sports fans who indulge their tendencies to tribalism.

This is not to say I don’t have my loyalties: I’m reliably on team dog rather than cat, and I track election forecasts with an obsessive fervor equal to any sports fanatic. But I tell myself that, in both cases, my loyalty is rational. 

I’m on team dog because there are good reasons why dogs make better pets.”

“I track elections because something important is at stake, unlike in a sports game.”

These are the sorts of lies I tell myself in order to maintain my self-conception as a rational, unbiased sort of person. By the end of this post, I hope to convince you that these are, in fact, lies.

The Olympic Chink

The first bit of evidence that I’m not as unbiased as I’d like to think, comes from my interest in the Olympics. I genuinely care about how the U.S. does in the Olympics. For example, I was disappointed when, for the first time in fifty years, the U.S. failed to medal day one.

Nor do I have any clever story for why this bias is rational. While I think there is a strong case to be made for a certain kind of moral patriotism, my desire to see the U.S. win the most Olympic medals is not a patriotism of that sort. Nor do I think that the U.S. winning the most medals will have important implications for geopolitics; it is not as though, for example, the U.S. winning more medals than China will help demonstrate the value of extensive civil liberties.

Instead, I want the US to win because it is my team. I fully recognize that if I lived in Portugal, I’d be rooting for Portugal.

But why do I care if my team wins? After all, everything I said earlier about sports is also true of the Olympics. Nothing in my life will be improved if the U.S. wins more medals.

Turning to Psychology

To answer this question, we need to turn to psychology. It turns out that humans are hardwired to care about our in-group. Perhaps the most famous studies demonstrating the effects of in-group bias come from the social psychologist Henri Tajfel.

In one study, Tajfel brought together a group of fourteen- and fifteen-year-old boys. Tajfel wanted to know what it would take to get people invested in ‘their team.’ It turns out, it barely requires anything at all.

Tajfel first had the boys estimate how many dots were flashed on a screen, ostensibly for an experiment on visual perception. Afterwards the boys were told that they were starting a second experiment, and that, to make it easier to code the results, the experimenters were dividing the boys into subgroups based on if they tended to overestimate or underestimate the number of flashed dots (in actual fact the subgroups were random). The boys were then given the chance to distribute rewards anonymously to other participants.

What Tajfel found was that the mere fact of being categorized into a group of ‘overestimators’ or ‘underestimators’ was enough to produce strong in-group bias. When distributing the reward between two members of the same group, the boys tended to distribute the reward fairly. However, when distributing between one member of the in-group and one member of the out-group, the boys would strongly favor members in their same group. This was true even though there was no chance for reciprocation, and despite participants knowing that the group membership was based on something as arbitrary as “overestimating the number of dots flashed on a screen.”

Subsequent results were even more disturbing. Tajfel found that not only did the boys prioritize their arbitrary in-group, but they actually gave smaller rewards to people in their own group if it meant creating a bigger difference between the in-group and out-group. In other words, it was more important to treat the in-group out-group differently than it was to give the biggest reward to members of the in-group.

Of course, this is just one set of studies. You might think that these particular results have less to do with human nature and more to do with the fact that lots of teenage boys are jerks. But psychologists have found tons of other evidence for strong in-group biases. Our natural in-group bias seems to explain phenomena as disparate as racism, motherlove, sports fandom, and political polarization.

Sometimes this in-group bias is valuable. It is good if parents take special care of their children. Parental love provides an extremely efficient system to ensure that most children get plenty of individualized attention and care. Similarly, patriotism is an important political virtue, it motivates us to sacrifice to improve our nation and community.

Sometimes this in-group bias is largely benign. There is nothing pernicious in wanting your sports team to win, and taking sides provides a source of enjoyment for many.

But sometimes this in-group bias is toxic and damaging. A nationalistic fervor that insists your own country is best, as opposed to just your own special responsibility, often leads people to whitewash reality. In-group bias leads to racism and political violence. Even in-group sports fandom sometimes results in deadly riots.

A Dangerous Hypocrisy

If this is right, then it is unsurprising that I root for the U.S. during the Olympic games. What is perhaps much more surprising is that I don’t care about the results of other sporting games. Why is it then, if in-group bias is as deep as the psychologists say it is, that I don’t care about the performance of FSU’s football team?

Is my self-conception right, am I just that much more rational and enlightened? Have I managed to, at least for the most part, transcend my own tribalism?

The psychology suggests probably not. But if I didn’t transcend tribalism, what explains why I don’t care about the performance of my tribe’s football team?

Jonathan Haidt, while reflecting on his own in-group biases, gives us a hint:

“In the terrible days after the terrorist attacks of September 11, 2001, I felt an urge so primitive I was embarrassed to admit it to my friends: I wanted to put an American flag decal on my car. . . . But I was a professor, and professors don’t do such things. Flag waving and nationalism are for conservatives. Professors are liberal globetrotting universalists, reflexively wary of saying that their nation is better than other nations. When you see an American flag on a car in a UVA staff parking lot, you can bet that the car belongs to a secretary or a blue-collar worker.”

Haidt felt torn over whether to put up an American flag decal. This was not because he had almost transcended his tribal loyalty to the US. Rather he was being pulled between two different tribal loyalties. His loyalty to the US pulled him one way, his loyalty to liberal academia pulled the other. Haidt’s own reticence to act tribally by putting up an American flag decal, can itself be explained by another tribal loyalty.

