Babies show racial bias at nine months, U of T study suggests

A pair of interesting studies, with some caveats by other researchers:

Two new University of Toronto studies suggest racial bias can develop in babies at an early age — before they’ve even started walking.

Led by the school’s Ontario Institute of Child Study professor Kang Lee, in partnership with researchers from the U.S., U.K., France, and China, the studies examined how infants react to individuals of their own race, compared to individuals of another race.

“The goal of the study was to find out at which age infants begin to show racial bias,” Lee said. “With existing studies, the evidence shows that kids show bias around 3 or 4 years of age. We wanted to look younger.”

The first study looked at 193 Chinese infants from three to ninth months, recruited from a hospital in China, who hadn’t had direct contact with people of other races. The babies were then shown videos of six Asian women and six African women, paired with either happy or sad music.

The study found that infants from three to six months old didn’t associate sad or happy music with people of the same race or of other races, which indicates they “are not biologically predisposed to associate own- and other-race faces with music of different emotional valence.”

However, at around nine months old, the reactions were different.

According to the study, nine-month-old babies looked at their own-race faces paired with happy music for a longer period of time, as well as other-race faces paired with sad music. Lee says this supports the hypothesis that infants associate people of the same race with happy music, and other races with sad music.

That’s not to say parents are teaching their children how to discriminate against other raced individuals, Lee says.

“We are very confident that the cause of this early racial bias is actually the lack of exposure to other raced individuals,” he said. “It tells us that in Canada, if we introduce our kids to other-raced individuals, then we are likely to have less racial bias in our kids against other-raced people.”

Andrew Baron, an associate professor of psychology the University of British Columbia, said while the goal of the study is “terrific,” there are many reasons infants would look for longer amounts of time at faces of different races. For example, he says an infant could spend more time looking at an own-race face because it is familiar, or at an other-race face because it is different and unexpected.

“It’s impossible to draw that conclusion about association from a single experiment when you could have half a dozen reasons why you would look longer that don’t support the conclusion that was made in that paper,” said Baron, who was not involved in the studies, but specializes in a similar field — the development of implicit associations among infants.

“There’s multiple reasons — and contradictory reasons — why we look longer at things. We look longer at things we fear, we look longer at things we like. That’s an inherent tension in how you choose to interpret the data.”

The second study took a closer look at that bias and how it affects children’s learning skills.

Researchers showed babies videos of own-race and other-race adults looking in the same direction that photos of animals appeared (indicating they are reliable) and looking in the wrong direction of the animals (indicating they are unreliable).

The study found that when adults were reliable and looking in the direction of the animals, the infants followed both own- and other-raced individuals equally. The same results occurred when the adults were unreliable and looking in the wrong direction.

However, when the adults gaze was only sometimes correct, the children were more likely to take cues provided by adults of their own race.

“In this situation, very interestingly, kids treated their own-raced individuals — who are only 50 per cent correct — as if they were 100 per cent correct,” Lee said.

“There is discrimination, but only when there is uncertainty.”

The first study was published in Developmental Science and the second was in Child Development.

The study was conducted in China, Lee says, because the researchers were able to control the exposure to other-raced individuals.

Lee said he has been trying for nearly 10 years to organize a study looking at babies born into mixed-race families. He suspects infants born into mixed-race families would show less racial bias.

When it comes to parents who want to try to eliminate racial bias from a young age, Lee says exposure is key.

“If parents want to prevent racial biases from emerging, the best thing to do is expose their kids to TV programs, books, and friends from different races,” he said.

“And the important message is they have to know them by name . . . it’s extremely important to know them as individuals.”

Source: Babies show racial bias at nine months, U of T study suggests | Toronto Star

A black woman in tech makes $79,000 for every $100,000 a white man makes – Recode

Impressive large-scale data analysis that show the extent of bias in the hiring process:

It’s no secret that the technology field can be brutal to anyone who isn’t a white male. New data shows just how those inequalities play out in today’s tech workers’ paychecks.

Nearly two in three women receive lower salary offers than men for the same job at the same company, according to Hired, a job website that focuses on placing people in tech jobs such as software engineer, product manager or data scientist. That’s slightly better than last year, when 69 percent of women received lower offers.

Women, on average, were paid 4 percent less than men for the same kind of job, the study found.

