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Duarte, R., Correia, F., Arriaga, P. & Paiva, A. (2023). AI trust: Can explainable AI enhance warranted trust?. Human Behavior and Emerging Technologies. 2023
R. D. Duarte et al., "AI trust: Can explainable AI enhance warranted trust?", in Human Behavior and Emerging Technologies, vol. 2023, 2023
@article{duarte2023_1724524973939, author = "Duarte, R. and Correia, F. and Arriaga, P. and Paiva, A.", title = "AI trust: Can explainable AI enhance warranted trust?", journal = "Human Behavior and Emerging Technologies", year = "2023", volume = "2023", number = "", doi = "10.1155/2023/4637678", url = "https://www.hindawi.com/journals/hbet/contents/" }
TY - JOUR TI - AI trust: Can explainable AI enhance warranted trust? T2 - Human Behavior and Emerging Technologies VL - 2023 AU - Duarte, R. AU - Correia, F. AU - Arriaga, P. AU - Paiva, A. PY - 2023 SN - 2578-1863 DO - 10.1155/2023/4637678 UR - https://www.hindawi.com/journals/hbet/contents/ AB - Explainable artificial intelligence (XAI), known to produce explanations so that predictions from AI models can be understood, is commonly used to mitigate possible AI mistrust. The underlying premise is that the explanations of the XAI models enhance AI trust. However, such an increase may depend on many factors. This article examined how trust in an AI recommendation system is affected by the presence of explanations, the performance of the system, and the level of risk. Our experimental study, conducted with 215 participants, has shown that the presence of explanations increases AI trust, but only in certain conditions. AI trust was higher when explanations with feature importance were provided than with counterfactual explanations. Moreover, when the system performance is not guaranteed, the use of explanations seems to lead to an overreliance on the system. Lastly, system performance had a stronger impact on trust, compared to the effects of other factors (explanation and risk). ER -