Rational Security: The “We’re Moving to Microsoft” Edition
This week on Rational Security, a contentedly full post-Thanksgiving Scott and Quinta sat down with two Lawfare colleagues—Senior Editor and Brookings Institution Senior Fellow Molly Reynolds and Cyber Fellow Eugenia Lostri—to talk through the week’s big national security news stories, including:
- “Showdown with an Only O.K. Rationale.” The House and Senate are preparing for a showdown over national security priorities, with assistance for Ukraine (and Israel and border security) hanging in the balance. Where does the debate seem likely to go from here—and what will the global ramifications be?
- “Bringing Down the @SamA.” OpenAI, the non-profit(?) behind ChatGPT, has had a chaotic few weeks, with its board ousting CEO Sam Altman on the apparent grounds that he was not taking AI safety concerns seriously enough, only for the vast majority of organization’s employees to threaten to resign unless he was brought back—a step the board took, just before most of its members resigned. What do these events tell us about the state of the AI industry?
- “Carpe Ceasefire.” A fragile pause in hostilities has emerged centered on the exchange of Israeli hostages held by Hamas for imprisoned Palestinians—momentum the Biden administration is reportedly hoping to build on. Yet calls for a permanent ceasefire continue amidst mounting civilian casualties and humanitarian needs, and there remains no clear plan for a post-war Gaza. How long will the pause last? What happens when hostilities resume?
For object lessons, Quinta recommended the 1990s classic “Distant Star” by Robert Bolaño. Scott gave his Thanksgiving gold star to Eric Kim’s creamy mac and cheese recipe. Molly leaned into her love for local NPR affiliates and recommended WGBH’s podcast “The Big Dig,” focusing on Boston’s legendary highway project. And secret gamer nerd Eugenia recommended a compelling video game that even parents of toddlers have time to tackle, What Remains of Edith Finch.
Support this show http://supporter.acast.com/lawfare.
Hosted on Acast. See acast.com/privacy for more information.
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.