The effort to make our workplaces and institutions more diverse is typically framed as a moral issue or an opportunity to make society more just. Given the many aspects of our society that advantage certain groups of people and disadvantage others, this is a worthwhile pursuit 鈥 and a fair way of framing the challenge. But what if it wasn鈥檛 the only way of establishing a value proposition for diversity and inclusion? For years, Scott Page, the John Seely Brown distinguished university professor of complexity, social science and management at UM-Ann Arbor, has been making a numbers case for diversity. His basic thesis: If you want innovation, or to solve complex 21st-century problems like income inequality or climate change, then groups of experts, at least as we鈥檙e accustomed to thinking about them, are going to have a hard time competing with talented teams of people with relevant diverse perspectives.
Page recently laid out his argument in an entertaining lecture in UM-Dearborn鈥檚 Thought Leaders series, which brings experts to campus to talk about big ideas relating to our strategic plan priorities. A key point in Page鈥檚 case is distinguishing between simple and complex tasks. For example, he says if you鈥檙e looking to maximize output for your logging business in northern Michigan in the 1820s, then a straightforward measure of how many trees a person can cut down in a day may be a good hiring metric. By assembling a team of the most productive loggers and aggregating their effort, you reap the most profit 鈥 simple as that. But Page says group dynamics work differently for more complex tasks. For example, say you want to make forecasts about the economy, and you ask 40 really good economists to make predictions and then average them. (This, by the way, is a common method for producing economic forecasts in the U.S. and European Union.) Page says when you crunch the numbers, a couple interesting phenomena emerge. One, the group鈥檚 average prediction is better than any of the predictions of the individual economists. Even more interesting, the group鈥檚 prediction actually has less error than the average error of the individual members, and the size of the extra benefit from this group average actually corresponds to how different their predictions were. In other words, diversity yields a 鈥渂onus.鈥
So why is this the case? 鈥淥nce you have something that鈥檚 really high-dimensional, by definition, people are going to go about it in different ways, and when they go about it in different ways, you get this benefit,鈥 Page said. Stated a little differently, when something is very complex, it鈥檚 hard to figure out, which means no one is going to get it exactly right. So 鈥測ou want people getting it wrong in different ways鈥 so you鈥檙e accounting for a greater degree of the complexity. Needless to say, this is a different approach than many institutions take to solving problems. Typically, Page says, our inclination is to assemble a team of the best experts on a particular topic, as measured by an accepted set of credentials. But in doing so, we鈥檙e missing an opportunity to reap a diversity bonus. 鈥淔or example, when I go to the New York Fed, they鈥檒l have 60 people with PhDs in economics and no sociologists and no psychologists,鈥 Page said. 鈥淭hey鈥檙e all trained to see the world in the same way, through the exact same categories, the exact same models.鈥 Page is quick to point out, however, that diversity doesn鈥檛 mean random difference. If you鈥檙e trying to solve a complex physics problem, the solution isn鈥檛 to 鈥渂ring Tony Hawk in to CERN.鈥 The people on your team have to have knowledge or skills that are germane to the task. But if you鈥檙e trying to come up with policy solutions to, say, income inequality or inflation, it鈥檚 going to help to have economists working alongside sociologists or psychologists, because they鈥檒l all approach the problem a little differently and the group鈥檚 solution will capture more complexity.
In addition, Page says we shouldn鈥檛 assume that traditional metrics, like what academic discipline a person got their doctorate in, are the only ways to measure or predict this advantageous 鈥渃ognitive diversity鈥 of the group. The amalgam of someone's life experiences is also very important in what they bring to the table, which is why diversity of identity can also matter. People of different races, genders, social classes, national origins, etc. will inherently have had different life experiences, which inform how they see the world and thus their approach to problems. When this kind of identity diversity contributes to more cognitive diversity, Page says it can boost diversity bonuses.
Page also notes that environmental conditions must be favorable to maximize this benefit you get from diverse teams. Most importantly, institutions have to create environments where people feel trusted and validated, so there鈥檚 no holding back when they鈥檙e working as a group. Under these conditions, Page says you can often reap even more benefits through 鈥渟ynergy鈥 鈥 moments when ideas combine in unexpected ways to create especially great solutions. Viewed this way, creating an inclusive environment where everyone has a seat at the table becomes an 鈥渁mazing opportunity鈥 to create solutions for today鈥檚 complex problems 鈥 in addition to being the right thing to do.
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Want to learn more about Scott Page鈥檚 work on diversity and innovation? Check out his book "." Also, look out for the next installment in our Thought Leaders series on Nov 10 : 鈥淗ow Technology Developers and Social Scientists Can Work Together to Combat Bias in the Metaverse鈥 with the University of Pennsylvania鈥檚 Desmond Patton. .
