Explainable AI is Responsible AI: How Explainability Creates Trustworthy
  and Socially Responsible Artificial Intelligence
Stephanie Baker Wei Xiang
Artificial intelligence (AI) has been clearly established as a technology
with the potential to revolutionize fields from healthcare to finance - if
developed and deployed responsibly. This is the topic of responsible AI, which
emphasizes 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 for
responsible AI (RAI), with most of the literature considering it as a solution
for improved transparency. This work proposes that XAI and responsible AI are
significantly more deeply entwined. In this work, we explore state-of-the-art
literature on RAI and XAI technologies. Based on our findings, we demonstrate
that XAI can be utilized to ensure fairness, robustness, privacy, security, and
transparency in a wide range of contexts. Our findings lead us to conclude that
XAI is an essential foundation for every pillar of RAI.