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57. Dylan Hadfield-Menell - Humans in the loop

57. Dylan Hadfield-Menell - Humans in the loop

FromTowards Data Science


57. Dylan Hadfield-Menell - Humans in the loop

FromTowards Data Science

ratings:
Length:
65 minutes
Released:
Nov 11, 2020
Format:
Podcast episode

Description

Human beings are collaborating with artificial intelligences on an increasing number of high-stakes tasks. I’m not just talking about robot-assisted surgery or self-driving cars here — every day, social media apps recommend content to us that quite literally shapes our worldviews and our cultures. And very few of us even have a basic idea of how these all-important recommendations are generated.
As time goes on, we’re likely going to become increasingly dependent on our machines, outsourcing more and more of our thinking to them. If we aren’t thoughtful about the way we do this, we risk creating a world that doesn’t reflect our current values or objectives. That’s why the domain of human/AI collaboration and interaction is so important — and it’s the reason I wanted to speak to Berkeley AI researcher Dylan Hadfield-Menell for this episode of the Towards Data Science podcast. Dylan’s  work is focused on designing algorithms that could allow humans and robots to collaborate more constructively, and he’s one of a small but growing cohort of AI researchers focused on the area of AI ethics and AI alignment.
Released:
Nov 11, 2020
Format:
Podcast episode

Titles in the series (100)

Researchers and business leaders at the forefront of the field unpack the most pressing questions around data science and AI.