This episode features a lively (and – fair warning – long) interview with Daphne Keller, Director of the Program on Platform Regulation at Stanford University’s Cyber Policy Center. We explore themes from her recent paper on regulation of online speech. It turns out that more or less everyone has an ability to restrict users’ speech online, and pretty much no one has both authority and an interest in fostering free-speech values. The ironies abound: Conservatives may be discriminated against, but so are Black Lives Matter activists. In fact, it looks to me as though any group that doesn’t think it’s the victim of biased content moderation would be well advised to scream as loudly about censorship or the others for fear of losing the victimization sweepstakes. Feeling a little like a carny at the sideshow, I serve up one solution for biased moderation after another, and Daphne methodically shoots them down. Transparency? None of the companies is willing, and the government may have a constitutional problem forcing them to disclose how they make their moderation decisions. Competition law? A long haul, and besides, most users like a moderated Internet experience. Regulation? Only if we take the First Amendment back to the heyday of broadcast regulation. As a particularly egregious example of foreign governments and platforms ganging up to censor Americans, we touch on the CJEU’s insufferable decision encouraging the export of European defamation law to the US – with an extra margin of censorship to keep the platform from any risk of liability. I offer to risk my Facebook account to see if that’s already happening.


Continue Reading Episode 302: Will the First Amendment Kill Free Speech in America?

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

We open the episode with David Kris’s thoughts on the two-years-late CFIUS investigation of TikTok, its Chinese owner, ByteDance, and ByteDance’s US acquisition of the lip-syncing company Musical.ly. Our best guess is that this unprecedented reach-back investigation will end in a more or less precedented mitigation agreement.


Continue Reading Episode 285: ByteDance bitten by CFIUS