The push to deliver unbiased and responsible artificial intelligence is admirable, but there are many roadblocks to overcome. Chiefly, AI is only as fair as the data that goes into it. In light of the slow progress addressing AI bias and unfairness, business and technology leaders may be finally arriving at a consensus that they need to concentrate on more "responsible" approaches to AI. A recent survey of 504 IT executives, released by Appen and conducted by The Harris Poll, finds heightened concern about the data that is increasingly driving decisions about customers, markets, and opportunities. It also hints at recognition by both types of leaders that the data they have tends to be problematic, wreaking damage to people, communities, and businesses.

Software engineer Henry Gan got a surprise last summer when he tested his team's new facial recognition system on coworkers at startup Gfycat. The machine-learning software successfully identified most of his colleagues, but the system stumbled with one group. "It got some of our Asian employees mixed up," says Gan, who is Asian. "Which was strange because it got everyone else correctly." Gan could take solace from the fact that similar problems have tripped up much larger companies.