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Artificial intelligence (AI) has been clearly established as a technologywith the potential to revolutionize fields from healthcare to finance - ifdeveloped and deployed responsibly. This is the topic of responsible AI, whichemphasizes the need to develop trustworthy AI systems that minimize bias,protect privacy, support security, and enhance transparency and accountability.Explainable AI (XAI) has been broadly considered as a building block forresponsible AI (RAI), with most of the literature considering it as a solutionfor improved transparency. This work proposes that XAI and responsible AI aresignificantly more deeply entwined. In this work, we explore state-of-the-artliterature on RAI and XAI technologies. Based on our findings, we demonstratethat XAI can be utilized to ensure fairness, robustness, privacy, security, andtransparency in a wide range of contexts. Our findings lead us to conclude thatXAI is an essential foundation for every pillar of RAI.

Explainable AI is Responsible AI: How Explainability Creates Trustworthy and Socially Responsible Artificial Intelligence