Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.