What AI can teach us about human bias in decision making

An ensemble of algorithms working together will produce far more accurate predictions than one working alone. In other words, the collective power of the weak is mightier than that of the strongest individual.

The debate between meritocracy and affirmative action has long simmered, and the arguments on both sides are familiar. But quickly to recap, let’s look at an exchange between two people, each on either side of the argument.

Vivek Ramaswamy is a self-made multimillionaire who founded a biotech company at the age of 28. He is a celebrity in conservative circles, having been a regular guest on Fox News and last year published Woke, Inc: Inside the Social Justice Scam, which takes corporations to task for — as he sees it — overstepping the mark in becoming involved in moral issues best left to society.

Recently, he recalled a debate with Kenneth Frazier, the former chief executive of the pharmaceuticals company Merck. Frazier had said in the wake of the police killing of African-American George Floyd: “There are, in fact, barriers that are faced by African Americans … We still have customs. We still have beliefs. We still have policies. We have practices that lead to inequity.” Therefore, he argued, “Businesses have to use every instrument at their disposal to reduce these barriers that existed [sic].” In short, he believed that companies needed to actively tilt the balance in favor of the disadvantaged.  

Yet Ramaswamy was skeptical. For him, racial diversity was just another fashionable social cause, such as (as he saw it) gender or climate change. Companies embraced these causes because they were on trend, he asserted. A pharmaceutical company should focus instead on serving patients first, and that means, Ramaswamy wrote: “We don’t care if the scientist who discovers a cure to COVID-19 is white or black, or a man or a woman.”

If only things were that simple. We are all human. We have limited knowledge. We may understand others well if they have had similar life experiences to ours. Human psychology tricks us, too. It makes us want to be around people who are like us — people with whom we can sympathize. That is all very innocent until you consider the cost to society.

The long history of gender bias in medicine

Take medicine. Men and women have different ways of reacting to illness. Hippocrates noted this over 2,000 years ago. Women with heart disease, for instance, often experience different symptoms than men with the same disease. Women might feel pain in the abdomen rather than the left arm.

Despite these distinctions, many modern-day clinical studies are stubbornly influenced by gender bias. Although we know that women’s bodies metabolize medicines differently, only 41.9% of participants in cardiovascular research are female. A shocking fact is that 51% of cancer patients are women, whereas only 41% of cancer trial participants are women.[…]

An ensemble of algorithms working together will produce far more accurate predictions than one working alone. In other words, the collective power of the weak is mightier than that of the strongest individual.

The long history of gender bias in medicine

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