Ken Goldberg in 5 Takeaways from TechCrunch Disrupt
Coming in near the top as #2 of the shortlist, "Bias in AI is a new face on an old problem" was emphasized TechCrunch as an important lesson to draw from its Disrupt SF Conference.
Ken Goldberg, BCMN faculty, took part in a panel that discussed how even data used to train AI systems are subject to the same biases of humans. If left unmonitored, AI can be used as an oppressive tool to perpetuate existing systemtic inequalities.
From the article:
A potential solution to prevent the spread of toxic algorithms was outlined by UC Berkeley’s Ken Goldberg who cited the concept of ensemble theory, which involves multiple algorithms with various classifiers working together to produce a single result.
But how do we know if the solution to inadequate tech is more tech? Goldberg says this is where having individuals from multiple backgrounds, both in and outside the world of AI, is vital to developing just algorithms. “It’s very relevant to think about both machine intelligence and human intelligence,” explained Goldberg. “Having people with different viewpoints is extremely valuable and I think that’s starting to be recognized by people in business… it’s not because of PR, it’s actually because it will give you better decisions if you get people with different cognitive, diverse viewpoints.”
Read the rest of the TechCrunch recap here.