As Congress barrels toward an election that could see at least one house change hands, efforts to squeeze big bills into law are mounting. The one with the best chance (and better than I expected) would drop $52 billion in cash and a boatload of tax breaks on the semiconductor industry. Michael Ellis points

Algorithms are at the heart of the Big Data/machine learning/AI changes that are propelling computerized decision-making. In their book, The Ethical Algorithm, Michael Kearns and Aaron Roth, two Computer Science professors at Penn, flag some of the social and ethical choices these changes are forcing upon us. My interview with them touches on many of the hot-button issues surrounding algorithmic decision-making. I disclose my views early: I suspect that much of the fuss over bias in machine learning is a way of smuggling racial and gender quotas and other academic social values into the algorithmic outputs. Michael and Aaron may not agree with that formulation, but the conversation provides a framework for testing it – and leaves me more skeptical about “bias hacking” of algorithmic outputs.

Continue Reading Episode 291: Ethical Algorithms with Michael Kearns and Aaron Roth