For the study, Hired mined data from 120,000 salary offers to 27,000 candidates at 4,000 companies. In general, applicants to these tech fields skew male (75 percent), but that doesn’t account for the disparity in who gets interviewed.

Companies interviewed only men for a position 53 percent of the time; 6 percent of the time, they interviewed only women.

“Not only are women getting lower offers when they actually get offers, but a large amount of time, companies have openings and they’re not interviewing women at all,” said Jessica Kirkpatrick, Hired’s data scientist.

Hired’s data also breaks down offer salaries by race, compared with a white man in the same job. The effects of race are even more dramatic:

  • Black women are offered 79 cents to every dollar offered to a white man.
  • Black men make 88 cents.
  • Latina women make 83 cents.
  • White women make 90 cents.

Additionally, LGBTQ women and men are offered less money than their non-LGBTQ counterparts.

There are numerous reasons for this pay inequity. Part of the problem is that women, minorities and LGBTQ people ask for less than white males for the same position.

According to Kirkpatrick, these groups ask for less because people base their salary expectations on what they’re already making. For these groups, their lower pay often reflects a lot of historical inequities accrued over their careers, like being denied raises or promotions.

By not offering people comparable wages, Kirkpatrick said that companies are jeopardizing their job retention. “When people figure out what their teammates are making, it’s ultimately not good for maintaining talent and creating a collegial environment,” she said.

It also makes Silicon Valley’s already tight talent pool even smaller.

Source: A black woman in tech makes $79,000 for every $100,000 a white man makes – Recode

Applying for a job in Canada with an Asian name: Policy Options

More good work on implicit biases and their effect on discrimination in hiring by Jeffrey G. Reitz, Philip Oreopoulos, and Rupa Banerjee:

Our most recent study analyzed factors that might affect discriminatory hiring practices: the size of an employer, the skill level of the posted job and the educational level of the applicant.

First, we divided the employers into large (500 or more employees), medium-sized (50 to 499 employees) and small (less than 50 employees). We expected that large employers might treat applicants more fairly because they have greater resources devoted to recruitment and often have a more professionalized recruitment process. They also tend to have more experience with ethno-racial diversity in their workforces.

Asian-named applicants’ relative callback rates were indeed the lowest in small and medium-sized organizations, and somewhat higher in the largest employers. Compared with applicants with Anglo names, the Asian-named applicants with all-Canadian qualifications got 20 percent fewer calls from the largest organizations, but 39 percent fewer from the medium-sized organizations and 37 percent fewer from the smallest organizations. So, the disadvantage of having an Asian name is less for applicants to the large organizations, although it is still evident.

Looking at treatment of Asian-named applicants with some foreign qualifications, we found the largest organizations are generally the most likely to call these applicants for interviews. Large employers called these applicants 35 percent less often than Anglo-Canadian applicants with Canadian education and experience; medium-sized employers called 60 percent less often, and the smaller employers called 66 percent less often.

We were also interested in whether the skill level of the job affected discriminatory hiring practices and, in particular, whether Asian-named applicants faced greater barriers in higher-skill jobs, which are likely to be better paid. We found that the extent of discrimination against Asian-named applicants with all-Canadian qualifications is virtually the same for both high-skill jobs and lower-skill jobs. For the high-skill jobs, these applicants were 33 percent less likely to get a call; for the low-skill jobs, 31 percent less likely.

Skill level matters much more when Asian-named applicants have some foreign qualifications. Overall, these applicants had about a 53 percent lower chance of receiving a callback than comparable Anglo-Canadian applicants. But their rate of receiving calls is significantly lower at higher skill levels: they receive 59 percent fewer callbacks for high-skill jobs, 46 percent fewer for low-skill jobs. Employers may respond less favourably to Asian-named and foreign-qualified applicants for higher-skill positions because in those jobs, more is at stake, and assessing foreign credentials is more difficult than checking local sources. Avoiding the issue by not calling applicants to an interview is apparently viewed as the safer option.

Finally, we asked whether having a higher level of education than Anglo-Canadian-named applicants would lessen the negative effect of having an Asian name. We found that Asian-named applicants with Canadian education including a Canadian master’s degree were 19 percent less likely to be called in for an interview than their Anglo-Canadian counterparts holding only a Bachelor’s degree. For Asian applicants with foreign qualifications and a Canadian master’s degree, the likelihood of a callback was 54 percent lower than the rate for less-educated Anglo-Canadian-named applicants. Acquiring a higher level of education in Canada did not seem to give Asian-named applicants much of an edge.

