Join Kate Crawford, Distinguished Research Professor at New York University, a Principal Researcher at Microsoft Research New York, and a Visiting Professor at the MIT Media Lab, to debate the biases built into machine learning, and what that means for inequality.
Advances in artificial intelligence (AI) mean that computer systems can now give highly accurate predictions or recommendations, drawing insights from data in ways that were not previously possible and supporting new products or services. In some cases, AI is supporting decision-making situations that have a significant personal or social impact; whether it be informing judicial decisions in sentencing or parole, advising organisations about who to hire (or fire), or contributing to decisions about access to public services. Recent years have revealed a number of examples of the difficulties ensuring AI systems work well for everyone, and the subject of bias in AI is a growing area of interest for researchers and policymakers. But what can be done about it?
In the fourth discussion of the You and AI series, Kate Crawford will explore how experts and researchers are confronting questions about bias, and formulating crucial strategies that might help overcome it.
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