Misinformation and Manipulation
Using AI systems to gain a personal advantage over others such as through cheating, fraud, scams, blackmail or targeted manipulation of beliefs or behavior. Examples include AI-facilitated plagiarism for research or education, impersonating a trusted or fake individual for illegitimate financial benefit, or creating humiliating or sexual imagery.
"Recent studies have demonstrated that LLMs can be exploited to craft deceptive narratives with levels of persuasiveness similar to human-generated content (Pan et al., 2023b; Spitale et al., 2023), to fabri- cate fake news (Zellers et al., 2019; Zhou et al., 2023f), and to devise automated influence operations aimed at manipulating the perspectives of targeted audiences (Goldstein et al., 2023). LLMs have also been found to be used in malicious social botnets (Yang and Menczer, 2023), powering automated accounts used to disseminate coordinated messages. More broadly, the use of LLMs for the deliberate generation of misleading information could significantly lower the barrier for propaganda and manip- ulation (Aharoni et al., 2024), as LLMs can generate highly credible misinformation with significant cost-savings compared to human authorship (Musser, 2023), while achieving considerable scale and speed of content generation (Buchanan et al., 2021; Goldstein et al., 2023)."(p. 84)
Part of Vulnerability to Poisoning and Backdoors
Other risks from Anwar et al. (2024) (26)
Agentic LLMs Pose Novel Risks
7.2 AI possessing dangerous capabilitiesMulti-Agent Safety Is Not Assured by Single-Agent Safety
7.6 Multi-agent risksDual-Use Capabilities Enable Malicious Use and Misuse of LLMs
4.0 Malicious Actors & MisuseCorporate power may impeded effective governance
6.1 Power centralization and unfair distribution of benefitsJailbreaks and Prompt Injections Threaten Security of LLMs
2.2 AI system security vulnerabilities and attacksVulnerability to Poisoning and Backdoors
2.2 AI system security vulnerabilities and attacks