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

TL;DR

This paper surveys potential malicious uses of AI across various domains, offering forecasts, prevention strategies, and mitigation approaches, while highlighting research directions and discussing the evolving attacker-defender dynamics.

Contribution

It provides a comprehensive overview of AI security threats and proposes high-level recommendations and research areas to improve defense mechanisms.

Findings

Identification of key threat domains: digital, physical, political

Four high-level recommendations for AI security stakeholders

Discussion on long-term attacker-defender equilibrium

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.