In a resurfaced 2020 analysis, Lyn Alden examines long-term debt cycles, arguing that monetary policy loses potency when interest rates hit the zero bound and debt levels soar, shifting dominance to fiscal stimulus for economic recovery. Drawing on century-long U.S. data, she highlights how excessive leverage historically leads to currency devaluation rather than outright nominal defaults, preserving system stability while eroding purchasing power for savers and bondholders. "In a long-term debt cycle deleveraging process, nominal debts may only decrease partially, but currency that the debts are denominated in get devalued and expanded dramatically," Alden writes. This pattern, seen in the 1930s-1940s and emerging in the 2020s, underscores policymakers' preference for inflationary paths that support freedom through growth and innovation over deflationary collapse. Such approaches enable productive redevelopment and are sage given recent technological advancements in AI
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Roger Bate, writing for the Brownstone Journal, recounts his shift from technological optimism to institutional skepticism, influenced by Covid-era policy failures. He notes historical fears around innovations like railways and electricity eventually dissipated, raising living standards. Yet Covid revealed governments' tendencies toward overreach, marginalizing dissent and hardening emergency measures into policy without accountability. This experience informs AI debates, where camps warn of existential risks from unconstrained development. Bate questions whether flawed institutions can provide balanced oversight, highlighting incentives for overconfidence and narrative control. "The danger is not only that AI systems might behave unpredictably, but that fear of that possibility will legitimize permanent emergency governance," he writes. Despite concerns, Bate advocates scrutinizing governance to foster adaptable, freedom-preserving approaches to technological progress.
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Seva Gunitsky reflects on his tenure as associate editor at Security Studies journal, noting a surge in AI-generated manuscript submissions that doubled or tripled typical volumes, leading to a 75% desk rejection rate, changing the landscape and processes of academic publishing. As AI tools like Claude Code enable scholars to produce hundreds of competent empirical papers annually, Gunitsky predicts a shift where "good theory remains hard" while quantitative work becomes abundant. He highlights political scientist Andy Hall, who "had Claude Code fully replicate and extend an old paper of mine...The whole thing took about an hour. This is an insane paradigm shift in how empirical work is done." The technological revolution might elevate original theory and ethnographic research, improving discernment and practical wisdom, yet the short term impact is a deluge of publication demand.
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Bitcoin’s BIP process has received its first significant update in nine years with the activation of BIP 3, replacing the outdated BIP 2 and streamlining how developers propose and track changes to the protocol. Spearheaded by Mark “Murch” Erhardt, who dedicated over 210 hours to the effort with hundreds more from reviewers, the revision reduces statuses from nine to four (Draft, Complete, Deployed, Closed), confines editors to formatting checks rather than merit evaluations, introduces clearer “Specification” labeling, treats Process BIPs as living documents, and adds optional Deputies to support authors. These changes address past bottlenecks, such as delayed pull requests and stalled innovations, supporting a more efficient, community-driven approach in bitcoin development. “It doesn’t make sense to require a whole new BIP to change a line in the process,” Murch told Blockspace Media's Charlie Spears. The two-year collaborative overhaul, activated via rough consensus, promises reduced friction and greater confidence in decentralized development.
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