In AI, Diversity Is A Business Imperative
Organizations today recognize the critical importance of diversity. They address it by changing internal practices and establishing chief diversity officers to enable equal opportunities and to strive for greater inclusion so that teams with a wealth of cultures, beliefs, experiences and skills can make their companies even stronger.
The realization that diverse teams achieve better outcomes than homogenous ones was further reinforced by a McKinsey study that found that the most ethnically and racially diverse companies had a better chance of outperforming their peers. Those companies had a 33% great probability of achieving above-average returns. Whether it’s pricing stocks or determining guilt or innocence in a trial, a diverse group is more likely to examine the facts and be objective and accurate.
In actuality, the artificial intelligence (AI) ecosystem is no different than the real world – diversity is the springboard to well-functioning algorithms.
Take for example the million-dollar Netflix challenge, in which a team of diverse individuals from different professions around the world developed more accurate algorithms for predicting how consumers rated movies than the ones Netflix had developed internally. They were successful because diverse individuals brought different ideas and ways of thinking.
This diversity is critical in solving complex problems. People (specifically data scientists) create the algorithms that help AI programs learn. If data scientists represent only one group, one way of thinking and one way to categorize, model and process information, then they are not only more likely to have a limited viewpoint, but they also are more likely to create errors. Importantly, they are also more likely to bring unintended biases into the algorithms that train the AI apps.
Coding In Biases
As more organizations rely on algorithms to help with decision making, we have a responsibility to ensure that we are not programming bias into our AI systems. A recent report found pervasive biases in the AI industry, which is predominately comprised of white males. A major concern is that the bias that has crept into so many of our policies and practices in hiring, education and mortgage lending, to name a few, are being programmed into AI apps. To help shed light on biases in AI systems and promote practices to help address this concern, The Algorithmic Justice League was formed by Joy Buolamwini. (read more)