Harmful Content Generation at Scale: Non-Consensual Content
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.
"The misuse of generative AI has been widely recognized in the context of harms caused by non-consensual content generation. Historically, generative adversarial networks (GANs) have been used to generate realistic-looking avatars for fake accounts on social media services. More recently, diffusion models have enabled a new generation of more flexible and user-friendly generative AI capabilities that are able to produce high-resolution media based on user-supplied textual prompts. It has already been recognized that these models can be used to create harmful content, including depictions of nudity, hate, or violence. Moreover, they can be used to reinforce biases and subject individuals or groups to indignity. There is also the potential for these models to be used for exploitation and harassment of citizens, such as by removing articles of clothing from pre-existing images or memorizing an individual’s likeness without their consent. Furthermore, image, audio, and video generation models could be used to spread disinformation by depicting political figures in unfavorable contexts. This growing list of AI misuses involving non-consensual content has already motivated debate around what interventions are warranted for preventing misuse of AI systems. Advanced AI assistants pose novel risks that can amplify the harm caused by non-consensual content generation. Third-party integration, tool-use, and planning capabilities can be exploited to automate the identification and targeting of individuals for exploitation or harassment. Assistants with access to the internet and third-party tool-use integration with applications like email and social media can also be exploited to disseminate harmful content at scale or to microtarget individuals with blackmail."(p. 75)
Part of Malicious Uses
Other risks from Gabriel et al. (2024) (69)
Capability failures
7.3 Lack of capability or robustnessCapability failures > Lack of capability for task
7.3 Lack of capability or robustnessCapability failures > Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
6.5 Governance failureCapability failures > Safe exploration problem with widely deployed AI assistants
7.3 Lack of capability or robustnessGoal-related failures
7.1 AI pursuing its own goals in conflict with human goals or valuesGoal-related failures > Misaligned consequentialist reasoning
7.3 Lack of capability or robustness