{"_id":"56479","language":[{"iso":"eng"}],"year":"2024","author":[{"last_name":"Liedeker","full_name":"Liedeker, Felix","first_name":"Felix","id":"93275"},{"first_name":"Christoph","last_name":"Düsing","full_name":"Düsing, Christoph"},{"last_name":"Nieveler","full_name":"Nieveler, Marcel","first_name":"Marcel"},{"full_name":"Cimiano, Philipp","last_name":"Cimiano","first_name":"Philipp"}],"citation":{"ieee":"F. Liedeker, C. Düsing, M. Nieveler, and P. Cimiano, “An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity,” presented at the 2nd World Conference on eXplainable Artificial Intelligence, Valetta, Malta, 2024.","apa":"Liedeker, F., Düsing, C., Nieveler, M., &#38; Cimiano, P. (2024). <i>An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity</i>. 2nd World Conference on eXplainable Artificial Intelligence, Valetta, Malta.","bibtex":"@inproceedings{Liedeker_Düsing_Nieveler_Cimiano_2024, title={An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity}, author={Liedeker, Felix and Düsing, Christoph and Nieveler, Marcel and Cimiano, Philipp}, year={2024} }","mla":"Liedeker, Felix, et al. <i>An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity</i>. 2024.","short":"F. Liedeker, C. Düsing, M. Nieveler, P. Cimiano, in: 2024.","ama":"Liedeker F, Düsing C, Nieveler M, Cimiano P. An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity. In: ; 2024.","chicago":"Liedeker, Felix, Christoph Düsing, Marcel Nieveler, and Philipp Cimiano. “An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity,” 2024."},"keyword":["XAI","Explanation Complexity","User Perception"],"status":"public","conference":{"location":"Valetta, Malta","end_date":"2024-07-19","start_date":"2024-07-17","name":"2nd World Conference on eXplainable Artificial Intelligence"},"date_created":"2024-10-09T14:57:49Z","abstract":[{"lang":"eng","text":"While the importance of explainable artificial intelligence in high-stakes decision-making is widely recognized in existing literature, empirical studies assessing users' perceived value of explanations are scarce. In this paper, we aim to address this shortcoming by conducting an empirical study focused on measuring the perceived value of the following types of explanations: plain explanations based on feature attribution, counterfactual explanations and complex counterfactual explanations. We measure an explanation's value using five dimensions: perceived accuracy, understandability, plausibility, sufficiency of detail, and user satisfaction. Our findings indicate a sweet spot of explanation complexity, with both dimensional and structural complexity positively impacting the perceived value up to a certain threshold."}],"user_id":"93275","title":"An Empirical Investigation of Users' Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity","department":[{"_id":"660"}],"date_updated":"2024-10-09T15:06:00Z","project":[{"_id":"128","name":"TRR 318 - C5: TRR 318 - Subproject C5"}],"type":"conference"}