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AI systems pose both opportunities and threats in various industries. To harness these opportunities and mitigate risks, accountability is crucial. Traditionally, developers bear the responsibility for auditing and modifying algorithms. How-ever, in the evolving landscape of versatile AI, developers may lack contextual understanding across diverse fields. This paper proposes a theoretical framework that distributes accountability to developers and practitioners according to their capabilities. This framework enhances systemic com-prehension of shared roles, empowering both groups to col-laboratively avert potential adverse impacts.
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Lee et al. (2024) studied this question.
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