The Matter of Bias

It was April 12th, 2018. Two black men walked into a Starbucks outlet in Philadelphia for a business meeting.  Not long after three police officers arrived to arrest the duo. Their crime? Sitting in the coffee shop without ordering any item and asking to use the restroom. The manager, quoting store policy, refused to allow them to use the restroom since they were non-paying customers and asked them to leave. When the two men refused to leave, the manager called the police. 

This incident led to a huge outcry amid calls to boycott Starbucks as well as protests at the Philadelphia Starbucks where the men were arrested. Executive Chairman of Starbucks Howard Schultz stated that the store manager was acting on her “unconscious bias,” and the company apologized to the men. 

Starbucks  moved quickly to handle the fallout from the incident and closed more than 8,000 of its U.S. stores on May 29, 2018. The coffee chain went on to conduct racial bias and diversity training for its 175,000 employees “to ensure everyone inside a Starbucks store feels safe and welcome”. 

Bias at the workplace

Biases can hurt interactions with customers, impact the hiring process adversely, and thwart efforts at building a diverse workforce. Earlier this year in March, JobBuzz, an employer rating and review platform by TimesJobs, surveyed 1,940 employees to understand the shades of bias and diversity at  Indian workplaces. The survey found that about 33 percent of Indian employees face or have faced age-based bias at their workplace. This was followed by 17 percent who faced bias because of their physical appearance and 15 percent of others had faced bias on the basis of their religion or culture. Gender-based bias was claimed by 14 percent of the survey responders. The JobBuzz survey asked employees of any if their C-suite leaders was LGBTQ or specially-abled and 76% of the respondents replied in the negative. This indicates that these professionals are still not well-represented at boardrooms.

Even in these pandemic times, there is a talk of a bias in COVID-19 layoffs. According to the Pew Research Center, more women than men lost their jobs from February to May 2020—11.5 million vs. 9.0 million.

Research suggests that judging others is our natural instinct. We categorize people and things using easily observed criteria such as skin colour, gender, age and weight. We also pigeonhole people according to disability, sexuality, accent, social status, job title and educational level.  We tend to put people with similar traits in the same category, thus stereotyping them.  Stereotyping is harmful, causing people to have biases against those who are different from them. 

How does bias affect people? 

Whatever shape bias takes, it diminishes productivity and engagement. Bias can impact morale, motivation, commitment, and desire to advance in the organisation.

It has been found that working under managers with a high degree of unconscious bias causes employees to underperform and never go out of their way to excel at work. People tend to feel isolated and alienated, which can increase absenteeism in the workplace.

How are organizations attempting to keep bias at bay? 

Instead of recruiting from a limited talent pool, from a small set of  universities as they had been doing over several years, companies such as Unilever are attempting to remove bias during hiring by encouraging candidates to submit their LinkedIn profile instead. This allows the multinational consumer goods company to hire promising candidates from a large, diverse talent pool – unhindered by the university the candidate attended. After this, candidates are required to play a series of short games on recruitment platforms, which use behavioral science and AI technology to assess a  job seeker’s true potential. Once this is cleared, the candidate is invited to complete a video interview using an AI-enhanced video platform that has the capability of assessing different traits of the candidate, including word choice, voice inflection, eye movement and facial cues, among many others.

As a result of the Black Lives Matter movement that recently took the world by storm, following the death of George Floyd in the US, companies like Twitter are reexamining how technical terms are used. Racially charged terms like “master/slave” are being replaced by neutral terms like “primary/secondary”. Similarly, some companies have stopped using the terms “blacklist” and “whitelist” and are instead using  “block list” and “allow list”.  

In June this year, multinational giant Hindustan Unilever Limited announced that it would rebrand its bestselling skin-lightening cream, Fair & Lovely to “Glow & Lovely”. It removed the words “light/lightening”, “fair/fairness” and “white/whitening” from its brand packaging, and featured women of all skin tones in future advertising campaigns. In a country where the fair skin obsession runs deep, this is a tiny but significant step to embracing all shades of skin colour. 

This month, the Oscars raised their inclusion standardsto encourage equitable representation on and off screen in order to better reflect the diversity of the movie-going audience.” The eligibility reforms address race, gender, sexual orientation,  disability and ethnicity.  

Technology to the rescue for reducing bias

It is a known fact that unconscious bias against older workers, minorities and women is common and makes hiring unfair. This leads to large pools of applicants being ignored and a lack of diversity at the workplace.  Companies today are capitalizing on artificial intelligence to address the concern of any kind of bias by using AI-based algorithms to conceal the gender, name and other details of a candidate at the screening stage. This allows recruiters to assess the candidate purely on merit. Even with regard to performance management, AI-assisted performance management processes can highlight any bias in assigning ratings and compensation for individuals. 

However, a point to note is that human biases do creep into AI systems. An AI system is able to make predictions and identify patterns based on data that it “learns” from. If this data itself is biased, then the AI system’s decisions and predictions will also be prejudiced.  We just need to be aware of these risks and work to reduce them.

For companies to have visibility into the data around the actual work performance of employees, workforce analytics help. Such analytics enable businesses to make unbiased workforce and data-driven decisions to kindle  a progressive workplace and an inclusive culture. 

However, we need to keep in mind that even with access to the best technology in the world, human judgment will remain important. In the end, it is all about building more inclusive societies and creating a world where everyone is accepted without exception. As Michelle Obama says in her book Becoming

“Let’s invite one another in. Maybe then we can begin to fear less, to make fewer wrong assumptions, to let go of the biases and stereotypes that unnecessarily divide us. Maybe we can better embrace the ways we are the same. It’s not about being perfect. It’s not about where you get yourself in the end. There’s power in allowing yourself to be known and heard, in owning your unique story, in using your authentic voice.”

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