I expect something similar is going on in my own case. It’s not that I lack in-group bias. It’s that my real in-group is ‘fellow philosophers’ or ‘liberal academics’ or even ‘other nerds,’ none of whom get deeply invested in FSU football. While I conceive of myself as “rational,” “high-brow,” and “cosmopolitan”; the reality is that I am largely conforming to the values of my core tribal community (the liberal academy). It’s not that I’ve transcended tribalism, it’s that I have a patriotic allegiance to a group that insists we’re above it. I have an in-group bias to appear unbiased; an irrational impulse to present myself as rational; a tribal loyalty to a community united around a cosmopolitan ideal.

But this means my conception of myself as rational and unbiased is a lie. I have failed to eliminate my in-group bias after all.

An Alternative Vision of Moral Education

But we seem to face a problem. On the one hand, my in-group bias seems to be so deep that even my principled insistence on rationality turns out to be motivated by a concern for my in-group. But on the other hand, we know that in-group bias often leads to injustice and the neglect of other people.

So what is the solution? How can we avoid injustice if concern for our in-group is so deeply rooted in human psychology?

We solve this problem, not by trying to eliminate our in-group bias, but rather by bringing more people into our in-group. This has been the strategy taken by all the greatest moral teachers throughout history.

Consider perhaps the most famous bit of moral instruction in all of human history, the parable of the Good Samaritan. In this parable, Jesus is attempting to convince the listening Jews that they should care for Samaritans (a political out-group) in the same way they care for Jews (the political in-group). But he does not do so by saying that we should not have a special concern for our in-group. Rather, he uses our concern for the in-group (Jesus uses the word ‘neighbor’) and simply tries to bring others into the category. He tells a story which encourages those listening to recognize, not that they don’t have special reasons to care for their neighbor (their in-group), but to redefine the category of ‘neighbor’ to include Samaritans as well.

This suggests something profound about moral education. To develop in justice, we don’t eliminate our special concern for the in-group. Instead we expand the in-group so that our special concern extends to others. This is why language like ‘brotherhood of man’ or ‘fellow children of God’ has proven so powerful throughout history. Rather than trying to eliminate our special concern for family, it instead tries to get us to extend that very same special concern to all human beings.

This is why Immanuel Kant’s language of the ‘Kingdom of Ends’ is so powerful. Rather than trying to eliminate a special concern for our society, instead we recognize a deeper society in which all humans are members.

The constant demand of moral improvement is not to lose our special concern for those near us, but to continually draw other people into that same circle of concern.

More Than Words: Hate Crime Laws and the Atlanta Attack

photograph of "Stop Asian Hate' sign being held

There’s an important conversation happening about how we should understand Robert Aaron Long’s murder of eight individuals, including six Asian women (Daoyou Feng, Hyun Jung Grant, Suncha Kim, Soon Chung Park, Xiaojie Tan, Yong Ae Yue) last week. Were Long’s actions thoughtless or deliberate? Is the attack a random outburst at an unrelated target, or “a new chapter in an old story”? Is the attack better explained as a byproduct of anti-Asian American sentiment left to fester, or merely the result of a young, white man having “a really bad day”? Behind these competing versions lies a crucial distinction: in judging the act, should we take on the point of view of the attacker or his victims?

In the wake of the tragedy, President Biden urged lawmakers to endorse the COVID-19 Hate Crimes Act aimed at addressing the rise in violence directed at Asian Americans. The bill intends to improve hate crime reporting, expand resources for victims, and encourage prosecution of bias-based violence. As Biden has emphasized, “every person in our nation deserves to live their lives with safety, dignity, and respect.” By publicly condemning the Atlanta attack as a hate crime, the president hopes to address the climate of fear, distrust, and unrest that’s set in.

Unfortunately, hate crime legislation has proven more powerful as a public statement than a prosecutorial tool. The enhanced punishment attached to those criminal offenses motivated by the offender’s biases against things like race, religion, and gender are rarely sought. Part of the problem stems from the legal difficulty in demonstrating motive. This requires going beyond mere intent — assessing the degree to which one meant to cause harm — and instead considering the reasons why the person acted as they did. We’re encouraged to judge the degree to which prejudice might have precipitated violence. Establishing motive, then, requires us to speculate as to the inner workings of another’s mind. Without a confession, we’re left to try to string bits of information together into a compelling narrative of hate. It’s a flimsy thing to withstand scrutiny beyond a reasonable doubt.

This trouble with motive is currently on clear display: Long has insisted that race and gender had nothing to do with the attack, and the police seem willing to take him at his word. On Thursday, FBI director Christopher Wray deferred to the assessment by local police saying that “it does not appear that the motive was racially motivated.” Instead, Long’s actions have been explained as the consequence of sex addiction in conflict with religious conviction; Long’s goal has been described as the elimination of temptation.

How this explanation insulates Long’s actions from claims of bias-inspired violence is not clear. As Grace Pai of Asian Americans Advancing Justice suggested, “To think that someone targeted three Asian-owned businesses that were staffed by Asian American women […] and didn’t have race or gender in mind is just absurd.” The theory fails to appreciate the way Long’s narrative fetishizes Asian American women and reduces them to sexual objects. Rather than avoiding the appearance of bias, the current story seems to possess all the hallmarks. Sure, it might prove a bit more difficult to establish in a court of law, but as Senator Raphael Warnock argued, “we all know hate when we see it.”

So what makes politicians run toward, and law enforcement run from, the hate crime designation? In addition to the difficulty in prosecution, hate crime laws have a shaky record as a deterrent, made worse by the fact that they are rarely reported, investigated, or prosecuted. Despite all but three states now having hate crime laws on the books, rates of bias-inspired violence and harassment over the past several years have remained relatively high. (Many attribute this trend to the xenophobic and racist rhetoric that came out of the previous White House administration.)

