148 citations · 164 across the 3 of their papers we have counts for
3 papers
cs.CY2023★ 5 cited
A Cost Analysis of Generative Language Models and Influence Operations
Micah Musser
Despite speculation that recent large language models (LLMs) are likely to be used maliciously to improve the quality or scale of influence operations, uncertainty persists regardi…
cs.CR2023★ 11 cited
Adversarial Machine Learning and Cybersecurity: Risks, Challenges, and Legal Implications
Micah Musser, Andrew Lohn, James X. Dempsey +14
In July 2022, the Center for Security and Emerging Technology (CSET) at Georgetown University and the Program on Geopolitics, Technology, and Governance at the Stanford Cyber Polic…
cs.CY2023★ 148 cited
Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations
Josh A. Goldstein, Girish Sastry, Micah Musser +3
Generative language models have improved drastically, and can now produce realistic text outputs that are difficult to distinguish from human-written content. For malicious actors,…