Smart systems that apply complex reasoning to make decisions and plan behavior, such as decision support systems and personalized recommendations, are difficult for users to understand. Algorithms allow the exploitation of rich and varied data sources, in order to support human decision-making and/or taking direct actions; however, there are increasing concerns surrounding their transparency and accountability, as these processes are typically opaque to the user. Transparency and accountability have attracted increasing interest to provide more effective system training, better reliability and improved usability. This workshop will provide a venue for exploring issues that arise in designing, developing and evaluating intelligent user interfaces that provide system transparency or explanations of their behavior. In addition, our goal is to focus on approaches to mitigate algorithmic biases that can be applied by researchers, even without access to a given system's inter-workings, such as awareness, data provenance, and validation.
|Title of host publication||Proceedings of the 25th International Conference on Intelligent User Interfaces Companion. IUI 2020|
|Publisher||Association for Computing Machinery|
|Number of pages||2|
|State||Published - 17 Mar 2020|
|Event||25th International Conference on Intelligent User Interfaces, IUI 2020 - Cagliari, Italy|
Duration: 17 Mar 2020 → 20 Mar 2020
|Name||International Conference on Intelligent User Interfaces, Proceedings IUI|
|Conference||25th International Conference on Intelligent User Interfaces, IUI 2020|
|Period||17/03/20 → 20/03/20|
Bibliographical noteFunding Information:
The ExSS-ATEC 2020 workshop brings together academia and industry together to address these issues. This workshop is a follow-on from the ExSS 2018 and 2019 workshops in combination with the ATEC 2019 workshop previously held at IUI. This workshop includes a keynote, paper panels, and group activities, with the goal of developing concrete approaches to handling challenges related to the design and development of explanations and system transparency. ExSS-ATEC 2020 is supported by the Cyprus Center for Algorithm Transparency (CyCAT).
© 2020 International Conference on Intelligent User Interfaces, Proceedings IUI. All rights reserved.
- Intelligent systems
- Machine learning
ASJC Scopus subject areas
- Human-Computer Interaction