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

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

Arti cial intelligence and machine learning capabilities are growing
at an unprecedented rate. These technologies have many widely bene cial applications, ranging from machine translation to medical image analysis. Countless more such applications are being developed and can be expected over the long term. Less attention has historically been paid to the ways in which arti cial intelligence can be used maliciously. This report surveys the landscape of potential security threats from malicious uses of arti cial intelligence technologies, and proposes ways to better forecast, prevent, and mitigate these threats. We analyze, but do not conclusively resolve, the question of what the long-term equilibrium between attackers and defenders will be. We focus instead on what sorts of attacks we are likely to see soon if adequate defenses are not developed