TY - GEN
T1 - TExSS 22
T2 - 27th International Conference on Intelligent User Interfaces, IUI 2022
AU - Kuflik, Tsvi
AU - Dodge, Jonathan
AU - Kleanthous, Styliani
AU - Lim, Brian
AU - Negreanu, Carina
AU - Sarkar, Advait
AU - Shulner-Tal, Avital
AU - Smith-Renner, Alison
AU - Stumpf, Simone
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/3/22
Y1 - 2022/3/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85127761452&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85127761452&partnerID=8YFLogxK
U2 - 10.1145/3490100.3511165
DO - 10.1145/3490100.3511165
M3 - Conference contribution
AN - SCOPUS:85127761452
T3 - International Conference on Intelligent User Interfaces, Proceedings IUI
SP - 16
EP - 17
BT - 27th International Conference on Intelligent User Interfaces, IUI 2022 Companion
PB - Association for Computing Machinery
Y2 - 22 March 2022 through 25 March 2022
ER -