Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations
Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations
A joint report with Georgetown University’s Center for Security and Emerging Technology OpenAI and Stanford Internet Observatory
In recent years, artificial intelligence (AI) systems have significantly improved and their capabilities have expanded. In particular, AI systems called “generative models” have made great progress in automated content creation, such as images generated from text prompts. One area of particularly rapid development has been generative models that can produce original language, which may have benefits for diverse fields such as law and healthcare. However, there are also possible negative applications of generative language models, or “language models” for short. For malicious actors looking to spread propaganda—information designed to shape perceptions to further an actor’s interest—these language models bring the promise of automating the creation of convincing and misleading text for use in influence operations, rather than having to rely on human labor. For society, these developments bring a new set of concerns: the prospect of highly scalable—and perhaps even highly persuasive—campaigns by those seeking to covertly influence public opinion. This report aims to assess: how might language models change influence operations, and what steps can be taken to mitigate these threats? This task is inherently speculative, as both AI and influence operations are changing quickly.