Why can't we get it right? The challenges and limits of "Responsible" AI

How can technology be designed to exploit its usefulness without exploiting its users? 

Over the years arguments about technology have moved from concerns about data and privacy, to bias and discrimination in algorithmic systems, to ethical concerns about large language models. The current solution seems to be "Responsible AI" - a set of tools, methods, checklists, standards, compliance evaluations, and ways of thinking.

You will learn how AI systems continue to fail, plagued by problems of bias, privacy concerns, and overhyped promises that consistently fall short. Why do problematic AI systems seem unavoidable and what does it take to create AI responsibly? We will focus on the problems of data quality, when and how technical challenges become ethical concerns, and the limits of "being ethical" when developing AI.

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