How we can build AI to help humans, not hurt us | Margaret Mitchell

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4.1 • 11.9K Ratings

🗓️ 20 February 2018

⏱️ 10 minutes

🔗️ Recording | iTunes | RSS

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Summary

As a research scientist at Google, Margaret Mitchell helps develop computers that can communicate about what they see and understand. She tells a cautionary tale about the gaps, blind spots and biases we subconsciously encode into AI -- and asks us to consider what the technology we create today will mean for tomorrow. "All that we see now is a snapshot in the evolution of artificial intelligence," Mitchell says. "If we want AI to evolve in a way that helps humans, then we need to define the goals and strategies that enable that path now."

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Transcript

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0:00.0	This TED Talk features AI research scientist Margaret Mitchell, recorded live at TED at BCG 2017.
0:10.0	I work on helping computers communicate about the world around us. There are a lot of ways to do this,
0:16.9	and I like to focus on helping computers to talk about what they see and understand.
0:22.6	Given a scene like this,
0:24.6	a modern computer vision algorithm can tell you that there's a woman and there's a dog.
0:29.6	It can tell you that the woman is smiling.
0:31.6	It might even be able to tell you that the dog is incredibly cute.
0:35.6	I work on this problem thinking about how humans understand and process the world.
0:42.6	The thoughts, memories, and stories that is seen like this might evoke for humans,
0:48.6	all the interconnections of related situations.
0:53.1	Maybe you've seen a dog like this one before, or you've
0:56.8	spent time running on a beach like this one, and that further evokes thoughts and memories of a
1:02.7	past vacation, past times to the beach, time spent running around with other dogs. One of my guiding
1:09.8	principles is that by helping computers to understand
1:13.6	what it's like to have these experiences,
1:17.2	to understand what we share and believe and feel,
1:23.3	then we're in a great position to start evolving computer technology
1:27.6	in a way that's complementary with our own experiences.
1:33.0	So, digging more deeply into this,
1:36.3	a few years ago, I began working on helping computers
1:40.0	to generate human-like stories from sequences of images.
1:44.6	So one day, I was working with my computer to ask it what it thought about a trip to Australia.
	...

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