Overall, we found that employers both large and small discriminate in assessing Asian-named applicants, even when the applicants have Canadian qualifications; and they show even more reluctance to consider Asian-named applicants with foreign qualifications. These biases are particularly evident in hiring for jobs with the highest skill levels. However, there is a substantial difference between larger and smaller organizations. Larger organizations are more receptive to Asian-named applicants than smaller ones, whether or not the applicants have Canadian qualifications.

In order to fully understand the disadvantages that racial minorities experience in the Canadian labour market, it is crucial to go beyond surveys, in which discrimination may be hidden and difficult to identify. Audit studies like ours capture “direct discrimination” by observing actual employer responses to simulated resumés. This form of discrimination is particularly significant since the inability to get an interview may prevent potentially qualified job-seekers from finding appropriate work. Its effect may be compounded in promotions and other stages of the career process and in turn exacerbate ethno-racial income inequality in Canada.

Meanwhile, employers might also be unwittingly disadvantaged, because it can prevent them from finding the best-qualified applicants. Small employers are particularly disadvantaged since they may lack the resources and expertise to fully tap more diverse segments of the workforce.

A number of measures may help to reduce name-based discrimination in the hiring process. First, a relatively low-cost measure would be for employers to introduce anonymized resumés. They could simply mask the names of applicants during the initial screening, and then track whether this results in more diverse hiring. Second, employers should ensure that more than one person is involved in the screening and interview process and that the process of resumé evaluation is open and transparent. Lastly, hiring managers should receive training on implicit bias and how to recognize and mitigate their own biases when recruiting job applicants.

Source: Applying for a job in Canada with an Asian name

No simple fix to weed out racial bias in the sharing economy

Two options to combat implicit bias and discrimination: less information (blind cv approach) or more information (expanded online reviews). The first has empirical evidence behind it, the second is exploratory at this stage:

One of the underlying flaws of any workplace is the assumption that the cream rises to the top, meaning that the best people get promoted and are given opportunities to shine.

While it’s tempting to be lulled into believing in a meritocracy, years of research on women and minorities in the work force demonstrate this is rarely the case. Fortunately, in most corporate settings, protocols exist to try to weed out discriminatory practices.

The same cannot necessarily be said for the sharing economy. While companies such as Uber and Airbnb boast transparency and even mutual reviews, they remain far from immune to discriminatory practices.

In 2014, Benjamin Edelman and Michael Luca, both associate professors of business administration at Harvard Business School, uncovered that non-black hosts can charge 12 per cent more than black hosts for a similar property. In this new economy, that simply means non-white hosts earn less for a similar service. This sounds painfully familiar to those who continue to fight this battle in the corporate world – although in this case, it occurs without the watchful eye of a human-resources division.

In the corporate world, companies have moved from focusing on overt to subconscious bias, according to Mr. Edelman and Mr. Luca, but the nature of the bias in the sharing economy remains unclear.

It’s either statistical, meaning users infer that the property remains inferior based on the owner’s profile, or “taste-based,” suggesting the decision to rent comes down to user preference. To curb discriminatory practices, the authors recommend concealing basic information, such as photos and names, until a transaction is complete, as on Craigslist.

Reached by e-mail this week, Mr. Edelman stands by that approach.

“Broadly, my instinct is to conceal information that might give rise to discrimination. If we think hosts might reject guests of [a] disfavoured race, let’s not tell hosts the race of a guest when they’re deciding whether to accept. If we think drivers might reject passengers of [a] disfavoured race, again, don’t reveal the race in advance,” he advised.

While Mr. Edelman feels those really bent on discrimination will continue to do so, other, more casual discriminators will realize it’s too costly.

An Uber driver who only notices a passenger’s race at the pickup point might think to himself he already has driven about five kilometres. If he cancels, not only will he be without a fare, but also Uber might notice and become suspicious, Mr. Edelman surmised.

Not everyone agrees that less information is the best route to take to combat discrimination in the sharing economy. In fact, more information may be the fix, according to recent research conducted by Ruomeng Cui, an assistant professor at Indiana University’s Kelley School of Business, Jun Li, an assistant professor at the University of Michigan’s Stephen M. Ross School of Business, and Dennis Zhang, an assistant professor at the John M. Olin Business School at Washington University in Saint Louis.

