Meaningful Human Control and Responsibility Gaps in AI: No Culpability Gap, but Accountability and Active Responsibility Gap
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Abstract
At the current stage of technological development, the rapid advancement of Artificial Intelligence (AI) has given rise to various ethical concerns. Among these, the “Responsibility Gap” notion has appeared as a prominent issue. Within the scholarly literature, ethicists primarily focus on culpability (or blameworthiness). The central question is: when the development or use of AI results in morally harmful outcomes, who bears moral responsibility? This article argues that moral responsibility encompasses multiple distinct forms, each fulfilling specific functions within a society, especially in the context of AI development and application. Then, three forms of responsibility are considered: culpability, accountability, and active responsibility. Each carries unique social and ethical implications. Drawing on the concept of “meaningful human control,” which serves as a foundational framework, this article contends that the gap in culpability is not as significant or troubling as often suggested in existing research. Instead, the more pressing ethical challenges are associated with gaps in accountability and active responsibility. To address these challenges, this article elaborates on the “tracing condition,” a key element of meaningful human control, to mitigate and prevent morally harmful outcomes and the absence of human responsibility in the age of AI.
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