Author: Sanat Dutta
DOI Link: https://doi.org/10.70798/Bijmrd/03020006
Abstract: The integration of Artificial Intelligence (AI) into political decision-making has the potential to revolutionize governance by enhancing efficiency, objectivity, and data-driven policymaking. However, this technological advancement also raises profound ethical concerns that threaten democratic principles and public trust. This paper examines the ethical implications of AI in political decision-making, focusing on issues such as algorithmic bias, lack of transparency, accountability gaps, privacy violations, and the potential for misuse. Through a systematic review of literature and case study analysis, the study highlights how biased algorithms can perpetuate discrimination, opaque decision-making processes can erode trust, and the delegation of authority to AI systems can complicate accountability. Additionally, the collection and analysis of vast amounts of personal data for AI applications pose significant privacy risks, while the misuse of AI tools, such as social media bots and micro-targeting algorithms, can manipulate public opinion and undermine democratic processes. Despite these challenges, AI offers opportunities for improving governance, including data-driven policymaking, increased administrative efficiency, and enhanced public engagement. To address these ethical concerns, the paper proposes recommendations such as developing ethical guidelines, ensuring transparency in AI systems, strengthening accountability mechanisms, protecting privacy, and promoting public participation in AI deployment. By adopting these measures, policymakers and stakeholders can harness the benefits of AI while mitigating its risks, ensuring that AI serves the public good and contributes to a more just, equitable, and democratic society. This paper underscores the urgent need for ethical frameworks and regulatory oversight to guide the responsible use of AI in political decision-making.
Keywords: Artificial Intelligence, Political Decision-Making, Ethics, Bias, Transparency, Accountability, Privacy, Democratic Processes.
Page No: 44-48