But perhaps the value of hate crime legislation can’t be adequately captured by focusing on deterrence. Maybe it’s about communication. Perhaps the power of these laws is about coming together as a community to say that we condemn violence aimed at difference in a show of solidarity. We want it known that these particular individuals — these particular acts — don’t speak for us. Words matter, as the controversy regarding the sheriff’s office explanation of the attacker’s state of mind makes clear. Making the public statement, then, is a crucial step even if political and legal factors mean the formal charge is not pursued. It’s a performance directed at all of us, not at the perpetrator. The goal is restoration and reconciliation. Failing to call out bias-inspired violence when we see it provides cover and allows roots to take hold and to continue to grow unchecked.

Still, the importance of signalling this moral commitment doesn’t necessarily settle the legal question of whether hate crime legislation can (and should) play the role we’ve written for it. Hate crime laws are built on our belief that bias-inspired violence inflicts greater societal harm. These crimes inflict distinct emotional harms on their victims, and send a specific message to particular members of the community. Enhanced legal consequences are justified, then, on the basis of this difference in severity and scope. Punishment must fit the crime.

Some critics, however, worry that hate crime laws reduce individuality to membership of a protected group. In a way, it’s guilty of a harm similar to that perpetrated by the attacker: it renders victims anonymous. It robs a person of her uniqueness, strips her of her boundless self, and collapses her to a single, representative label. Because of this, hate crime laws seem at once both necessary for securing justice for the victim — they directly address the underlying explanation of the violence — and diametrically opposed to that goal — the individual victim comes to be defined first and foremost by her group identity.

The resolution to these competing viewpoints is not obvious. On the one hand, our intuitions suggest that people’s intentions impact the moral situation. Specifically targeting individuals on the basis of their gender or ethnicity is clearly a different category of moral wrong. But the consequences that come from the legal application of those moral convictions have serious repercussions. Ultimately, the lasting debate surrounding hate crime legislation speaks to the slipperiness in pinning down what precisely justice demands.

Stereotyping and Statistical Generalization

photograph of three different multi-colored pie charts

Let’s look at three different stories and use them to investigate statistical generalizations.

Story 1

This semester I’m teaching a Reasoning and Critical Thinking course. During the first class, I ran through various questions designed to show that human thinking is subject to predictable and systematic errors. Everything was going swimmingly. Most students committed the conjunction fallacy, ignored regression towards the mean, and failed the Wason selection task.

I then came to one of my favorite examples from Kahneman and Tversky: base rate neglect. I told the students that “Steve is very shy and withdrawn, invariably helpful but with little interest in people or in the world of reality. A meek and tidy soul, he has a need for order and structure, and a passion for detail,” and then asked how much more likely it is that Steve is a librarian than a farmer. Most students thought it was moderately more likely that Steve was a librarian.

Delighted with this result, I explained the mistake. While Steve is more representative of a librarian, you need to factor in base-rates to conclude he is more likely to actually be a librarian. In the U.S. there are about two million farmers and less than one hundred and fifty thousand librarians. Additionally, while 70% of farmers are male, only about 20% of librarians are. So for every one librarian named Steve you should assume there are at least forty-five farmers so named.

This culminated in my exciting reveal: even if you think that librarians are twenty times more likely than farmers to fit the personality sketch, you should still think Steve is more than twice as likely to be a farmer.

This is counter-intuitive, and I expected pushback. But then a student asked a question I had not anticipated. The student didn’t challenge my claim’s statistically illegitimacy, he challenged its moral illegitimacy. Wasn’t this a troubling generalization from gender stereotypes? And isn’t reasoning from stereotypes wrong?

It was a good question, and in the moment I gave an only so-so reply. I acknowledged that judging based on stereotypes is wrong, and then I…

  1. distinguished stereotypes proper from empirically informed statistical generalizations (explaining the psychological literature suggesting stereotypes are not statistical generalizations, but unquantified generics that the human brain attributes to intrinsic essences);
  2. explained how the most pernicious stereotypes are statistically misleading (e.g., we accept generic generalizations at low statistical frequencies about stuff we fear), and so would likely be weakened by explicit reasoning from rigorous base-rates rather than intuitive resemblances;
  3. and pointed out that racial disparities present in statistical generalizations act as important clarion calls for political reform.

I doubt my response satisfied every student — nor should it have. What I said was too simple. Acting on dubious stereotypes is often wrong, but acting on rigorous statistical generalizations can also be unjust. Consider a story recounted in Bryan Stevenson’s Just Mercy:

Story 2

“Once I was preparing to do a hearing in a trial court in the Midwest and was sitting at counsel table in an empty courtroom before the hearing. I was wearing a dark suit, white shirt, and tie. The judge and the prosecutor entered through a door in the back of the courtroom laughing about something.

When the judge saw me sitting at the defense table, he said to me harshly, ‘Hey, you shouldn’t be in here without counsel. Go back outside and wait in the hallway until your lawyer arrives.’

I stood up and smiled broadly. I said, ‘Oh, I’m sorry, Your Honor, we haven’t met. My name is Bryan Stevenson, I am the lawyer on the case set for hearing this morning.’

The judge laughed at his mistake, and the prosecutor joined in. I forced myself to laugh because I didn’t want my young client, a white child who had been prosecuted as an adult, to be disadvantaged by a conflict I had created with the judge before the hearing.”

