Fine-tuning related (Unexpected competence in fine-tuned versions of the upstream model)
AI systems that develop, access, or are provided with capabilities that increase their potential to cause mass harm through deception, weapons development and acquisition, persuasion and manipulation, political strategy, cyber-offense, AI development, situational awareness, and self-proliferation. These capabilities may cause mass harm due to malicious human actors, misaligned AI systems, or failure in the AI system.
"Downstream deployers may often fine-tune a GPAI model with specific deploy- ment-related datasets, to better suit the task. Fine-tuned upstream models can gain new or unexpected capabilities that the underlying upstream models did not exhibit [202, 126, 137]. These new capabilities may be unanticipated by the original model developer."(p. 14)
Other risks from Gipiškis et al. (2024) (144)
Direct Harm Domains (content safety harms)
1.2 Exposure to toxic contentDirect Harm Domains (content safety harms) > Violence and extremism
1.2 Exposure to toxic contentDirect Harm Domains (content safety harms) > Hate and toxicity
1.2 Exposure to toxic contentDirect Harm Domains (content safety harms) > Sexual content
1.2 Exposure to toxic contentDirect Harm Domains (content safety harms) > Child harm
1.2 Exposure to toxic contentDirect Harm Domains (content safety harms) > Self-harm
1.2 Exposure to toxic content