The trio of academics argues that rental decisions on platforms such as Airbnb are based on racial preferences only when not enough information is available. When more information is shared, specifically through peer reviews, discriminatory practices are reduced or even eliminated.

“We recommend platforms take advantage of the online reputation system to fight discrimination. This includes creating and maintaining an easy-to-use online review system, as well as encouraging users to write reviews after transactions. For example, sending multiple e-mail reminders or offering monetary incentives such as discounts or credits, especially for those relatively new users,” Dr. Li said.

“Eventually, sharing-economy platforms have to figure how to better signal user quality; nevertheless, whatever they do, concealing information will not help,” she added.

Still, others believe technology itself can offer a solution to the incidents of bias in the sharing economy, such as Copenhagen-based Sara Green Brodersen, founder and chief executive of Deemly, which launched last October. The company’s mission is to build trust in the sharing economy through social ID verification and reputation software, which enables users to take their reputation with them across platforms. For example, if a user has ratings on Airbnb, they can collate it with their reviews on Upwork.

“Recent studies in this area suggest that ratings and reviews are what creates most trust between peers. [For example] when a user on Airbnb looks at a host, they put the most emphasis on the previous reviews from other guests more than anything else on the profile. Essentially, this means platforms could present anonymous profiles showing only the user’s reputation, but not gender, profile picture, ethnicity, name and age and, in this way, we can avoid the bias which has been presented,” Ms. Brodersen said.

Regardless of the solution, platforms and their users need to recognize that combatting discriminatory practices is their responsibility and the sharing economy, like the traditional work force, is no meritocracy.

“This issue is not going to be smaller on its own,” Ms. Brodersen warned.

Source: No simple fix to weed out racial bias in the sharing economy – The Globe and Mail

Barbara Kay: Actually, it turns out that you may be less racist than you’ve been led to believe

What Kay misses is the usefulness of the IAT for people to become more mindful of their implicit biases, and, in so doing, be more aware of their “thinking fast” mode to use Kahneman’s phrase.

It is not automatic that being more mindful or aware changes behaviour but it can play a significant role (and yes, the benefits can be overstated). Having implicit biases does not necessarily mean acting on them.

Kay did not mention whether or not she took the test. Given her biases evident in her columns, it would be interesting to know whether she took the IAT and what, if anything, she learned.

I certainly found it useful, revealing and most important, discomforting as I became more aware of the gap between my policy mind and views, and what was under the surface.

Anyone can take the test on the Project Implicit Website, hosted by Harvard U. By October 2015, more than 17 million individuals had completed it (with presumably 90-95 per cent of them then self-identifying as racist). Liberal observers love the IAT. New York Times columnist Nicholas Kristof wrote in 2015, “It’s sobering to discover that whatever you believe intellectually, you’re biased about race, gender, age or disability.” Kristof’s tone is more complacent than sober, though. For progressives, the more widespread bias can be demonstrated to be, the more justifiable institutional and state intrusions into people’s minds become.

Banaji and Greenwald have themselves made far-reaching claims for the test: the “automatic White preference expressed on the Race IAT is now established as signaling discriminatory behavior. It predicts discriminatory behavior even among research participants who earnestly (and, we believe, honestly) espouse egalitarian beliefs. …. Among research participants who describe themselves as racially egalitarian, the Race IAT has been shown, reliably and repeatedly, to predict discriminatory behavior that was observed in the research.”

Problem is, none of this can be authenticated. According to Singal, a great deal of scholarly work that takes the shine off the researchers’ claims has been ignored by the media. The IAT is not verifiable and correlates weakly with actual lived outcomes. Meta-analyses cannot examine whether IAT scores predict discriminatory behaviour accurately enough for real-world application. An individual can score high for bias on the IAT and never act in a biased manner. He can take the test twice and get two wildly different scores. After almost two decades, the researchers have never posted test-retest reliability of commonly used IATs in publication.

It’s a wonder the IAT has a shred of credibility left. In 2015 Greenwald and Banaji responded to a critic that the psychometric issues with race and ethnicity IATS “render them problematic to use to classify persons as likely to engage in discrimination,” and that “attempts to diagnostically use such measures for individuals risk undesirably high rates of erroneous classifications.” Greenwald acknowledged to Singal that “no one has yet undertaken a study of the race IAT’s test-related reliability.” In other words, the IAT is a useless tool for measuring implicit bias.