This judge did something wrong. Because Bryan Stevenson is black, the judge assumed he was the defendant, not the defense. Now, I expect the judge acted on an implicit racist stereotype, but suppose the judge had instead reasoned from true statistical background data. It is conceivable that more of the Black people who enter that judge’s courtroom — even those dressed in suit and tie — are defendants than defense attorneys. Would shifting from stereotypes to statistics make the judge’s behavior ok?

No. The harm done had nothing to do with the outburst’s mental origins, whether it originated in statistics or stereotypes. Stevenson explains that what is destructive is the “accumulated insults and indignations caused by racial presumptions,” the burden of “constantly being suspected, accused, watched, doubted, distrusted, presumed guilty, and even feared.” This harm is present whether the judge acted on ill-formed stereotypes or statistically accurate knowledge of base-rates.

So, my own inference about Steve is not justified merely because it was grounded in a true statistical generalization. Still, I think I was right and the judge was wrong. Here is one difference between my inference and judge’s. I didn’t act as though I knew Steve was a farmer — I just concluded it was more likely he was. The judge didn’t act the way he would if he thought it was merely likely Stevenson was the defendant. The judge acted as though he knew Stevenson was the defendant. But the statistical generalizations we are considering cannot secure such knowledge.

The knowledge someone is a defendant justifies different behavior than the thought someone is likely a defendant. The latter might justify politely asking Stevenson if he is the defense attorney. But the latter couldn’t justify the judge’s actual behavior, behavior unjustifiable unless the judge knows Stevenson is not an attorney (and dubious even then). A curious fact about ethics is that certain actions (like asserting or punishing a criminal) require, not just high subjective credence, but knowledge. And since mere statistical information cannot secure knowledge, statistical generalizations are unsuitable justifications for some actions.

Statistical disparities can justify some differential treatment. For instance, seeing that so few of the Black people in his courtroom are attorneys could justify the judge in funding mock trial programs only at majority Black public schools. Indeed, it might even justify the judge, in these situations, only asking Black people if they are new defense attorneys (and just assuming white people are). But it cannot justify behavior, like harsh chastisement, that requires knowledge the person did something wrong.

I didn’t do anything that required knowledge that Steve was a farmer. So does this mean I’m in the clear? Maybe. But let’s consider one final story from the recent news:

Story 3

Due to COVID-19 the UK canceled A-level exams — a primary determinant of UK college admissions. (If you’re unfamiliar with the A-levels they are sort of like really difficult subject-specific SAT exams.) The UK replaced the exams with a statistical generalization. They subjected the grades that teachers and schools submitted to a statistical normalization based on the historical performance of the student’s school. Why did the Ofqual (Office of Qualifications and Examinations Regulation) feel the need to normalize the results? Well, for one thing, the predicted grades that teachers submitted were 12% higher than last year’s scores (unsurprising without any external test to check teacher optimism).

The normalization, then, adjusted many scores downward. If the Ofqual predicted, based on historical data, that at least one student in a class would have failed the exam then the lowest scoring student’s grade was adjusted to that failing grade (irrespective of how well the teacher predicted the student would have done).

Unsurprisingly, this sparked outrage and the UK walked back the policy. Student’s felt the system was unfair since they had no opportunity to prove they would have bucked the trend. Additionally since wealthier schools tended to perform better on the A-levels in previous years, the downgrading hurt students in poorer schools at a higher rate.

Now, this feels unfair. (And since justifiability to the people matters for government policy, I think the government made the right choice in walking back the policy.) But was it actually unfair? And if so, why?

It’s not an issue of stereotypes — the changes weren’t based on hasty stereotypes, but rather on a reasonable statistical generalization. It’s not an issue of compounding algorithmic bias (of the sort described in O’Neil’s book) as the algorithm didn’t produce results more unequal than actual test results. Nor was the statistical generalization used in a way that requires knowledge. College admissions don’t assume we know one student is better than another. Rather, they use lots of data to make informed guesses about which students will be the fit. The algorithm might sometimes misclassify, but so could any standardized test.

So what feels unfair? My hunch is the algorithm left no space for the exceptional. Suppose four friends who attended a historically poor performing school spent the last two years frantically studying together in a way no previous group had. Had they sat the test, all could have secured top grades — a first for the school. Unfortunately, they couldn’t all sit the test, and because their grades are normalized against previous years the algorithm eliminates their possibility of exceptional performance. (To be fair to the UK, they said students could sit the exams in the fall if they felt they could out-perform their predicted score).

But what is unfair about eliminating the possibility of exceptional success? My further hunch is that seeing someone as having the possibility of exceptional success is part of what it is to see them as an individual (perhaps for Kantian reasons of seeing someone as a free first cause of their own actions). Sure, we can accept that most people will be like most people. We can even be ok with wealthier schools, in the aggregate, consistently doing better on standardized tests. But we aren’t ok with removing the possibility for any individual to be an exception to the trend.

When my students resisted my claim that Steve was likely a farmer, they did not resist the generalization itself. They agreed most farmers are men and most librarians are women. But they were uncomfortable moving from that general ratio to a probabilistic judgment about the particular person, Steve. They seemed to worry that applying the generalization to Steve precluded seeing Steve as an exception.

While I think the students were wrong to think the worry applied in this case — factoring in base-rates doesn’t prevent the exceptional from proving their uniqueness — they might be right that there is a tension between seeing someone within a statistical generalization and seeing someone as an individual. It’s a possibility I should have recognized, and a further way acting on even good statistical generalizations might sometimes be wrong.

