57. Dylan Hadfield-Menell - Humans in the loop
Towards Data Science - A podcast by The TDS team
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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.