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3 cognitive biases perpetuating racism at work — and how to overcome them
Researchers say that moral self-licensing occurs "because good deeds make people feel secure in their moral self-regard."

Books about race and anti-racism have dominated bestseller lists in the past few months, bringing to prominence authors including Ibram Kendi, Ijeoma Oluo, Reni Eddo-Lodge, and Robin DiAngelo.
Sales of these books increased by up to 6,800% in the aftermath of global protests against racial injustice, according to Forbes, showing the role such work plays in raising awareness and leading to a cultural reckoning.
While readers learned about allyship, companies also showed their strengthened resolve to tackle racial inequality by making public statements on their social media accounts, and releasing detailed action plans with their commitments to change. It is still too early to say what affect these individual and collective actions will have in the long-term, and whether reading books on anti-racism and making public statements will result in a more just society where everyone has access to the same opportunities and is treated fairly.
But what we do know is that lasting, positive change is difficult to achieve without deliberate, sustained effort informed by reliable data that is free from bias.
And it's important not to underestimate the role cognitive bias can play in undermining these efforts - and to stay vigilant in spotting and mitigating it.
What is cognitive bias?
Human brains are hardwired to take shortcuts when processing information to make decisions, resulting in "systematic thinking errors", or unconscious bias.
When it comes to influencing our decisions and judgments around people, cognitive or unconscious bias is universally recognized to play a role in unequal outcomes for people of colour.
This helps to explain why unconscious bias training is often the first resort for companies looking to build more inclusive workplaces, with outcomes that may be highly variable and, at times, result in little measurable improvement.
These three cognitive biases are likely to be at play and could influence our decisions:
1. Moral licensing
This is when people derive such confidence from past moral behaviour that they are more likely to engage in immoral or unethical ways later.
In a 2010 study, researchers argued that moral self-licensing occurs "because good deeds make people feel secure in their moral self-regard", and future problematic behaviour does not evoke the same feelings of negative self-judgment that it otherwise would.
Participants who had voiced support for US President Barack Obama just before the 2008 election were less likely, when presented with a hypothetical slate of candidates for a police force job, to select a Black candidate for the role.
As the study authors hypothesize, "presumably, the act of expressing support for a Black presidential candidate made them feel that they no longer needed to prove their lack of prejudice". Other research shows that implicit and explicit attitudes toward African Americans did not substantively change during the period of the Obama presidency.
Moral licensing may help explain the limitations of corporate unconscious bias training in creating an anti-racist work environment, an effect which has already been observed when it comes to tackling gender inequality.
Iris Bohnet, a behavioural economist, suggests that "diversity programs aimed at influencing the worst offenders might backfire… Training designed to raise awareness about gender and race inequality may end up making gender and race more salient and thereby highlighting differences."
2. Affinity bias
This is our tendency to get along with others who are like us, and to evaluate them more positively than those who are different. Our personal beliefs, assumptions, preferences, and lack of understanding about people who are not like us may lead to repeatedly favouring 'similar-to-me' individuals.
In organizations, this often affects who gets hired, who gets promoted, and who gets picked for opportunities to manage people or projects.
Employees who look like those already in leadership are given opportunities to develop their careers, due to affinity bias, resulting in a lack of representation in senior leadership roles for BIPOC.
Affinity bias is particularly insidious in recruitment processes, where it presents as a lack of "culture fit", an ambiguous evaluation that should be avoided as an explanation for declining to hire a candidate.
Many hiring managers have a hard time articulating their organization's specific culture, or explaining what exactly they mean when they say "culture fit", leading to this being misused to engage employees that managers feel they will personally relate to.
3. Confirmation bias
This is the tendency to seek out, favour, and use information that confirms what you already believe. The other side of this is that people tend to ignore new information that goes against their preconceived notions, leading to poor decision-making.
It can hinder efforts to create and nurture an antiracist workplace culture, and also contributes to the limited effectiveness of unconscious bias training, together with moral licensing and affinity bias.
