Paper Number

ECIS2026-2812

Paper Type

CRP

Abstract

As artificial intelligence (AI) increasingly influences economic and social systems, governance frameworks often assume universally shared ethical principles. However, growing evidence suggests that how principles such as fairness, accountability, and transparency are interpreted and prioritized varies systematically across cultural contexts. To address this gap, we develop a configurational typology of AI governance based on cultural–ethical fit. Drawing on a systematic literature review, we identify eight ideal-type AI governance profiles, namely group fairness, individual fairness, market-led growth, value-led growth, human oversight fortress, autonomous growth, individual control, and collective security, each reflecting distinct alignments between cultural value orientations, ethical priorities, and regulatory mechanisms central to ethical and responsible AI. The typology provides a structured basis for analysing and designing context-sensitive AI governance, while offering a foundation for future empirical validation and comparative research.

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Jun 14th, 12:00 AM

Toward Cultural–Ethical Fit In AI Governance: A Global Typology Of Governance Profiles

As artificial intelligence (AI) increasingly influences economic and social systems, governance frameworks often assume universally shared ethical principles. However, growing evidence suggests that how principles such as fairness, accountability, and transparency are interpreted and prioritized varies systematically across cultural contexts. To address this gap, we develop a configurational typology of AI governance based on cultural–ethical fit. Drawing on a systematic literature review, we identify eight ideal-type AI governance profiles, namely group fairness, individual fairness, market-led growth, value-led growth, human oversight fortress, autonomous growth, individual control, and collective security, each reflecting distinct alignments between cultural value orientations, ethical priorities, and regulatory mechanisms central to ethical and responsible AI. The typology provides a structured basis for analysing and designing context-sensitive AI governance, while offering a foundation for future empirical validation and comparative research.

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