Sarath Swaminathan, Nathaniel Park, et al.
NeurIPS 2025
Artificial Intelligence is becoming part of any technology we use nowadays. If the AI informs people's decisions, the explanation about AI's outcomes, results, and behavior becomes a necessary capability. However, the discussion of XAI features with various stakeholders is not a trivial task. Most of the available frameworks and methods for XAI focus on data scientists and ML developers as users. Our research is about XAI for end-users of AI systems. We argue that we need to discuss XAI early in the AI-system design process and with all stakeholders. In this work, we aimed at investigating how to operationalize the discussion about XAI scenarios and opportunities among designers and developers of AI and its end-users. We took the Signifying Message as our conceptual tool to structure and discuss XAI scenarios. We experiment with its use for the XAI discussion of a healthcare AI-System.
Workshop "Operationalizing Human-Centered Perspectives in Explainable AI": https://hcxai.jimdosite.com/
Sarath Swaminathan, Nathaniel Park, et al.
NeurIPS 2025
Thomas Bohnstingl, Ayush Garg, et al.
ICASSP 2022
Wojciech Ozga, Do Le Quoc , et al.
IFIP DBSec 2021
Jiaqi Han, Wenbing Huang, et al.
NeurIPS 2022