Governance - Regulation
Inadequate regulatory frameworks and oversight mechanisms that fail to keep pace with AI development, leading to ineffective governance and the inability to manage AI risks appropriately.
In response to the multitude of new risks associated with generative AI, papers advocate for legal regulation and governmental oversight. The focus of these discussions centers on the need for international coordination in AI governance, the establishment of binding safety standards for frontier models, and the development of mechanisms to sanction non-compliance. Furthermore, the literature emphasizes the necessity for regulators to gain detailed insights into the research and development processes within AI labs. Moreover, risk management strategies of these labs shall be evaluated. However, the literature also acknowledges potential risks of overregulation, which could hinder innovation.(p. 7)
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
Not coded
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
Not coded
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
Not coded
Other risks from Hagendorff (2024) (16)
Fairness - Bias
1.1 Unfair discrimination and misrepresentationSafety
7.1 AI pursuing its own goals in conflict with human goals or valuesHarmful Content - Toxicity
1.2 Exposure to toxic contentHallucinations
3.1 False or misleading informationPrivacy
2.1 Compromise of privacy by leaking or correctly inferring sensitive informationInteraction risks
5.1 Overreliance and unsafe use