Many people's perceptions of others with different identities and with whom they have limited interaction, is strongly influenced by media depictions and longstanding cultural stereotypes.
For example, a 2017 study published in the American Psychological Association's Journal of Personality and Social Psychology found that people tended to perceive young Black men as taller, heavier, and more muscular than similarly sized white men, and hence more physically threatening.
Persistent notions about female or BIPOC candidates being inherently less qualified than white male candidates can undermine efforts to increase diversity, because such candidates are more likely to be negatively evaluated and ultimately not selected.
Confirmation bias also helps to explain why Asian Americans are underrepresented in leadership positions despite outperforming other minorities and white people in the US on education, employment and income. Long-held stereotypes lead to Asian Americans being seen as modest, deferential, and low in social skills, while at the same time penalizing those who adopt more dominant behaviours.
How to overcome unconscious bias
1. Change systems, not individuals
The main reason unconscious bias training programmes fail to have the desired effect in creating lasting change, is that they are focused on changing individual behaviours while leaving largely untouched the systems that enabled those behaviours to thrive.
Individual biases are difficult to shift in the long term, and the academic evidence suggests that knowing about bias does not result in changes in behaviour by managers and employees.
The whole social environment - rather than the individual - needs to be addressed. This can be done by implementing company policies and programmes designed to mitigate bias through all stages of the employee's journey, from selection processes to performance ratings and promotion decisions.
These structures, which should be audited regularly, are important in ensuring that any individual's own bias is limited and does not influence decisions at an organizational level.
Such structural initiatives may end up influencing social norms within organizations, so behavioural change happens on a larger group level, leading to improved compliance from individuals as they gain a new understanding of socially-acceptable behaviour.
2. Slow down and act deliberately
Bias is most likely to affect decision-making when decisions are made quickly, according to Stanford University psychology professor Jennifer Eberhardt, who studies implicit bias in police departments.
We are less likely to act on bias when we slow down and control our thoughts, consciously overcoming first impressions and the biases that come with them.
This is where unconscious bias training may have an impact, because self-awareness and education are key to shifting mindsets. Such mindset shifts are needed for people of colour as well, as research shows that they are equally subject to the unconscious bias provoked by negative stereotypes.
At work, slowing down may take the form of ensuring that one person's biases do not contaminate processes through establishing control mechanisms: ensuring a diversity of feedback givers during recruitment processes, and establishing structured interviews with the same set of defined questions and evaluation criteria for each candidate.
3. Set concrete goals and work towards them
Data is essential to making real progress on diversity goals, and especially important when it comes to mitigating the effects of bias because it provides an objective measure of what has improved – or worsened – over time.
The goals themselves will be specific to each organization's needs and context. But taking into consideration local variables such as countries of operation, company size, business goals, and organizational culture, setting goals and tracking progress in a transparent way ensures the environmental change (as opposed to individual) that is needed for success.
Data is key to buy-in, and companies can increase accountability by collecting and analysing data on diversity over time, comparing the numbers with those at other organizations, and sharing them with key stakeholders internally and externally.
Data collection also helps companies identify roadblocks, and engage with key stakeholders on strategies to address them.
Reprinted with permission of the World Economic Forum. Read the original article.
- Can A.I. remove human bias from the hiring process? - Big Think ›
- The Difference Between Implicit Bias and Racism - Big Think ›
How New York's largest hospital system is predicting COVID-19 spikes
Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting
<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />Northwell emergency departments use the dashboard to monitor in real time.
Credit: Northwell Health
<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>Making machine-learning tools openly accessible
<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>Listen: Scientists re-create voice of 3,000-year-old Egyptian mummy
Scientists used CT scanning and 3D-printing technology to re-create the voice of Nesyamun, an ancient Egyptian priest.
