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arXiv:1802.07228cs.AI

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Miles Brundage, Shahar Avin, Jack Clark, Helen Toner, Peter Eckersley, Ben Garfinkel, Allan Dafoe, Paul Scharre, Thomas Zeitzoff, Bobby Filar, Hyrum Anderson, Heather Roff, Gregory C. Allen, Jacob Steinhardt, Carrick Flynn, Seán Ó hÉigeartaigh, SJ Beard, Haydn Belfield, Sebastian Farquhar, Clare Lyle, Rebecca Crootof, Owain Evans, Michael Page, Joanna Bryson, Roman Yampolskiy, Dario Amodei

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

This report surveys the landscape of potential security threats from malicious uses of AI, and proposes ways to better forecast, prevent, and mitigate these threats. After analyzing the ways in which AI may influence the threat landscape in the digital, physical, and political domains, we make four high-level recommendations for AI researchers and other stakeholders. We also suggest several promising areas for further research that could expand the portfolio of defenses, or make attacks less effective or harder to execute. Finally, we discuss, but do not conclusively resolve, the long-term equilibrium of attackers and defenders.

arXiv comments
Journal reference
DOI
Subjects
cs.AIArtificial Intelligence cs.CRCryptography and Security cs.CYComputers and Society

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Feb 2018 to Feb 2018. Found in 6 HN submissions from Feb 2018 to Sep 2026. Open submission discussions.

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    • In case it saves anyone time: the real meat in this link is the arxiv paper: The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation https://arxiv.org/abs/1802.07228

      appleflaxenView on HNParent context

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