Ethical and Responsible AI: Governance Frameworks and Policy Implications for Multi-Agent Systems - Tejaskumar Pujari; Anshul Goel; Ashwin Sharma (International Journal Science and Technology, 2024)
Semi-autonomous, augmented- Artificial Intelligence has become increasingly relevant as collective activities are practiced by two or more autonomic entities. MAS and AI at the intersection have fostered very new waves of socioeconomic exchange, necessitating technological governance and, the most challenging element of them all, ethical governance. These autonomous systems involve a network of decision-making agents working in a decentralized environment, entailing very high accountability, transparency, explanability, ethical alignment, and practically everything in between. The escalated societal functioning of these systems necessitates massive social governance policy interventions and an interdisciplinary governance framework. As an overarching look of multispecialty fields, the research aimed to underscore and pinpoint technology like responsible AI, normative governance frameworks, and multi-agent coordination. This paper unravels insofar as the ethical dilemmas in MAS, picking up loose threads from such international governance configurations and proposing a more adaptive regulatory ethic from an awareness of what it means to coordinate intelligent agents. Bringing together thoughts from ethics, law, computer science, and policy studies, the paper essentially sketches out a path for establishing an AI environment that is sustainable, trustworthy, and ethically grounded.