- Scientists printed a 3D replica of the vocal tract of Nesyamun, an Egyptian priest whose mummified corpse has been on display in the UK for two centuries.
- With the help of an electronic device, the reproduced voice is able to "speak" a vowel noise.
- The team behind the "Voices of the Past" project suggest reproducing ancient voices could make museum experiences more dynamic.
Howard et al.
<p style="margin-left: 20px;">"While this approach has wide implications for heritage management/museum display, its relevance conforms exactly to the ancient Egyptians' fundamental belief that 'to speak the name of the dead is to make them live again'," they wrote in a <a href="https://www.nature.com/articles/s41598-019-56316-y#Fig3" target="_blank">paper</a> published in Nature Scientific Reports. "Given Nesyamun's stated desire to have his voice heard in the afterlife in order to live forever, the fulfilment of his beliefs through the synthesis of his vocal function allows us to make direct contact with ancient Egypt by listening to a sound from a vocal tract that has not been heard for over 3000 years, preserved through mummification and now restored through this new technique."</p>Connecting modern people with history
<p>It's not the first time scientists have "re-created" an ancient human's voice. In 2016, for example, Italian researchers used software to <a href="https://www.smithsonianmag.com/smart-news/hear-recreated-voice-otzi-iceman-180960570/" target="_blank">reconstruct the voice of Ötzi,</a> an iceman who was discovered in 1991 and is thought to have died more than 5,000 years ago. But the "Voices of the Past" project is different, the researchers note, because Nesyamun's mummified corpse is especially well preserved.</p><p style="margin-left: 20px;">"It was particularly suited, given its age and preservation [of its soft tissues], which is unusual," Howard told <em><a href="https://www.livescience.com/amp/ancient-egypt-mummy-voice-reconstructed.html" target="_blank">Live Science</a>.</em></p><p>As to whether Nesyamun's reconstructed voice will ever be able to speak complete sentences, Howard told <em><a href="https://abcnews.go.com/Weird/wireStory/ancient-voice-scientists-recreate-sound-egyptian-mummy-68482015" target="_blank">The Associated Press</a>, </em>that it's "something that is being worked on, so it will be possible one day."</p><p>John Schofield, an archaeologist at the University of York, said that reproducing voices from history can make museum experiences "more multidimensional."</p><p style="margin-left: 20px;">"There is nothing more personal than someone's voice," he told <em>The Associated Press.</em> "So we think that hearing a voice from so long ago will be an unforgettable experience, making heritage places like Karnak, Nesyamun's temple, come alive."</p>Put on a happy face? “Deep acting” associated with improved work life
New research suggests you can't fake your emotional state to improve your work life — you have to feel it.
What is deep acting?
<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDk2OS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxNTY5MzA0Nn0._s7aP25Es1CInq51pbzGrUj3GtOIRWBHZxCBFnbyXY8/img.jpg?width=1245&coordinates=333%2C-1%2C333%2C-1&height=700" id="ddf09" class="rm-shortcode" data-rm-shortcode-id="9dc42c4d6a8e372ad7b72907b46ecd3f" data-rm-shortcode-name="rebelmouse-image" data-width="1245" data-height="700" />Arlie Russell Hochschild (pictured) laid out the concept of emotional labor in her 1983 book, "The Managed Heart."
