Paper Type
Complete
Paper Number
PACIS2026-2117
Description
AI is becoming embedded in organisational and social life, yet MIS scholarship has only begun to explain the ethical consequences of how AI becomes normalised and how AI, in turn, can (de)normalise beliefs, practices, artifacts and arrangements. This paper helps address that gap by reviewing emerging cross-disciplinary literature positioned directly at this intersection to formulate a formative framework of AI's Ethical Normalisation; Epistemic Regimes, Power Relations, Behavioural Design, and Meaning & Identity. Importantly, we distinguish between Normalisation of AI and Normalisation using AI and draw on scholarly work to illuminate how AI’s ethical effects arise not only at adoption, but through routinisation, stabilisation, and moral invisibility as AI becomes embedded in practice. The paper's contribution is to advance responsible-AI research in MIS through a formative framework of AI's Ethical Normalisation, along with overarching mechanisms of intervention, and research directions for studying AI's ethical normalisation as socio-technical governance challenge.
Recommended Citation
Mcloughlin, Shane J., "Living Above The Algorithm: The Intersection of AI, Normalisation and Ethics Research" (2026). PACIS 2026 Proceedings. 19.
https://aisel.aisnet.org/pacis2026/ai_ethic/ai_ethic/19
Living Above The Algorithm: The Intersection of AI, Normalisation and Ethics Research
AI is becoming embedded in organisational and social life, yet MIS scholarship has only begun to explain the ethical consequences of how AI becomes normalised and how AI, in turn, can (de)normalise beliefs, practices, artifacts and arrangements. This paper helps address that gap by reviewing emerging cross-disciplinary literature positioned directly at this intersection to formulate a formative framework of AI's Ethical Normalisation; Epistemic Regimes, Power Relations, Behavioural Design, and Meaning & Identity. Importantly, we distinguish between Normalisation of AI and Normalisation using AI and draw on scholarly work to illuminate how AI’s ethical effects arise not only at adoption, but through routinisation, stabilisation, and moral invisibility as AI becomes embedded in practice. The paper's contribution is to advance responsible-AI research in MIS through a formative framework of AI's Ethical Normalisation, along with overarching mechanisms of intervention, and research directions for studying AI's ethical normalisation as socio-technical governance challenge.
Comments
03-EthicsSocietalImpact