In an interesting aside, Singal points to a 2012 study published in Psychological Science by psychologist Jacquie Vorauer. As her experiment, Vorauer set white Canadians to work with aboriginal partners. Before doing so, some of the participants took an IAT that pertained to aboriginals, some took a non-race IAT and others were asked for their explicit feelings about the group. Aboriginals in the race-IAT group subsequently reported feeling less valued by their white partners as compared to aboriginals in all of the other groups. Vorauer writes, “If completing the IAT enhances caution and inhibition, reduces self-efficacy, or primes categorical thinking, the test may instead have negative effects.” As Singal notes, this “suggests some troubling possibilities.”The IAT has potentially misinformed millions of test-takers, who believe that they are likely to act, or are routinely acting, with bias against their fellow citizens. Harbouring biases is part of the human condition, and it is our right to hold them, especially those warranted by epidemiology and reason. Our actions are all that should concern our employers or the state’s legal apparatus. Any directive to submit to the IAT by the state or a state-sponsored entity like the CBC constitutes an undemocratic intrusion into the individual’s privacy.

Source: Barbara Kay: Actually, it turns out that you may be less racist than you’ve been led to believe | National Post

Bias Isn’t Just A Police Problem, It’s A Preschool Problem : NPR

Worth reading in terms of just how embedded implicit bias is:

New research from the Yale Child Study Center suggests that many preschool teachers look for disruptive behavior in much the same way: in just one place, waiting for it to appear.

The problem with this strategy (besides it being inefficient), is that, because of implicit bias, teachers are spending too much time watching black boys and expecting the worst.

The Study

Lead researcher Walter Gilliam knew that to get an accurate measure of implicit bias among preschool teachers, he couldn’t be fully transparent with his subjects about what, exactly, he was trying to study.

Implicit biases are just that — subtle, often subconscious stereotypes that guide our expectations and interactions with people.

“We all have them,” Gilliam says. “Implicit biases are a natural process by which we take information, and we judge people on the basis of generalizations regarding that information. We all do it.”

Even the most well-meaning teacher can harbor deep-seated biases, whether she knows it or not. So Gilliam and his team devised a remarkable — and remarkably deceptive — experiment.

At a big, annual conference for pre-K teachers, Gilliam and his team recruited 135 educators to watch a few short videos. Here’s what they told them:

“We are interested in learning about how teachers detect challenging behavior in the classroom. Sometimes this involves seeing behavior before it becomes problematic. The video segments you are about to view are of preschoolers engaging in various activities. Some clips may or may not contain challenging behaviors. Your job is to press the enter key on the external keypad every time you see a behavior that could become a potential challenge.”

Each video included four children: a black boy and girl and a white boy and girl.

Here’s the deception: There was no challenging behavior.

While the teachers watched, eye-scan technology measured the trajectory of their gaze. Gilliam wanted to know: When teachers expected bad behavior, who did they watch?

“What we found was exactly what we expected based on the rates at which children are expelled from preschool programs,” Gilliam says. “Teachers looked more at the black children than the white children, and they looked specifically more at the African-American boy.”

Indeed, according to recent data from the U.S. Department of Education, black children are 3.6 times more likely to be suspended from preschool than white children. Put another way, black children account for roughly 19 percent of all preschoolers, but nearly half of preschoolers who get suspended.

One reason that number is so high, Gilliam suggests, is that teachers spend more time focused on their black students, expecting bad behavior. “If you look for something in one place, that’s the only place you can typically find it.”

The Yale team also asked subjects to identify the child they felt required the most attention. Forty-two percent identified the black boy, 34 percent identified the white boy, while 13 percent and 10 percent identified the white and black girls respectively.

The Vignette

The Yale study had two parts. And, as compelling as the eye-scan results were, Gilliam’s most surprising takeaway came later.

He gave teachers a one-paragraph vignette to read, describing a child disrupting a class; there’s hitting, scratching, even toy-throwing. The child in the vignette was randomly assigned what researchers considered a stereotypical name (DeShawn, Latoya, Jake, Emily), and subjects were asked to rate the severity of the behavior on a scale of one to five.