Credit: Wikimedia Commons
<p>Deep and surface acting are the principal components of emotional labor, a buzz phrase you have likely seen flitting about the Twittersphere. Today, "<a href="https://www.bbc.co.uk/bbcthree/article/5ea9f140-f722-4214-bb57-8b84f9418a7e" target="_blank">emotional labor</a>" has been adopted by groups as diverse as family counselors, academic feminists, and corporate CEOs, and each has redefined it with a patented spin. But while the phrase has splintered into a smorgasbord of pop-psychological arguments, its initial usage was more specific.</p><p>First coined by sociologist Arlie Russell Hochschild in her 1983 book, "<a href="https://www.ucpress.edu/book/9780520272941/the-managed-heart" target="_blank">The Managed Heart</a>," emotional labor describes the work we do to regulate our emotions on the job. Hochschild's go-to example is the flight attendant, who is tasked with being "nicer than natural" to enhance the customer experience. While at work, flight attendants are expected to smile and be exceedingly helpful even if they are wrestling with personal issues, the passengers are rude, and that one kid just upchucked down the center aisle. Hochschild's counterpart to the flight attendant is the bill collector, who must instead be "nastier than natural."</p><p>Such personas may serve an organization's mission or commercial interests, but if they cause emotional dissonance, they can potentially lead to high emotional costs for the employee—bringing us back to deep and surface acting.</p><p>Deep acting is the process by which people modify their emotions to match their expected role. Deep actors still encounter the negative emotions, but they devise ways to <a href="http://www.selfinjury.bctr.cornell.edu/perch/resources/what-is-emotion-regulationsinfo-brief.pdf" target="_blank">regulate those emotions</a> and return to the desired state. Flight attendants may modify their internal state by talking through harsh emotions (say, with a coworker), focusing on life's benefits (next stop Paris!), physically expressing their desired emotion (smiling and deep breaths), or recontextualizing an inauspicious situation (not the kid's fault he got sick).</p><p>Conversely, surface acting occurs when employees display ersatz emotions to match those expected by their role. These actors are the waiters who smile despite being crushed by the stress of a dinner rush. They are the CEOs who wear a confident swagger despite feelings of inauthenticity. And they are the bouncers who must maintain a steely edge despite humming show tunes in their heart of hearts.</p><p>As we'll see in the research, surface acting can degrade our mental well-being. This deterioration can be especially true of people who must contend with negative emotions or situations inside while displaying an elated mood outside. Hochschild argues such emotional labor can lead to exhaustion and self-estrangement—that is, surface actors erect a bulwark against anger, fear, and stress, but that disconnect estranges them from the emotions that allow them to connect with others and live fulfilling lives.</p>Don't fake it till you make it
<p>Most studies on emotional labor have focused on customer service for the obvious reason that such jobs prescribe emotional states—service with a smile or, if you're in the bouncing business, a scowl. But <a href="https://eller.arizona.edu/people/allison-s-gabriel" target="_blank">Allison Gabriel</a>, associate professor of management and organizations at the University of Arizona's Eller College of Management, wanted to explore how employees used emotional labor strategies in their intra-office interactions and which strategies proved most beneficial.</p><p>"What we wanted to know is whether people choose to engage in emotion regulation when interacting with their co-workers, why they choose to regulate their emotions if there is no formal rule requiring them to do so, and what benefits, if any, they get out of this effort," Gabriel said in <a href="https://www.sciencedaily.com/releases/2020/01/200117162703.htm" target="_blank">a press release</a>.</p><p>Across three studies, she and her colleagues surveyed more than 2,500 full-time employees on their emotional regulation with coworkers. The survey asked participants to agree or disagree with statements such as "I try to experience the emotions that I show to my coworkers" or "I fake a good mood when interacting with my coworkers." Other statements gauged the outcomes of such strategies—for example, "I feel emotionally drained at work." Participants were drawn from industries as varied as education, engineering, and financial services.</p><p>The results, <a href="https://psycnet.apa.org/doiLanding?doi=10.1037%2Fapl0000473" target="_blank" rel="noopener noreferrer">published in the Journal of Applied Psychology</a>, revealed four different emotional strategies. "Deep actors" engaged in high levels of deep acting; "low actors" leaned more heavily on surface acting. Meanwhile, "non-actors" engaged in negligible amounts of emotional labor, while "regulators" switched between both. The survey also revealed two drivers for such strategies: prosocial and impression management motives. The former aimed to cultivate positive relationships, the latter to present a positive front.