Author(s) :   Milan Singh

Abstract : As artificial intelligence (AI) continues to permeate various aspects of society, ensuring accountability and transparency in AI decision-making processes has become imperative. This paper explores the significance of accountability and transparency in AI systems, addressing the ethical, social, and legal implications. It examines the challenges associated with opaque AI algorithms and the potential consequences of biased or unjust decision-making. Furthermore, it highlights the strategies and mechanisms proposed to enhance accountability and transparency, including explainable AI (XAI) techniques, algorithmic audits, and regulatory frameworks. The paper concludes by emphasizing the importance of interdisciplinary collaboration among technologists, ethicists, policymakers, and other stakeholders to establish robust governance mechanisms that uphold accountability and transparency in AI decision-making, thereby fostering trust and mitigating potential harm.

Keywords: Artificial Intelligence, Algorithms, Transparency, Accountability.

DOI : Available on author(s) request.

Pages : 27-31

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