Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations

By Josh A. Goldstein et al

Published on Jan. 10, 2023

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Table of Contents

Contents
Executive Summary
1 Introduction
1.1 Motivation
1.2 Threats and Mitigations
1.3 Scope and Limitations
1.4 Outline of the Report
2 Orienting to Influence Operations
2.1 What Are Influence Operations, and Why Are They Carried Out?
2.2 Influence Operations and Impact
3 Recent Progress in Generative Models
3.1 What Are Generative Models, and How Are They Built?
3.2 Access and Diffusion of Generative Models
4 Generative Models and Influence Operations
4.1 Language Models and the ABCs of Disinformation
4.2 Expected Developments and Critical Unknowns
5 Mitigations
5.1 A Framework for Evaluating Mitigations
5.2 Model Design and Construction
5.3 Model Access
5.4 Content Dissemination
5.5 Belief Formation
6 Conclusions
6.1 Language Models Will Likely Change Influence Operations
6.2 There Are No Silver Bullet Solutions
6.3 Collective Responses Are Needed
6.4 Mitigations Must Address Demand As Well As Supply
6.5 Further Research Is Necessary
References

Summary

This paper discusses the impact of generative language models on influence operations, highlighting potential threats and mitigation strategies. It explores the intersection of AI technology and political influence operations, emphasizing the importance of understanding the current limitations and critical unknowns in utilizing language models for malicious purposes. The authors propose frameworks for evaluating threats and suggest a variety of mitigation strategies to address the risks associated with the misuse of generative language models in influence campaigns. The paper concludes that a comprehensive approach involving multiple stakeholders is necessary to effectively mitigate the potential threats posed by these advanced AI systems.