Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there’s been growing recognition that explainability is inherently human-centric, tied to how people perceive explanations. Despite this, there is no consensus in the research community on whether user evaluation is crucial in XAI, and if so, what exactly needs to be evaluated and how. This systematic literature review addresses this gap by providing a detailed overview of the current state of affairs in human-centered XAI evaluation. We reviewed 73 papers across various domains where XAI was evaluated with users. These studies assessed what makes an explanation “good” from a user’s perspective, i.e., what makes an explanation meaningful to a user of an AI system. We identified 30 components of meaningful explanations that were evaluated in the reviewed papers and categorized them into a taxonomy of human-centered XAI evaluation, based on: (a) the contextualized quality of the explanation, (b) the contribution of the explanation to human-AI interaction, and (c) the contribution of the explanation to human- AI performance. Our analysis also revealed a lack of standardization in the methodologies applied in XAI user studies, with only 19 of the 73 papers applying an evaluation framework used by at least one other study in the sample. These inconsistencies hinder cross-study comparisons and broader insights. Our findings contribute to understanding what makes explanations meaningful to users and how to measure this, guiding the XAI community toward a more unified approach in human-centered explainability.
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Background: Information is scarce concerning the perceived needs and the amount of health-care utilization of persons with suicidal ideation (SI) compared to those without SI. Aims: To describe the needs and health care use of persons with and without SI and to investigate whether these differences are associated with the severity of the axis-I symptomatology. Method: Data were obtained from 1,699 respondents with a depressive and/or anxiety disorder who participated in the Netherlands Study of Depression and Anxiety. Persons with and without SI were distinguished. Outcome variables were perceived needs and health-care utilization. We used multivariate regression in two models: (1) adjusted only for sociodemographic variables and (2) adjusted additionally for severity of axis-I symptomatology. Results: Persons with SI had higher odds for both unmet and met needs in almost all domains and made more intensive use of mental-health care. Differences in needs and health-care utilization of persons with and without SI were strongly associated with severity of axis I symptomatology. Conclusions: Our results validate previous findings about perceived needs and health-care use of persons with SI. The results also suggest that suicidal persons are more seriously ill, and that they need more professional care, dedication, and specialized expertise than anxious and depressed persons without SI, especially in the domains of information and referral.
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