Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Transparency in Translation: A Deep Dive into Explainable AI Techniques for Bias Mitigation Subject The topic of the resource Bias mitigation; Counterfactual explanations; Explainable AI (XAI); Fairness; Layerwise Relevance Propagation; LIME (Local Interpretable Model-agnostic Explanations); Sensitivity Analysis; SHAP (SHapley Additive exPlanations) Description An account of the resource In an era dominated by artificial intelligence (AI), concerns about bias and discrimination loom large. The quest for fairness and equity in AI-driven decision-making has led to the exploration of Explainable AI (XAI) as a viable solution. This paper undertakes a thorough examination of the bias ingrained within AI systems and posits XAI as a potent antidote. Beginning with an exploration of the origins and aftermath of bias in AI, the analysis traverses the evolution of XAI techniques, including SHAP, LIME, and counterfactual explanations, clearly stating their advantages and drawbacks. With each XAI method thoroughly inspected, the study unravels their applicability across diverse AI models and domains. Furthermore, a compelling case study is presented, showcasing XAI's practical application in a language translation app, where it guarantees transparency and equity in the translation process. This tangible example serves as a testament to XAI's efficacy in mitigating bias within real-world applications. As the analysis concludes, it underscores the pivotal role XAI plays in fostering accountability and trustworthiness in AI systems. By shedding light on how XAI mitigates bias and offering concrete examples of its utility, the paper advocates for its widespread adoption as an imperative step towards the development of ethically robust AI systems. In a landscape filled with concerns about bias, XAI emerges as a beacon of hope, promising a future where AI decisions are transparent, fair, and equitable for all. 2024 IEEE. Creator An entity primarily responsible for making the resource Deokar R.; Nanjundan P.; Mohanty S.N. Source A related resource from which the described resource is derived 2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/APCIT62007.2024.10673712" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/APCIT62007.2024.10673712</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205531396&amp;doi=10.1109%2FAPCIT62007.2024.10673712&amp;partnerID=40&amp;md5=5aad0de73251aa5117c88d5478603bff" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205531396&amp;doi=10.1109%2fAPCIT62007.2024.10673712&amp;partnerID=40&amp;md5=5aad0de73251aa5117c88d5478603bff</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835036153-7 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Deokar R., Christ University, Department of Data Science, Pune, Lavasa, India; Nanjundan P., Christ University, Department of Data Science, Pune, Lavasa, India; Mohanty S.N., School of Computer Science &amp; Engineering, VIT -AP University, Andhra Pradesh, India