Prejudice in the NFL?

painting of lamar jackson in NFL game

The NFL is over for the next six months. The Superbowl has been won, all the player and coach accolades have been handed out, and teams are busy looking to build on the 2020-2021 season in free agency and the upcoming draft. But in today’s contemporary media environment, the NFL can’t be just about football. Over the past few seasons, the NFL has endured a series of serious media crisis–player safety, television ratings, and scandalous players (mostly Antonio Brown). But an issue that continues to linger is about diversity and the impact of racial issues on the game. This is no surprise to anyone, as the diversity issues were the subject of host Steve Harvey’s monologue at this year’s NFL 100 Awards ceremony. Indeed, the small pool of minorities that sit in front offices and on coaching staffs, as well as recent decisions regarding players of color raise the question of who’s to blame for the NFL’s diversity issues as well as who’s responsible for finding solutions for them.

70% of NFL players are black–the lineman, the runningbacks, the defense, the receiving core. But if you look at one position in particular, it’s not reflective of the majority demographic–the quarterback. Per The New York Times, 12 black quarterbacks started for the NFL 2019-2020 season, but it’s one QB short for tying the record of most black quarterback starts in a single season. There’s even been a bit of controversy regarding black quarterbacks in the last few seasons. The most recent being about the NFL 2019 MVP Lamar Jackson. The Ravens quarterback was unanimously voted the league’s most valuable player, but his talents weren’t always recognized. Many sports analysts, league owners, and coaches considered Jackson a running back disguised as a quarterback. Some even suggested that he move to the wide receiver position. On one hand, comments about Jackson’s game could be purely based on what he demonstrated at the combine. But on the other hand, a black man being judged predominantly by white males hints at something deeper. Maybe it wasn’t just Jackson’s performance at the combine, it was that he didn’t fit the traditional image of a NFL quarterback–Joe Montana, Dan Marino, or Tom Brady (who Jackson happened to beat last season). However, in the same token, Superbowl champ Patrick Mahomes and Texans QB Deshaun Watson are also impacting the traditional image of a quarterback through their style of play.

Lamar Jackson isn’t the only black quarterback that has received pushback for what he does on the field. There’s Colin Kaepernick, the former San Francisco 49ers QB who exited the league after kneeling on the sidelines during the national anthem in protest of police brutality of African Americans. Team GM’s, owners, and even the President of the United States condemned Kaepernick for his actions. Now, are the comments from NFL GM’s and owners indicative of prejudice? Like Lamar Jackson, Kaepernick’s critics were mostly white men. The fact that they were against speaking out against police brutality, no matter how controversial the topic might be for the league, is questionable. But at the same time, once Kaepernick left the league and couldn’t sign with a team, the main reason he couldn’t get a job was because he was considered a PR nightmare. Regardless if teams agreed with Kaep’s kneeling or not, no team wanted the news stories that would come from signing him. If so, then the issue of prejudice would be about the fans’ bias if they condemned Kaepernick for kneeling. To complicate matters even further, Dak Prescott, QB of the Dallas Cowboys, said that Kaepernick’s protests had no place in the league despite being a black man himself. Either way, some sentiment surrounding Jackson and Kaepernick might go beyond what they do on the field.

Jackson and Kaep are only the most recent cases though. Since black men were allowed to play quarterback in the league, they were often considered not smart enough to run offenses or read defenses. Marlin Briscoe, the first ever black quarterback to start in the league, threw 14 touchdowns during his rookie season with the Denver Broncos. John Elway, a legend Broncos QB, only threw half as many touchdowns as Briscoe during his rookie season. Despite the performance, Briscoe never played quarterback again. Warren Moon, the only black quarterback in the NFL Hall of Fame made MVP for the 1977 Rose Bowl and still wasn’t invited to the NFL Combine. He didn’t play in the NFL for six seasons after he left college. Like Jackson, Moon was also told to switch to running back or wide receiver.

The same negative sentiment didn’t only apply to players either. Although 70% of the players in the NFL are black, only 9% of the managers in league’s front offices are and 0% are CEO’s or team presidents. There is only one black general manager and out of the 32 NFL teams, 3 of the league’s head coaches are black. Back in 2003, the league introduced the Rooney Rule, a policy aimed at addressing the lack of diversity at the head coaching level. Per the Rooney Rule, teams are required to interview at least one minority for head-coaching positions and front office jobs. But per a study by the Global Sport and Education Lab at Arizona State University, the Rooney Rule didn’t improve minorities’ chances of being hired. According to The Atlantic, in the past three years 19 head coaching positions were made available and only 2 black coaches filled the openings. Some black coaches are rarely given a chance to make an impact on a team either. Former Detroit Lions coach Jim Caldwell was fired after back to back 9-7 records for the 2017 and 2018 season. Bob Quinn, the Lions’ GM, said that Caldwell wasn’t meeting expectations. But Quinn then went on to hire former New England Patriots defensive coordinator Matt Patricia, who went 9-22 in his first two seasons as head coach. Last season, the Lions record was 3-12-1.

It could be argued that rather than prejudice, the NFL’s diversity issues are purely “best man for the job” decisions. Teams look for the best quarterbacks that fit their offense and can lead a team. Team owners and GMs bring in coaches that can draw up plays accustomed to their team’s culture. But simultaneously, race is the driving force behind many if not all of the United States’ issues. Politics, advertising, music, fashion, literature, and every other medium that can be thought of is influenced by race is some form or fashion. Is it so farfetched to think that sports isn’t any different? Perhaps some personnel decisions are purely based on skill and compatibility. But at the same time, the league has been around for decades, and maybe some of the racist sentiment of the past century has seeped into the present.

