%0 Generic %1 f28ada09996a4b7eaa8179600576fb56 %A Méndez, Julián %A Satkowski, Marc %A Rzayev, Rufat %D 2023 %K topic_visualcomputing FIS_scads artificial explainable hybrid intelligence, interfaces, mixed reality user %P 251--256 %R 10.1109/ISMAR-Adjunct60411.2023.00058 %T How Does Explainability Look in Hybrid User Interfaces? %U https://ismar23.org/ %X The recent growth of Artificial Intelligence (AI) based systems considerably widespread their use in many application areas and our daily lives 28. For instance, AI models are nowadays imbued into web search engines, self-autonomous vehicles, recommendation systems, games, and healthcare 24. Accordingly, the demand for eXplainable AI (XAI) has risen 20 , 21 to help users cope with the growing complexity and opaqueness of the emerging generation of AI models 20 , 21. By allowing users to perceive and make sense of the behaviors and outcomes of such models, XAI enables users of diverse levels of expertise to trust, manage, design, inspect, and develop AI models 13.

@conference{f28ada09996a4b7eaa8179600576fb56, abstract = {The recent growth of Artificial Intelligence (AI) based systems considerably widespread their use in many application areas and our daily lives [28]. For instance, AI models are nowadays imbued into web search engines, self-autonomous vehicles, recommendation systems, games, and healthcare [24]. Accordingly, the demand for eXplainable AI (XAI) has risen [20] , [21] to help users cope with the growing complexity and opaqueness of the emerging generation of AI models [20] , [21]. By allowing users to perceive and make sense of the behaviors and outcomes of such models, XAI enables users of diverse levels of expertise to trust, manage, design, inspect, and develop AI models [13].}, added-at = {2024-11-28T16:27:18.000+0100}, author = {M{\'e}ndez, Juli{\'a}n and Satkowski, Marc and Rzayev, Rufat}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2201cc79a8d433db63662aff4e5f54e3d/scadsfct}, day = 16, doi = {10.1109/ISMAR-Adjunct60411.2023.00058}, interhash = {eafb312f7037599f07e88250fe1942a6}, intrahash = {201cc79a8d433db63662aff4e5f54e3d}, keywords = {topic_visualcomputing FIS_scads artificial explainable hybrid intelligence, interfaces, mixed reality user}, language = {English}, month = oct, note = {Publisher Copyright: {\textcopyright} 2023 IEEE.; 22nd IEEE International Symposium on Mixed and Augmented Reality ; Conference date: 16-10-2023 Through 20-10-2023}, pages = {251--256}, timestamp = {2024-11-28T17:41:38.000+0100}, title = {How Does Explainability Look in Hybrid User Interfaces?}, url = {https://ismar23.org/}, year = 2023 }