About the Workshop

Smart systems that apply complex reasoning to make decisions, such as decision support or recommender systems, are difficult for people to understand. Algorithms allow the exploitation of rich and varied data sources, in order to support human decision-making; however, there are increasing concerns surrounding their fairness, bias, and accountability, as these processes are typically opaque to users. Transparency and accountability have attracted increasing interest toward more effective system training, better reliability, appropriate trust, and improved usability. The workshop on Transparency and Explanations in Smart Systems (TExSS) will provides a venue for exploring issues when designing, developing, or evaluating transparent intelligent user interfaces, with additional focus on explaining systems and models toward ensuring fairness and social justice.

This workshop was preceded by the joint workshop on Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies (ExSS-ATEC 2020), 2nd Workshop on Explainable Smart Systems (ExSS 2019), and the 2nd International Workshop on Intelligent User Interfaces for Algorithmic Transparency in Emerging Technologies (IUI-ATEC 2019).


Keynote Speaker: Timnit Gebru

Timnit GebruTimnit Gebru co-leads the Ethical Artificial Intelligence research team at Google, working to reduce the potential negative impacts of AI. Timnit earned her doctorate under the supervision of Fei-Fei Li at Stanford University in 2017 and did a postdoc at Microsoft Research NYC in the FATE team. She is also the cofounder of Black in AI, a place for sharing ideas, fostering collaborations and discussing initiatives to increase the presence of Black people in the field of Artificial Intelligence.