The Jezebel Stereotype and Hip-Hop

photograph of Lil' Kim on stage

Back in the day, black people were depicted in media through a series of racist caricatures that endured the majority of the 20th century. These caricatures became popularized in films, television, cartoons, etc. There was the classic sambo–the simple minded black man often portrayed as lazy and incoherent. Then, there was the mammy–the heavyset black woman maid who possessed a head-scratching loyalty to her white masters. The picaninny depicted black children as buffoons and savages. The sapphire caricature was your standard angry black woman, a trope that is still often portrayed in media today. But perhaps one of the most enduring caricatures is that of the jezebel. This caricature had an insatiable need for sex, so much so that they were portrayed as predators. One of the ways that this stereotype has endured time is through hip-hop. It could be argued that some black women in the rap game today reflect some of the attributes of the jezebel due to the promiscuity in their music. Therefore, are black women in rap facilitating the jezebel stereotype and, in turn, adversely affecting the depiction of black women in general?

Before we get any further, it should be noted that rap music has never been kind to women, especially black women (see “Hip-Hop Misogyny’s Effects on Women of Color”). You wouldn’t have to look far to confirm this. After all, Dr. Dre’s iconic album The Chronic has a song called “Bitches Ain’t Shit” with uncle Snoop Dogg singing the hook. It’s become a staple in rap music to disregard women in some form or fashion. But perhaps a line from Kanye West’s verse on The Game’s song “Wouldn’t Get Far” best embodies treatment of women and black women in the rap genre. West raps “Pop quiz how many topless, black foxes did I have under my belt like boxers?” In the music video, a bunch of black women in bikinis dance around West while he raps. Black women in rap are presented as objects of sexual desire–they’re arm candy. It’s the updated version of the jezebel. Before, as a racist caricature, the jezebel stereotype was used by slave masters to justify sex with female slaves. But even prior to that, Europeans traveled to Africa and saw the women there with little to no clothing and practicing polygamy. To Europeans, this signaled an inherently promiscuous nature rather than a social tradition. To them, it meant sexual desire.

Now, there’s a narrative of black women rappers in hip-hop who are embracing their sexualization in media. Junior M.A.F.I.A rapper and the Notorious B.I.G. femme fatale Lil’ Kim started this trend, spitting verses that your parents definitely would not have let you listen to as a kid. For example, on her song “Kitty Box,” Kim raps,

“Picture Lil’ Kim masturbatin in a drop

Picture Lil’ Kim tan and topless on a yacht

Picture Lil’ Kim suckin on you like some candy

Picture Lil’ Kim in your shirt and no panties.”

Fast forward from Lil’ Kim, and there’s Nicki Minaj with her song “Anaconda,” where the music video features her and several other black women twerking. But even past Nikki Minaj, there’s new rapper Megan Thee Stallion, who, although having developed an original sound, seems to have traces of Kim and Minaj in her music. On her song “Big Ole Freak,” Megan raps,

“Pop it, pop it, daydreaming ‘bout how I rock it.

He hit my phone with a horse so I know that mean come over and ride it.”

Posing a compelling contrast to “Big Ole Freak,” is another MC, Doja Cat. In the music video for her song “Juicy,” Doja dances to her lyrics that sound like a mash up of Megan Thee Stallion and Nicki Minaj, rapping,

“He like the Doja and the Cat,

yeah, He like it thick he like it fat,

Like to keep him wanting more.”

Though Doja’s music has traces of that jezebel stereotype with sexual desire, there’s a positive aspect to it as well. With all of the sexual innuendos in “Juicy,” at its core, the song is about body positivity. While rapping about that “natural beauty,” Doja features women of all shapes and sizes in her music video and is unapologetic about her figure–it’s as if her message is more about empowerment than it is sex. Megan Thee Stallion also incorporates empowerment for women in her raps with the term she coined “Hot Girl Summer,” which to Megan, is where women are unapologetic about their sexuality and simply enjoying life. At the same time, women in rap have also always put forth some positive sentiment in their music. One of the pioneering rap artists for women were MC’s like Queen Latifah, Lauryn Hill, and MC Lyte. For example, in her song U.N.I.T.Y., Queen Latifah begins her verse by rapping,

“Every time I hear a brother call a girl a bitch or a ho,

Tryna make a sister feel low, You know all of that gots to go.”

So, are the rappers today merely facilitating the jezebel stereotype and sexualization of black women? True, the messages in their music are reminiscent of some aspects of the jezebel trope, but there’s an aspect of positivity that challenges this reductionist view. It could also be that rappers like Doja Cat and Megan Thee Stallion are just smart entrepreneurs who understand that sex sells and are simply capitalizing on an opportunity. But these rappers might also be changing the sexualization of black woman by taking over the narrative for themselves.

But what does this mean for the rest of us? How does this help the black women who have to endure that stereotype everyday? They don’t have the platform like Doja Cat and Megan Thee Stallion do to start trends and see its impact. But maybe that’s where trends like “Hot Girl Summer” come in handy here. While the music and image from rap artists like Doja and Megan seem negative to some, it’s a form of empowerment for black women. Perhaps listening to “Juicy” lets some black women feel proud about their bodies and trends like “Hot Girl Summer” let them feel unapologetic about their bodies. Simultaneously, it’s important to understand that as time passes, stereotypes–how we define people–change meaning or lose meaning completely. But with that said, it’s still important to not forget the history of where those ideas came from.

