Malicious and Indirect

Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy

Sub-category

"Benign intermediate for harmful end objective"(p. 4)

Entity— Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent— Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal

Other

Without clearly specifying the intentionality

Timing— Whether the risk is pre- or post-deployment

Pre-deployment

Occurring before the AI is deployed

Post-deployment

Occurring after the AI model has been trained and deployed

Other

Without a clearly specified time of occurrence

Supporting Evidence (1)

"Malicious intent includes cases where users directly aim to create dangerous situations. Users may also employ an indirect “divide and conquer” approach by instructing the agent to synthesize or produce innocuous components that collectively lead to a harmful outcome."(p. 6)