Building a better society with better AI

"As humans, we are highly biased," says Beena Ammanath, the global head of the Deloitte AI Institute, and tech and AI ethics lead at Deloitte. "And as these biases get baked into the systems, there is very high likelihood of sections of society being left behind--underrepresented minorities, people who don't have access to certain tools--and it can drive more inequity in the world." Projects that begin with good intentions -- to create equal outcomes or mitigate past inequities -- can still end up biased if systems are trained with biased data or researchers aren't accounting for how their own perspectives affect lines of research. Thus far, adjusting for AI biases has often been reactive with the discovery of biased algorithms or underrepresented demographics emerging after the fact, says Ammanath. But, companies now have to learn how to be proactive, to mitigate these issues early on, and to take accountability for missteps in their AI endeavors.