{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T14:37:05Z","timestamp":1792852625962,"version":"4.5.0"},"reference-count":6,"publisher":"Naksh Solutions","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJARSCT"],"abstract":"<jats:p>The increasing integration of artificial intelligence (AI) into criminal justice has created opportunities to support crime analysis, investigative processes, legal research, and risk assessment. However, the use of AI in decisions affecting liberty and fundamental rights raises important ethical concerns. This paper examines four interconnected challenges associated with AI-driven decision-making in criminal justice: algorithmic bias, limited transparency, accountability gaps, and potential violations of privacy and human rights. Drawing on the themes developed in the underlying thesis and its reviewed literature, the paper develops a conceptual ethical framework for the responsible deployment of AI in criminal justice. The proposed framework emphasizes representative data, explainable decision-making, independent auditing, clearly assigned institutional responsibility, meaningful human oversight, and accessible mechanisms for contesting adverse decisions. It also considers the risks of predictive policing, surveillance technologies, and automated risk assessment. The paper argues that technical performance alone is insufficient to establish the legitimacy of AI-assisted criminal justice decisions. Responsible deployment requires continuous evaluation of fairness, protection of individual rights, and effective legal and institutional safeguards. The framework is intended to support researchers, policymakers, technology developers, and criminal justice institutions in assessing the ethical acceptability of AI systems<\/jats:p>","DOI":"10.48175\/ijarsct-40135","type":"journal-article","created":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T14:01:24Z","timestamp":1792850484000},"page":"269","source":"Crossref","is-referenced-by-count":0,"title":["Responsible AI in Criminal Justice: An Ethical Framework for Algorithmic Fairness, Transparency, Accountability, and Human Rights"],"prefix":"10.48175","author":[{"family":"Dr. Surineni Triveni","sequence":"first","affiliation":[{"name":"Government Degree College, Mancherial, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"25968","published-online":{"date-parts":[[2026,10,24]]},"reference":[{"key":"ref0","unstructured":"1.\tBarocas, S., Hardt, M., & Narayanan, A. (2019). Fairness and Machine Learning: Limitations and Opportunities. Online book manuscript."},{"key":"ref1","doi-asserted-by":"crossref","unstructured":"2.\tSelbst, A. D., et al. (2019). Fairness and abstraction in sociotechnical systems. Proceedings of the Conference on Fairness, Accountability, and Transparency.","DOI":"10.1145\/3287560.3287598"},{"key":"ref2","unstructured":"3.\tKroll, J. A., et al. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165(3), 633\u2013705."},{"key":"ref3","unstructured":"4.\tEuropean Commission High-Level Expert Group on Artificial Intelligence. (2019). Ethics Guidelines for Trustworthy AI."},{"key":"ref4","unstructured":"5.\tNational Institute of Standards and Technology. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). NIST AI 100-1."},{"key":"ref5","unstructured":"6.\tUNESCO. (2021). Recommendation on the Ethics of Artificial Intelligence."}],"container-title":["International Journal of Advanced Research in Science Communication and Technology"],"original-title":[],"deposited":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T14:01:26Z","timestamp":1792850486000},"score":1,"resource":{"primary":{"URL":"https:\/\/ijarsct.co.in\/Paper40135.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,24]]},"references-count":6,"URL":"https:\/\/doi.org\/10.48175\/ijarsct-40135","relation":{},"ISSN":["2581-9429"],"issn-type":[{"value":"2581-9429","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,24]]},"article-number":"40135"}}