Originally published December 7, 2017
Here is an excerpt:
Others in Long Beach hope to make the people building AI better reflect humanity. Like computer science as a whole, machine learning skews towards the white, male, and western. A parallel technical conference called Women in Machine Learning has run alongside NIPS for a decade. This Friday sees the first Black in AI workshop, intended to create a dedicated space for people of color in the field to present their work.
Hanna Wallach, co-chair of NIPS, cofounder of Women in Machine Learning, and a researcher at Microsoft, says those diversity efforts both help individuals, and make AI technology better. “If you have a diversity of perspectives and background you might be more likely to check for bias against different groups,” she says—meaning code that calls black people gorillas would be likely to reach the public. Wallach also points to behavioral research showing that diverse teams consider a broader range of ideas when solving problems.
Ultimately, AI researchers alone can’t and shouldn’t decide how society puts their ideas to use. “A lot of decisions about the future of this field cannot be made in the disciplines in which it began,” says Terah Lyons, executive director of Partnership on AI, a nonprofit launched last year by tech companies to mull the societal impacts of AI. (The organization held a board meeting on the sidelines of NIPS this week.) She says companies, civic-society groups, citizens, and governments all need to engage with the issue.
The article is here.