A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context

A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context

연구 분야: Artificial Intelligence

학회: AIES '23: Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society

Acknowledging that society is made up of different sectors with their own rules and structures, this paper studies the relevance of a sector-specific perspective to AI ethics. Incidents with AI are studied in relation to five sectors (police, healthcare, education and academia, politics, automotive) using the AIAAIC repository. A total of 125 incidents are sampled and analyzed by conducting a qualitative content analysis on media reports. The results show that certain ethical principles are found breached across sectors: accuracy/reliability, bias/discrimination, transparency, surveillance/privacy, security. However, results also show that 1) some ethical issues (misinformation, safety, premise/intent) are sector specific, 2) the consequences and meaning of the same ethical issue is able to vary across sectors and 3) pre-existing sector-specific issues are reproduced with these ethical breaches. The paper concludes that general ethical principles are relevant to discuss across sectors, yet, a sector-based approach to AI ethics gives in-depth information on sector-specific structural issues.