Open||Source||Data Deep Fakes, Responsible Data Science, and Trust with David Danks
This episode features an interview with David Danks, Professor of Data Science and Philosophy and affiliate faculty in Computer Science and Engineering at University of California, San Diego. Prior to UCSD, David was the L.L. Thurstone Professor of Philosophy and Psychology at Carnegie Mellon University.
David’s research interests are at the intersection of philosophy, cognitive science, and machine learning. He has also examined the ethics surrounding artificial intelligence in the fields of healthcare, privacy, and security.
In this episode, David and Sam dive into responsible data science, deep fakes, and if data is to blame for the lack of trust among consumers.
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"There's a, almost, glorification of the technology that's happening at the moment. And the technology is obviously crucial, but what I really care about in a lot of ways is what are the human beings who build and use that technology doing with it? Because the exact same ones and zeros, the exact same code can lead to enormous social benefit or social harm, depending on what we humans do with it. And so, I think we need to recognize that technology is not this hurricane bearing down on us, it's a thing that people build and use. And how do we influence the people, and the companies is maybe an easier thing to do than trying to focus just on the data and algorithms." – David Danks
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Episode Timestamps:
(01:41): What open source data means to David
(05:58): David’s transition from philosophy to AI
(09:03): Is data to blame for lack of trust in AI?
(13:40): How to be “future aware”
(16:32): Data science vs responsible data science
(20:20): Deep Fakes
(40:17): Advice for Ethical AI newcomers
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