Implicit Bias and the Efficacy of Training

colored image of a human brain

On September 12th, California’s state legislature passed a series of measures designed to reduce unconscious biases among medical practitioners and other public servants; under the new laws, doctors, nurses, lawyers and court workers will be expected to undergo implicit bias training as a regular continuing education requirement. A number of advocacy groups argue that it is these unconscious biases that strongly contribute to wage gaps, differential education outcomes, criminal justice proceedings, and healthcare results – such as the fact that pregnant black women are three to four times more likely to die from complications during labor and delivery than are pregnant white women. Bias training is supposed to be a tool for chipping away at the generations of crystallized racism encasing our society.

The only problem is that implicit bias training probably doesn’t work – at least not in the way that people want it to. 

At this point, the data seem clear about two things: 

    1. Unconscious biases are pervasive elements of how we perceive our social environments, and
    2. Unconscious biases are exceedingly difficult to permanently change.

Since Saul Tversky and Daniel Kahneman first drew attention to the phenomenon of cognitive biases in the early 1970s, researchers have explored the varieties of mental shortcuts on which we daily rely; tricks like ‘confirmation bias,’ ‘the halo effect,’ ‘the availability heuristic,’ ‘anchoring’ and more have been explored by everything from psychologists and philosophers trying to understand the mind to marketers trying to convince customers to purchase products

One of the more surprising things about implicit biases is how they can sometimes conflict with your explicit beliefs or attitudes. You might, for example, explicitly believe that racism or misogyny is wrong while nevertheless harboring an implicit bias against minority groups or genders that could lead you to naturally react in harmful ways (either behaviorally or even just by jumping to an unfounded conclusion).  You can explore this sort of thing yourself: implicit association tests (IATs) purport to be able to peel back your natural assumptions to reveal some of the underlying mental shortcuts that operate behind the scenes of your normal thought processes. In general, implicit bias training aims to highlight these cognitive biases by making the implicit processes explicit, with the hope that this will allow people to make conscious choices they actually endorse thereafter.

However, a study published this month in The Journal of Personality and Social Psychology indicates that the demonstrable effect of a variety of implicit bias training modules was, at best, a short-term affair that did not contribute to lasting changes in either explicit measures or behavior. By analyzing evidence from nearly 500 separate studies, researchers discovered that, although implicit bias training seminars, workshops, classes, or other short-form lessons could provoke short-term shifts in mood or emotions, there was next-to-no evidence that these shifts would ultimately translate into different patterns of actual behavior

This fits with a general pattern of casting doubt on the efficacy of intensive bias training; in fact, by focusing on implicit problems (rather than the manifest explicit issues), some have argued that implicit training is simply distracting from the systemic issues underlying the real problem – some evidence even suggests that mandatory training (as opposed to voluntary exercises) might even make said biases stronger. Overall, this is likely intuitive: the notion that biased attitudes built up over decades of a person’s life could somehow simply be broken apart by a single day’s training is, at best, naive. 

If there is one consistent beneficiary of implicit bias training, it’s the companies mandating them. Consider what happened after a video of two black customers being racially profiled at a Starbucks in Philadelphia went viral: the coffee company closed its stores nationwide for several hours so that its workforce could undergo bias training. By appearing decisive, Starbucks was able to address (and generally sidestep) an intensely damaging PR incident at the cost of a few hours of profit. The fact that the bias training was not likely to effectively change the racist environment that precipitated the video was beside the point. As Brian Nosek, one of the psychologists who helped develop the IAT, put it, “I have been studying this since 1996, and I still have implicit bias.” Nonetheless, Starbucks apologized and the news cycle moved on.

So, it remains to be seen what the future holds for the state of California. Certainly, the move towards action regarding the problems of implicit bias is a step in the right direction. However, that sort of training by itself, without a systemic addressals of the institutional problems that promote oppressive environments (intentionally or otherwise), will be ultimately powerless.

Faulty Forensics: Justice, Knowledge, and Bias

image of police tape with police lights in background

In June, Netflix began releasing a series called “Exhibit A,” which debunks one form of crime investigative science per episode. Dubious forensic techniques have been exposed for decades, yet still have been successful in incarcerating countless people. There are a number of reasons that this should be troubling to all of us and motivate real change. One issue that highlights the severity of continuing to rely on debunked forensic techniques is what psychologists call the “CSI effect” – jurors place an over-valued amount of credulity on evidence based on forensic methods. Thus, in a trial scenario, it is not just that some evidence is not as reliable as it seems, but it is just this sort of evidence that jurors seem to cling to in making their decisions.

It is well-documented that, even in some circumstances that we believe ourselves to be working with logical facts, we can be swayed by socialized prejudices and biases about historically disenfranchised, stigmatized, and marginalized groups. This is obviously unfortunate because it can lead to the continued unjust circumstances and treatment of such groups. A great deal of policies in a criminal justice system are put in place in order to create a more objective and just system than would be attained were the suspicions and individual reasoning of particular people with a great deal of power given full reign over crime and punishment. Practices in trials, standards for evidence, protections of citizen’s rights, and other features in the criminal justice system are in place to correct for the ways that injustices are socialized into individual reasoning, and improvements have been attempted to combat implicit biases in individual policing in many districts as well.

Because humans are socialized with these heuristics in our reasoning that are influenced by stigma and prejudices, people in the criminal justice system rely on the science of forensics to be more objective than hunches, suspicions, and our sometimes unreliable reasoning. These tools are one method of separating the functioning of our justice system from the injustice of our society. However, doubt has been cast on a number of common methods of forensics and the reliability of these tools.

