Beyond Procedural Compliance: Human Oversight as a Dimension of Well-being Efficacy in AI Governance

2025-12-15

AI Summary

Contemporary AI ethics guidelines and regulations—including the EU AI Act—emphasize human oversight but fail to define it as a cultivable core competency. Method: This paper introduces the paradigm of “human oversight as a well-being capability,” reconceptualizing oversight as a teachable, integrative capacity encompassing AI literacy, ethical reasoning, and need-awareness—particularly the identification and constraint of harmful needs—within the theoretical framework of Well-being Efficacy. Through interdisciplinary conceptual modeling, analysis of ethical competence structures, pedagogical pathway design, and development of a governance-capacity assessment framework, the study operationalizes human oversight as measurable, teachable, and sustainably developable. Contribution/Results: The work transcends compliance-driven approaches, bridging the gap between AI governance objectives and the cultivation of human agency. It establishes a foundational theory for systemic educational interventions and multi-context empirical validation in AI ethics and governance.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Humans and AI: Learning Human Values and Preferences
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Major AI ethics guidelines and laws, including the EU AI Act, call for effective human oversight, but do not define it as a distinct and developable capacity. This paper introduces human oversight as a well-being capacity, situated within the emerging Well-being Efficacy framework. The concept integrates AI literacy, ethical discernment, and awareness of human needs, acknowledging that some needs may be conflicting or harmful. Because people inevitably project desires, fears, and interests into AI systems, oversight requires the competence to examine and, when necessary, restrain problematic demands. The authors argue that the sustainable and cost-effective development of this capacity depends on its integration into education at every level, from professional training to lifelong learning. The frame of human oversight as a well-being capacity provides a practical path from high-level regulatory goals to the continuous cultivation of human agency and responsibility essential for safe and ethical AI. The paper establishes a theoretical foundation for future research on the pedagogical implementation and empirical validation of well-being effectiveness in multiple contexts.

Problem

• Defines human oversight as a distinct, developable capacity for AI governance.
• Integrates AI literacy, ethical discernment, and awareness of human needs.
• Proposes integrating this capacity into education for sustainable, ethical AI development.

Innovation

• Human oversight as a well-being capacity
• Integrates AI literacy, ethical discernment, and needs awareness
• Requires education integration for sustainable development