White teachers consistently held black students to a lower standard, rating their behavior as less severe than the same behavior of white students.

Gilliam says this tracks with previous research around how people may shift standards and expectations of others based on stereotypes and implicit bias. In other words, if white teachers believe that black boys are more likely to behave badly, they may be less surprised by that behavior and rate it less severely.

Black teachers, on the other hand, did the opposite, holding black students to a higher standard and rating their behavior as consistently more severe than that of white students.

Here’s another key finding: Some teachers were also given information about the disruptive child’s home life, to see if it made them more empathetic:

[CHILD] lives with his/her mother, his/her 8- and 6-year old sisters, and his/her 10-month-old baby brother. His/her home life is turbulent, between having a father who has never been a constant figure in his/her life, and a mother who struggles with depression but doesn’t have the resources available to seek help. During the rare times when his/her parents are together, loud and sometimes violent disputes occur between them. In order to make ends meet, [CHILD’s] mother has taken on three different jobs, and is in a constant state of exhaustion. [CHILD] and his/her siblings are left in the care of available relatives and neighbors while their mother is at work.

Guess what happened.

Teachers who received this background did react more empathetically, lowering their rating of a behavior’s severity — but only if the teacher and student were of the same race.

Source: Bias Isn’t Just A Police Problem, It’s A Preschool Problem : NPR Ed : NPR

Surprising New Evidence Shows Bias in Police Use of Force but Not in Shootings – The New York Times

Surprising_New_Evidence_Shows_Bias_in_Police_Use_of_Force_but_Not_in_Shootings_-_The_New_York_TimesUnderlying bias and discrimination remains of concern, but useful nuance to current debates:

new study confirms that black men and women are treated differently in the hands of law enforcement. They are more likely to be touched, handcuffed, pushed to the ground or pepper-sprayed by a police officer, even after accounting for how, where and when they encounter the police.

But when it comes to the most lethal form of force — police shootings — the study finds no racial bias.

“It is the most surprising result of my career,” said Roland G. Fryer Jr., the author of the study and a professor of economics at Harvard. The study examined more than 1,000 shootings in 10 major police departments, in Texas, Florida and California.

The result contradicts the image of police shootings that many Americans hold after the killings (some captured on video) of Michael Brown in Ferguson, Mo.; Tamir Rice in Cleveland; Walter Scott in South Carolina; Alton Sterling in Baton Rouge, La.; and Philando Castile in Minnesota.

The study did not say whether the most egregious examples — those at the heart of the nation’s debate on police shootings — are free of racial bias. Instead, it examined a larger pool of shootings, including nonfatal ones.

The counterintuitive results provoked debate after the study was posted on Monday, mostly about the volume of police encounters and the scope of the data. Mr. Fryer emphasizes that the work is not the definitive analysis of police shootings, and that more data would be needed to understand the country as a whole. This work focused only on what happens once the police have stopped civilians, not on the risk of being stopped at all. Other research has shown that blacks are more likely to be stopped by the police.

Photo

Roland G. Fryer Jr., a professor of economics at Harvard. CreditErik Jacobs for The New York Times 

Mr. Fryer, the youngest African-American to receive tenure at Harvard and the first to win a John Bates Clark medal, a prize given to the most promising American economist under 40, said anger after the deaths of Michael Brown, Freddie Gray and others drove him to study the issue. “You know, protesting is not my thing,” he said. “But data is my thing. So I decided that I was going to collect a bunch of data and try to understand what really is going on when it comes to racial differences in police use of force.”

Source: Surprising New Evidence Shows Bias in Police Use of Force but Not in Shootings – The New York Times

We never see Trump or Brexit coming because we drown in data and biases – Implicit Bias

Good piece by Mike Ross, Davide Pisanu and Blanche Ajarrista on the risks of bias and automatic thinking and the need to be more mindful:

Three ways to diminish the risk of overreliance on analytics or biased forecasting are the use of premortems, devil’s advocates and self-reflection. Tools that we all (including the market research organizations and newsrooms of the world) can implement more systematically to avoid shocks such as the Brexit result.

