It’s clear that Artificial Intelligence is here to stay. Most agree it is already influencing our lives and that influence is growing rapidly. But is most of the conversation about AI missing something big?
AIs are learning every day to anticipate needs, complete tasks, analyze data, and make decisions for us, but…what exactly are they learning? They are still input/output based, whether that input is human developers or machine learning from the mostly human-generated Internet. What data are they using to make decisions about humans? We know our own human systems and interactions can be fraught with biases. How do we keep those same biases from being replicated in AIs when we can’t seem to eliminate them from human society?
If the goal is for AIs to inform or make better, quicker decisions for us, we have to make sure those decisions are as free as possible from the biases that create inequity and injustice. When we take conscious action to build inclusion into the ways that AIs are programmed and how they learn, we help ensure we’re meeting that goal in the best way possible. Building inclusion into AI isn’t simply additive—ameliorating biases in systems improves results exponentially, helping to not only make the technology as effective as possible, but to change and enhance our human journey.