TExSS 22: Transparency and Explanations in Smart Systems

Abstract

Smart systems, such as decision support or recommender systems, continue to prove challenging for people to understand, but are nonetheless ever more pervasive based on the promise of harnessing rich data sources that are becoming available in every domain. These systems tend to be opaque, raising important concerns about how to discover and account for fairness or bias issues. The workshop on Transparency and Explanations in Smart Systems (TExSS) welcomes researchers and practitioners interested in exchanging ideas for overcoming the design, development, and evaluation issues in intelligent user interfaces. Specifically, we will focus on barriers preventing better reliability, trainability, usability, trustworthiness, fairness, accountability, and transparency. This year's theme is "Responsible, Explainable AI for Inclusivity and Trust", emphasizing the importance of responsibility that tech-industry and developers have towards the design, implementation and evaluation of explainable, inclusive and trustworthy human-AI interaction.