  • Premortems start with imagining that you are wrong, dead wrong, and that the worst has occurred. You then ask, what could be the cause of this predictive failure? Through this type of questioning, we can identify the limitations of the available data and dig deeper to improve the quality of the quality of the information used.
  • A devil’s advocate is appointed to ensure that contrarian positions have a voice at the table when groups are making decisions, but they are also useful on an individual basis. This person’s role is to argue against the group’s intention – essentially stating why everyone else is wrong. By clearly nominating someone to take this on (or by forcing yourself to question your own assumptions in this way), we free the advocate from the constraint of not wanting to go against the position of the group and in doing so allow them to highlight our collective blind spots.
  • Self reflection (by an individual or a group) is more of a habitual practice – ensuring that you think deeply on how your background, beliefs and socioeconomic context heavily bias your views. From the people you regularly interact with to the Facebook algorithm that pushes content to your stream, your view of the world is curated by your context. Forcing yourself to acknowledge this and actively seek out opinions counter to your own will diminish the influence your personal situation has on your decision-making, broaden your context and expand the range of data you’ll use to inform your decisions.

It’s not that data and analytics are inherently bad or that our biases are not useful in decision-making, but rather that these can be flawed.

By recognizing and using a set of tools to overcome these flaws, we can be much more effective decision-makers and avoid (and perhaps profit from) the shocking and the unexpected.

Source: We never see Trump or Brexit coming because we drown in data and biases – The Globe and Mail

We Just Can’t Handle Diversity: HBR

We_Just_Can’t_Handle_DiversityGood long read by Lisa Burrell at HBR and the difficulties in ensuring diversity given our implicit biases and automatic thinking:

Senior leaders need to recognize their organizations’ inequities—probably more than anyone else, since they have the power to make changes. But once they’ve climbed to their positions, they usually lose sight of what they had to overcome to get there. As a result, Rosette and Tost find, “they lack the motivation and perspective to actively consider the advantages that dominant-group members experience.” This is especially true of successful white women, who “reported [even] lower perceptions of White privilege than did highly successful White men.” It’s fascinating that their encounters with sexism don’t help them identify racial advantage after they’ve gotten ahead. Perhaps, the authors suggest, their hard-earned status feels so tenuous that they reflexively tighten their grip.

Beyond murkily defined concepts and somewhat defensive motivations, we have an even-higher-level conceptual obstacle to overcome: our bias against diversity itself. Recent research by Ohio State University’s Robert Lount Jr. and colleagues (Oliver Sheldon, of Rutgers; Floor Rink, of Groningen; and Katherine Phillips, of Columbia) shows that we assume diversity will spark interpersonal conflict. Participants in a series of experiments all read, watched, or listened to the exact same conversations among various groups. They consistently perceived the all-black or all-white groups as more harmonious than those with a combination of blacks and whites.

If we expect people to behave less constructively when they’re in diverse organizations or teams, how do we interpret and reward their actual performance? Under the influence of those flawed expectations? Quite possibly.

So, Is It Hopeless?

According to the renowned behavioral economist Daniel Kahneman, trying to outsmart bias at the individual level is a bit of a fool’s errand, even with training. We are fundamentally overconfident, he says, so we make quick interpretations and automatic judgments. But organizations think and move much more slowly. They actually stand a chance of improving decision making.

Research by John Beshears and Francesca Gino, of Harvard Business School, supports that line of thought. As they have written in HBR, “It’s extraordinarily difficult to rewire the human brain,” but we can “alter the environment in which decisions are made.” This approach—known as choice architecture—involves mitigating biases, not reversing them, and Beshears and Gino have found that it can lead to better outcomes in a wide range of situations. The idea is to deliberately structure how you present information and options: You don’t take away individuals’ right to decide or tell them what they should do. You just make it easier for them to reach more-rational decisions. (For more on this idea, also see “Designing a Bias-Free Organization,” an interview with Harvard behavioral economist Iris Bohnet.)

There’s still an element of manipulation here: The organization sets the stage for certain kinds of choices. But that brings us back to what most of us can agree on, at least in the abstract: Diversity improves performance, and people who apply themselves and do good work should be treated fairly.

If the members of an organization could get behind those broad ideas, would it bother them that they were being nudged to do what they wanted to do anyway? It might—and that would be another cognitive roadblock to clear.

Source: We Just Can’t Handle Diversity

Interesting that the recent public service discussions on diversity, judging by reports I have seen, show no evidence of this deeper thinking of the challenges involved (even if, judging by the numbers, the public service is reasonably diverse – see Diversity and Inclusion Agenda: Impact on the Public Service, Setting the baseline).

