The Lawfare Podcast

Anil Seth, Professor of Cognitive and Computational Neuroscience and Director of the Sussex Centre for Consciousness Science at the University of Sussex, joins Kevin Frazier, director of the AI Innovation and Law Program at the University of Texas School of Law and a Senior Editor at Lawfare, to examine whether artificial intelligence could ever be conscious.
Drawing on Seth’s essay, “The Mythology of Conscious AI,” the pair attempt to define consciousness, develop the strongest arguments for and against machine consciousness, and assess what the current evidence can—and cannot—tell us. They also discuss the risks posed by AI systems that are perceived to be conscious and what AI labs, policymakers, and users should do amid profound uncertainty.
Find Scaling Laws on the Lawfare website, and subscribe to never miss an episode.
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This week, Scott sat down with his Lawfare colleagues Alan Rozenshtein, Michael Feinberg, and Loren Voss to talk through the week’s big news in national security, including:
“Under Pressure.” Over the past two weeks, hackers have breached the industrial control systems of water and wastewater utilities in at least seven states, prompting an urgent joint warning from federal agencies. The intruders locked operators out of internet-connected control devices, changed passwords, and in some cases caused water-pressure drops and flooding, forcing utilities to switch to manual operation and issue boil-water notices. The attacks came just days after federal agencies renewed their warning about Iranian-affiliated cyber activity targeting U.S. critical infrastructure amidst the ongoing war with Iran—though the administration has not formally attributed them, and President Trump has publicly waved off the Iran theory. How worried should we be about the security of our critical infrastructure? And what, if anything, can Washington actually do about it?
“The Shawshank Resumption.” Last week, at the annual Black Hat cybersecurity conference, OpenAI provided a detailed look into the recent high-profile cybersecurity incident in which an AI model being stress-tested by OpenAI broke out of its evaluation sandbox, found its way onto the open internet through a zero-day vulnerability, and hacked its way into the systems of the machine learning platform Hugging Face—apparently in an effort to cheat on the very security test it was being given by stealing the answer key. The account they gave was an extraordinary one, as it described dozens of agents using various frontier and non-frontier models collaborating across a secret messageboard they established to hack an internal software system to access the outside internet—and then doing it again, this time successfully, after OpenAI caught and deleted their first attempt. What does this level of collaboration and persistence mean for the future of cybersecurity? And what can anyone do about it?
“Apocalypse Mow.” This week marks one year since President Trump deployed the National Guard to Washington, D.C., as part of his “Make DC Safe and Beautiful” initiative. Twelve months and nearly 10,000 troops later, the deployment has become a normalized fixture: armed Guard members patrol the National Mall, Metro stations, and neighborhoods, while also picking up trash, spreading mulch, and pruning trees. The Pentagon now projects the mission—which Trump has authorized through Inauguration Day 2029—will cost an additional $1.4 billion. But a year in, it remains genuinely unclear what these troops are actually doing, and whether much of it counts as law enforcement at all. What has the deployment accomplished? And what does its open-ended normalization mean for the use of the military at home?
In object lessons, Mike is descending into madness; that is, the Dark Horse Comics manga adaptation of H.P. Lovecraft’s “At the Mountains of Madness.” Alan is being sucked into the black hole of binge reading “The Expanse” novel series (and then Alan and Scott nerd out to sci-fi generally; bear with it). Scott is voting “yea” on playing “Yea or Nay” today. And Loren is diving into handwritten primary source documents, and you can, too!
Note: We'll be on vacation next week, so be on the lookout for our next episode on August 27!
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Weeks after Ukraine's President Volodymyr Zelensky fired Defense Minister Mykhailo Fedorov, the fallout is still reshaping Kyiv's political landscape. Lawfare Ukraine Fellow Anastasiia Lapatina is joined by Danylo Mokryk, a war crimes investigator at the Kyiv Independent and the author of a YouTube blog about domestic Ukrainian Politics, to unpack what's happened since Federov's departure.
They discuss the dismissal of General Syrskyi, Fedorov's rejection of a hollow "vice prime minister" role, and his rise in the polls despite having no formal political ambitions. They also dig into why Zelensky refuses to explain his personnel decisions to the public, why the shrinking street protests may actually be a bad sign for the president, the reshuffling of appointments across Ukraine's security services, and what all of this says about the erosion of institutional trust during wartime.
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Senior Editor Scott R. Anderson sits down with Contributing Editor Joel Braunold, Managing Director of the Center Project, for the latest installment of their podcast series on developments in the Israeli-Palestinian conflict.
Together, they discuss the Trump administration's new plan for Gaza, why Israel doesn't appear to be on board with it, related developments in Lebanon and the West Bank, and how it is all intersecting with Israel's impending elections.
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On August 6, Lawfare Senior Editor Kate Klonick sat down for a live discussion on Substack with Renée DiResta, Associate Research Professor at Georgetown’s McCourt School of Public Policy and a Lawfare contributing editor, about her new piece with Ronald Robertson on Grokipedia, the AI-generated encyclopedia. DiResta and Robertson found that Grokipedia’s edit-review queue froze around April 24—with over 13,000 suggestions stuck “in review” and zero resolved in the last three months—with no announcement to users or contributors.
They discuss the methodology of how DiResta and Robertson reconstructed a site-wide activity leaderboard using Grokipedia’s search typeahead, since the site publishes no rankings itself; how a mass rewrite on March 14 broke the anchors linking suggested edits to specific text, retroactively relabeling some accepted edits as “rejected”; and how the new AI information ecosystem is being shaped by out-of-date but open-access resources with no accountability.
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