</p><p>The researchers found deep actors were driven by prosocial motives and enjoyed advantages from their strategy of choice. These actors reported lower levels of fatigue, fewer feelings of inauthenticity, improved coworker trust, and advanced progress toward career goals. </p><p>As Gabriel told <a href="https://www.psypost.org/2021/01/new-psychology-research-suggests-deep-acting-can-reduce-fatigue-and-improve-your-work-life-59081" target="_blank" rel="noopener noreferrer">PsyPost in an interview</a>: "So, it's a win-win-win in terms of feeling good, performing well, and having positive coworker interactions."</p><p>Non-actors did not report the emotional exhaustion of their low-actor peers, but they also didn't enjoy the social gains of the deep actors. Finally, the regulators showed that the flip-flopping between surface and deep acting drained emotional reserves and strained office relationships.</p><p>"I think the 'fake it until you make it' idea suggests a survival tactic at work," Gabriel noted. "Maybe plastering on a smile to simply get out of an interaction is easier in the short run, but long term, it will undermine efforts to improve your health and the relationships you have at work. </p><p>"It all boils down to, 'Let's be nice to each other.' Not only will people feel better, but people's performance and social relationships can also improve."</p>You'll be glad ya' decided to smile
<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="88a0a6a8d1c1abfcf7b1aca8e71247c6"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/QOSgpq9EGSw?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span><p>But as with any research that relies on self-reported data, there are confounders here to untangle. Even during anonymous studies, participants may select socially acceptable answers over honest ones. They may further interpret their goal progress and coworker interactions more favorably than is accurate. And certain work conditions may not produce the same effects, such as toxic work environments or those that require employees to project negative emotions.</p><p>There also remains the question of the causal mechanism. If surface acting—or switching between surface and deep acting—is more mentally taxing than genuinely feeling an emotion, then what physiological process causes this fatigue? <a href="https://www.frontiersin.org/articles/10.3389/fnhum.2019.00151/full" target="_blank">One study published in the <em>Frontiers in Human Neuroscience</em></a><em> </em>measured hemoglobin density in participants' brains using an fNIRS while they expressed emotions facially. The researchers found no significant difference in energy consumed in the prefrontal cortex by those asked to deep act or surface act (though, this study too is limited by a lack of real-life task).<br></p><p>With that said, Gabriel's studies reinforce much of the current research on emotional labor. <a href="https://journals.sagepub.com/doi/abs/10.1177/2041386611417746" target="_blank">A 2011 meta-analysis</a> found that "discordant emotional labor states" (read: surface acting) were associated with harmful effects on well-being and performance. The analysis found no such consequences for deep acting. <a href="https://doi.apa.org/doiLanding?doi=10.1037%2Fa0022876" target="_blank" rel="noopener noreferrer">Another meta-analysis</a> found an association between surface acting and impaired well-being, job attitudes, and performance outcomes. Conversely, deep acting was associated with improved emotional performance.</p><p>So, although there's still much to learn on the emotional labor front, it seems Van Dyke's advice to a Leigh was half correct. We should put on a happy face, but it will <a href="https://bigthink.com/design-for-good/everything-you-should-know-about-happiness-in-one-infographic" target="_self">only help if we can feel it</a>.</p>World's oldest work of art found in a hidden Indonesian valley
Archaeologists discover a cave painting of a wild pig that is now the world's oldest dated work of representational art.
Pig painting at Leang Tedongnge in Indonesia, made at 45,500 years ago.
- Archaeologists find a cave painting of a wild pig that is at least 45,500 years old.
- The painting is the earliest known work of representational art.
- The discovery was made in a remote valley on the Indonesian island of Sulawesi.
Oldest Cave Art Found in Sulawesi
<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="a9734e306f0914bfdcbe79a1e317a7f0"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/b-wAYtBxn7E?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>What can Avicenna teach us about the mind-body problem?
The Persian polymath and philosopher of the Islamic Golden Age teaches us about self-awareness.
