Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{186536,
        author = {Ms. Jaymala Deshpande Kulkarni},
        title = {Exploring Bias, Fairness, and Accountability in Artificial Intelligence Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {441-443},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186536},
        abstract = {Artificial Intelligence (AI) is an integral part of decision-making processes in many sectors, including healthcare, finance, and criminal justice. However, concerns about bias, fairness, and accountability have raised ethical questions about its widespread use. This paper investigates the sources and consequences of bias in AI systems, reviews different fairness frameworks, and explores methods for ensuring accountability through transparency and regulation. By analyzing case studies where AI systems demonstrated biased behavior, this study highlights the urgent need for ethical AI practices to mitigate discrimination and ensure responsible deployment.},
        keywords = {AI bias, fairness, accountability, ethical AI, transparency, explainable AI, algorithmic justice},
        month = {},
        }