BiGS Actionable intelligence: CEOs, marketing chiefs, product designers and others risk leaving money on the table if they don’t take time to understand AI’s history, weaknesses, and risks for today’s diverse marketplace, a Harvard Business School fellow explains.

BOSTON – April 13, 2023 – During his recent standing-room-only seminar about artificial intelligence (AI) and race at Harvard Business School recently, marketing professor Broderick Turner displayed a slide showing several white blob-like characters that resembled the tubby mascot of French tire giant Michelin. He asked people in the room if they could figure out what he’d asked DALL-E2, the advanced AI system with a mission of creating AI that benefits humanity.

People in the audience were stumped. No one could guess. After about 40 seconds, Turner – a visiting fellow at HBS’s Institute for the Study of Business in Global Society (BiGS) who is Black – gave us the answer. “White men,” he declared. Huh?

It turns out that the people who created the internet, primarily White men, didn’t classify or tag themselves as anything. This means that when you ask the AI system – which uses information up to the year 2020 – to show an image of a white man, the only image it finds is a blobby character with male eyes with white as its color.

It was just one of the many moments that had the audience of PhDs gripped, waiting for more. And so much so that BiGS is now planning a conference where Turner and his lab mates will present more research that examines the intersection of race and AI.

The BiGS Fix stopped to chat with Turner about his evidence-based research, race and racism in the marketplace, and more. Turner founded and runs the Technology Race and Prejudice Lab.

Our conversation has been edited for length.

Q. Why do you research race and technology?

A. As a Black person, I don’t want to go to the past. The past is pretty bad. The present is better than 100 years ago and much better than 200 years ago.

Today, the tech world is building AI systems and making decisions that will use human inferences and data built on the past. So instead of mimicking the present and going forward, it could create a system that starts to look more like the past if I make automatic decisions that are all based on inferences of the past.

For consumers and the world, we have this opportunity right now to avoid using data from the past. We can create systems, so the future doesn’t replicate the past but creates a better future for all of us.

Q. When it comes to race, technology, and tomorrow’s business outcomes, what advice would you give to CEOs, CMOs and other top decision makers?

A. I advise them that if marginalized people and women weren’t involved in the past’s decision-making process, then you’re missing a huge understanding of your market and the way the world works. You’re leaving money on the table! You’re not going to make as much money as you could by not considering the experience of racialized Others.

Think about the tech space. I know there is a version of an automatic water faucet that doesn’t recognize my hands because I have melanin in my skin, but the company didn’t have people with my level of melanin or darker in the training so that product doesn’t work well for me, or folks who look like me. If I decide to market this product in Kenya, Ghana, Nigeria, or even parts of India, Bangladesh, and Pakistan, it’s not going to work. It’s also a problem if you build systems where nobody who has lived the experience is in the room. You can end up looking at the data and not understanding what the data means and, ultimately, not make good decisions.

Q. What’s the purpose of the T.R.A.P. Lab?

A. I consider it both a think tank and a time saver for people doing rigorous research on race and technology. It's an environment where social scientists working on these matters don’t have to defend why this stuff is important, which saves us a lot of time. A group of us share research on the intersection of race and capitalism –specifically, on race and technology since we live in the age of the digital transition and race is inherently embedded in algorithms and code simply because of who created the Internet more than 30 years ago (Maybe it was Al Gore?). Today we have nearly 20 people doing this type of research. It’s a safe place, people feel comfortable sharing what they’re doing, and we don’t have to spend time explaining what algorithms are or why race is organically part of the technology conversation.

Q. Politics aside, what myths or uninformed questions do you hear from business leaders of mainstream companies?

A. Over the years, I’ve heard plenty. They fall in three categories: expense, denial, and blame.

First, the expense myth comes up most often with people claiming that “diversity is expensive” and that “addressing diversity is going to cost me money.” Expense is a convenient boogeyman.

Secondly, the old denial case is still around. Even today, I hear people say, “I don’t see color.” That’s fine. Race is not real, but the effects of racism are. Our research on schools, for instance, finds that even if parents do not consider race when making school choices, they may still end up in racially segregated schools because racism has created a different motivation structure. Black parents, more than White parents, seek the highest-rated schools and are willing to travel further to get this access.

Third is the blame myth. When you show there are differences in outcomes among races, you can either believe there’s something that’s wrong with one of the groups – and that’s where a lot of people go, instead of seeing the data from an unbiased, data-driven lens. Think about the racial wealth gap. One explanation is that Black people are worse at creating wealth, but today we know the stories about the systematic bias ingrained in even how home inspectors often assign a lower value to a family’s home with Black family photos and décor vs. items showing White people.

In some ways, it’s easy to understand. People are people, so when you talk to companies that are run by people, sometimes the easiest explanation for racial inequality is that something is wrong or that White people are special. So, it’s easy to say that’s just how it’s supposed to be.

Q. You say your T.R.A.P. Lab’s research can help interpret data that often goes overlooked and can help a company increase their bottom line. What does that mean and how do you do it?

A. If you’re at a company, our research can show you why you might see Black consumers spend less or Asian consumers spend more. We ask “why?” We think about race and racism as part of a larger system that impacts consumer behavior, so we help you figure out what happens here. Why does this product or service not get adopted? What do people think about these things? Ultimately, our work will speak to this. Companies shouldn’t be making these same mistakes today -- there’s no need. No one should be surprised when you put out products – like an automatic, sensor-driven sink faucet – and people want you to pull it from the shelves.

Q. How did you wind up becoming a PhD doing a fellowship at Harvard Business School?

A. I can tell you it wasn’t my plan at all. I’m just a very lucky person and I surround myself with great people. Ten or so years ago, my wife and I started a company to try to combine a string of beauty schools. We did a leveraged buyout (LBO), raising over $10 million but the deal didn’t work out. My wife gave me a challenge: You can do anything you want in life, and you have 60 days to figure out whatever you’re going to do next. I sought feedback, so I reached out to people over age 60 in a range of professions – sales executives, entrepreneurs, principals, and others.

I discovered that business school professors over 60, unlike everybody else, were excited to go to work and looking forward to Monday and they were still on their first marriage. I love my wife, so that sealed the deal for me! After working with Dr. Jonathan Hasford at Florida International University and my mentor Dr. Tiffany Barnett-White at University of Illinois and the PhD Project to figure out where I should go to graduate school, I got into Northwestern University's Kellogg School of Management. I got really lucky at Kellogg and worked with phenomenal people there, including doctors Neal Roese, Angela Lee, Galen Bodenhasuen and Eugene Caruso. Next thing I know, I published some cool research. Got hired at Virginia Tech, and my friend Dr. Mike Norton at HBS told me I should apply for this fellowship…and ta da. Magic.

Q. So, I just had to ask: Is there a story behind calling your lab the T.R.A.P. Lab?

A. Well, as a matter of fact there is. It stands for "the race and prejudice lab," and t-r-a-p is the best genre of hip hop music that comes from Atlanta, where I’m from.

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