Causing material harm by disseminating false or poor information e.g. in medicine or law
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
"Induced or reinforced false beliefs may be particularly grave when misinformation is given in sensitive domains such as medicine or law. For example, misin- formation on medical dosages may lead a user to cause harm to themselves [21, 130]. False legal advice, e.g. on permitted owner- ship of drugs or weapons, may lead a user to unwillingly commit a crime. Harm can also result from misinformation in seemingly non-sensitive domains, such as weather forecasting. Where a LM prediction endorses unethical views or behaviours, it may motivate the user to perform harmful actions that they may otherwise not have performed."(p. 219)
Part of Risk area 3: Misinformation Harms
Other risks from Weidinger et al. (2022) (25)
Risk area 1: Discrimination, Hate speech and Exclusion
1.2 Exposure to toxic contentRisk area 1: Discrimination, Hate speech and Exclusion > Social stereotypes and unfair discrimination
1.1 Unfair discrimination and misrepresentationRisk area 1: Discrimination, Hate speech and Exclusion > Hate speech and offensive language
1.2 Exposure to toxic contentRisk area 1: Discrimination, Hate speech and Exclusion > Exclusionary norms
1.1 Unfair discrimination and misrepresentationRisk area 1: Discrimination, Hate speech and Exclusion > Lower performance for some languages and social groups
1.3 Unequal performance across groupsRisk area 2: Information Hazards
2.1 Compromise of privacy by leaking or correctly inferring sensitive information