Articles

  • Nov 17, 2024 | cnas.org | Markus Anderljung |Marie Boran

    Donald Trump's return to office has raised questions over potential changes to artificial intelligence policy in the United States. The president-elect has promised to dismantle incumbent President Joe Biden's landmark AI executive order and to establish a Department of Government Efficiency, nicknamed DOGE, led by Elon Musk.

  • Oct 22, 2024 | cnas.org | Paul Scharre |Markus Anderljung |Caleb Withers |Pablo Chavez

    Reports August 13, 2024 AI and the Evolution of Biological National Security Risks New AI capabilities may reshape the risk landscape for biothreats in several ways. AI is enabling new capabilities that might, in theory, allow advanced actors to optimize bio... By Bill Drexel & Caleb Withers Commentary Foreign Policy August 4, 2024 The 1960s Novella That Got AI (Mostly) Right A secret military project. A vast artificial mind. Questions of consciousness.

  • May 24, 2024 | cnas.org | Markus Anderljung |Caleb Withers |Paul Scharre

    A secret military project. A vast artificial mind. Questions of consciousness. These form the premise of Dino Buzzati’s The Singularity, originally published in 1960 at the dawn of the field of artificial intelligence (AI). The novella follows Italian scientist Ermanno Ismani, summoned by the Ministry of Defense to work on a top-secret project, as he ventures with his wife, Elisa, to a sprawling machine hidden in the mountains of the Italian countryside.

  • Mar 28, 2024 | lawfaremedia.org | Markus Anderljung |Lennart Heim |Haydn Belfield

    Published by The Lawfare Institute in Cooperation With Computing power—compute, for short—is a key driver of artificial intelligence (AI) progress. Over the past 13 years, the amount of compute used to train leading AI systems has increased by a factor of 350 million. This has enabled the major AI advances that have recently gained global attention. However, compute is important not only for the progress of AI but also for its governance. Governments have taken notice.

  • Feb 21, 2024 | cnas.org | Paul Scharre |Markus Anderljung |Caleb Withers

    Executive Summary Policymakers should prepare for a world of significantly more powerful AI systems over the next decade. These developments could occur without fundamental breakthroughs in AI science simply by scaling up today’s techniques to train larger models on more data and computation. The amount of computation (compute) used to train frontier AI models could increase significantly in the next decade.

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