This research explores how human and AI interactions influence ethical decision-making, suggesting accountability frameworks.
The interaction between humans and an Artificial Intelligence (AI) system should be seen as a collaborative endeavor between two actors engaged in a task. A basic element of cooperation between two individuals is mutual monitoring, when one participant oversees the activities of the other. This oversight guarantees that the task meets its goals while distributing accountability for its outcomes. Although AI is progressively used in decision-making (DM) processes, ethical decision-making (EDM) presents obstacles to the use of AI in autonomous systems (AS). Since humans occasionally reach consensus on ethical actions, how would AI-driven EDM be seen, and how would accountability be assigned in human-AI cooperation? This research examines the impact of the subject category (human vs. AI) and the degree of specialist independence (guide versus decision) on confidence, viewed accountability, and dependence. Respondents see humans as more ethically credible but less competent than their AI counterparts. This is seen in individuals' dependence on AI: AI advice and judgments are more often embraced than those of human specialists. Nonetheless, AI team specialists are seen as less accountable than humans, although developers and vendors of AI systems are considered somewhat liable.
No takes yet. Share an insight, caveat, or question.
Vora et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: