Hallucinations
AI systems that inadvertently generate or spread incorrect or deceptive information, which can lead to inaccurate beliefs in users and undermine their autonomy. Humans that make decisions based on false beliefs can experience physical, emotional or material harms
Significant concerns are raised about LLMs inadvertently generating false or misleading information, as well as erroneous code. Papers not only critically analyze various types of reasoning errors in LLMs but also examine risks associated with specific types of misinformation, such as medical hallucinations. Given the propensity of LLMs to produce flawed outputs accompanied by overconfident rationales and fabricated references, many sources stress the necessity of manually validating and fact-checking the outputs of these models.(p. 6)
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 contentPrivacy
2.1 Compromise of privacy by leaking or correctly inferring sensitive informationInteraction risks
5.1 Overreliance and unsafe useSecurity - Robustness
2.2 AI system security vulnerabilities and attacks