Ten years ago, a report by the National Academy of Sciences stated, “[w]ith the exception of nuclear DNA analysis, . . . no forensic method has been rigorously shown to have the capacity to consistently, and with a high degree of certainty, demonstrate a connection between evidence and a specific individual or source.” Blood splatter analysis, bite mark analysis, fingerprint analysis, and, perhaps most well-known to be unreliable, lie detector tests, all have had scientists’ doubt cast on them. The continued use of these methods in the court of law stacks the deck against defendants. Practitioners of the forensic methods “often believed their methods were reliable and their conclusions were accurate with little or no scientific foundation for their beliefs. As a consequence, judges and jurors were misled about the efficacy of forensic evidence, which too often resulted in wrongful convictions.”

Years ago, a study found that drug-sniffing dogs reacted to clues from the beliefs of their handlers. In the last two years there have been some efforts to develop training to minimize this bias. This is crucial for the system, for the drug-sniffing dogs are meant to be an objective way of detecting substances for further investigation, and, in most states, an alert form such a dog warrants police forces to further investigate citizens. If the canines are influenced by their perception of what their handlers think, then they are not a distinct source of information regarding whether potential illegal activity is taking place. If this is the case, the dogs’ actions should not be providing legal permission to search citizens beyond the officer’s suspicion: if the suspicion alone does not warrant search, then the dog’s behavior does not warrant search.

The problem with these methods isn’t that they aren’t completely objective or reliable, it is that they are currently playing a role in our criminal justice system that outstrips how objective or reliable they, in fact, are. When they are playing such a role in a system that so significantly alters lives, and does so at a disproportionate rate for groups that are marginalized already, it is crucial to critically engage with them as tools for legitimate investigation and trail.

Racist, Sexist Robots: Prejudice in AI

Black and white photograph of two robots with computer displays

The stereotype of robots and artificial intelligence in science fiction is largely of a hyper-rational being, unafflicted by the emotions and social infirmities like biases and prejudices that impair us weak humans. However, there is reason to revise this picture. The more progress we make with AI the more a particular problem comes to the fore: the algorithms keep reflecting parts of our worst selves back to us.

In 2017, research showed compelling evidence that AI picks up deeply ingrained racial- and gender-based prejudices. Current machine learning techniques rely on algorithms interacting with people in order to better predict correct responses over time. Because of the dependence on interacting with humans for standards of correctness, the algorithms cannot detect when bias informs a correct response or when the human is engaging in a non-prejudicial way. Thus, the best working AI algorithms pick up the racist and sexist underpinnings of our society. Some examples: the words “female” and “woman” were more closely associated with arts and humanities occupations and with the home, while “male” and “man” were closer to maths and engineering professions. Europeans were associated with pleasantness and excellence.

In order to prevent discrimination in housing, credit, and employment, Facebook has recently been forced to agree to an overhaul of its ad-targeting algorithms. The functions that determined how to target audiences for ads relating to these areas turned out to be racially discriminatory, not by design – the designers of the algorithms certainly didn’t encode racial prejudices – but because of the way they are implemented. The associations learned by the ad-targeting algorithms led to disparities in the advertising of major life resources. It is not enough to program a “neutral” machine learning algorithm (i.e., one that doesn’t begin with biases). As Facebook learned, the AI must have anti-discrimination parameters built in as well. Characterizing just what this amounts to will be an ongoing conversation. For now, the ad-targeting algorithms cannot take age, zip code, or gender into consideration, as well as legally protected categories.

The issue facing AI is similar to the “wrong kind of reasons” problem in philosophy of action. The AI can’t tell a systemic bias of humans from a reasoned consensus: both make us converge on an answer and support the algorithm to select what we may converge on. It is difficult to say what, in principle, the difference is between the systemic bias and a reasoned consensus is. It is difficult, in other words, to give the machine learning instrument parameters to tell when there is the “right kind of reason” supporting a response and the “wrong kind of reason” supporting the response.

In philosophy of action, the difficulty of drawing this distinction is illustrated by a case where, for instance, you are offered $50,000 to (sincerely) believe that grass is red. You have a reason to believe, but intuitively this is the wrong kind of reason. Similarly, we could imagine a case where you will be punished unless you (sincerely) desire to eat glass. The offer of money doesn’t show that “grass is red” is true, similarly the threat doesn’t show that eating glass is choice-worthy. But each somehow promote the belief or desire. For the AI, a racist or sexist bias leads to a reliable response in the way that the offer and threat promote a behavior – it is disconnected from a “good” response, but it’s the answer to go with.

For International Women’s Day, Jeanette Winterson suggested that artificial intelligence may have a significantly detrimental effect on women. Women make up 18% of computer science graduates and thus are left out of the design and directing of this new horizon of human development. This exclusion can exacerbate the prejudices that can be inherent in the design of these crucial algorithms that will become more critical to more arenas of life.

What Does It Mean To Be Implicitly Biased?

In 1998, a team of researchers founded Project Implicit for the purpose of identifying, measuring, and correcting implicit (i.e. subconscious) biases in the general public. Project Implicit is organized around the Implicit Association Test (IAT), a psychometric evaluation used to probe the depth and nature of bias in individuals. By showing test takers various pairings of words and concepts (“white,” “black,” “pleasant,” “unpleasant”), the IAT can determine which associations takers make more readily. Consistent lags in pairing a category, like “black,” with positive concepts, like “pleasant,” indicate that the test-taker is biased against that category of people.

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