When making a presentation on multiculturalism and the government’s inclusion and diversity agenda this week at Canadian Heritage, my assigned ‘homework’ for attendees was to take the Harvard-developed Implicit Association Test to be more mindful of their internal biases and prejudices. It certainly was revealing to me, as it has been to those I know who have taken it:

Public Servants Get Real About Diversity in the Public Service

How Talking To People Can Reduce Prejudice

Interesting example of how face-to-face conversations that help people understand the other’s experiences, and identify some commonalities, can make a difference:

After the dust settled [from a previously falsified study], Broockman and Kalla went on with their experiment on transgender prejudices. LaCour’s misconduct only made them more determined to do the study for real. “There were all these volunteers who gave their Saturdays [to do the experiment],” Broockman says. “We had a certain sense of responsibility.”

They sent out surveys to thousands of homes in Miami, asking people to answer questions that included how they felt about transgender people and if they would support legal protection against discrimination for transgender people. Then volunteers from SAVE, an LGBT advocacy organization based in Florida, visited half of the 501 people who responded and canvassed them about an unrelated topic, recycling. Volunteers went to the other half and started the conversations that Fleischer thinks can help change minds.

After the canvass, the study participants answered the same questions about transgender people that they had answered before the study, including how positively or negatively they felt towards transgender people on a scale of 0 to 100. Those who had discussed prejudice they’d experienced felt about 10 points more positively toward transgender people, on average.

Broockman says that public opinion about gay people has improved by 8.5 points between 1998 and 2012. “So it’s about 15 years of progress that we’ve experienced in 10 minutes at the door,” he says.

Three months after the canvass, Broockman asked participants to fill out the survey again. They still felt more positively about transgender people than those who had gotten the unrelated canvass. “[That’s] the moment I backed away from my monitor and said, ‘Wow, something’s really unique here,’ ” he says. If the effect persists, Broockman says, the technique could be used to reduce prejudice across society.

That doesn’t mean everybody came away feeling more positive about transgender rights. Kalla says some people came away from the canvasser feeling very differently and some people not so much at all. And an uptick in 10 points on a feeling scale of 0 to 100 doesn’t sound like an epiphany. There wasn’t, however, any indication that those who started out with very negative feelings about transgender people were particularly resistant to the conversation. Broockman and Kalla published the results in Science on Thursday.

It is a landmark study, according to Elizabeth Paluck, a psychologist at Princeton University who was not involved with the work. “They were very transparent about all the statistics,” she says. “It was a really ingenious test of the change. If the change was at all fragile, we should have seen people change their minds back [after three months].” There are very few tests of prejudice reduction methods, and Paluck says this suggests the Los Angeles LGBT Center’s approach is actually far more effective than previous efforts, like TV ads.

There might be a couple of reasons for that. Broockman, now an assistant professor of political economy at Stanford University, says asking someone questions face-to-face like, “What are the reasons you wouldn’t support protections for transgender people, or what does this make you think about?” gets them to begin thinking hard about the issue. “Burning the mental calories to do effortful thinking about it, that leaves a lasting imprint on your attitudes,” he says.

Empathy may also be a factor. “Canvassers asked people to talk about a time they were treated differently. Most people have been judged because of gender, race or some other issue. For many voters, they reflect on it and they realize that’s a terrible feeling they don’t want anyone to have,” Broockman says.

The study’s conclusions differ from the conclusions of the LaCour’s falsified study from 2014 in one crucial way, Broockman says. LaCour claimed that there was only an effect from the deep canvass if it came from someone who was LGBT. “We found non-trans allies had a lasting effect as well,” Broockman says. That means canvassing is much more about conversational skill rather than identity.

It will take more studies and replications of this study before scientists know exactly what is influencing people’s opinions. But for now, the findings are a relief to David Fleischer. “To go into it with high hopes and then get this really bad piece of news, then to go forward anyway and have the accurate results? What a roller coaster of emotions,” he says.

The technique might be used to target any societal prejudice — or be used to increase prejudice, Broockman acknowledges. But even if that happens, he says, it at least will encourage people to think deeply about the issues they’re going to vote on.

Source: How Talking To People Can Reduce Prejudice : Shots – Health News : NPR