Qiurui Wang

The surge of Artificial Intelligence (AI) for automatic decision-making raises concerns about transparency and interpretability of AI models. Explainable AI (XAI) addresses this by providing insights into AI predictions. Despite the availability of various methods for explaining decisions based on tabular data, there is no consensus on their effectiveness for different types of users. This paper introduces a novel XAI method, the Visual Map, and presents a human-grounded evaluation study comparing it with three common XAI methods. In an online experiment (N = 49), participants with either high or low AI-literacy evaluated all four methods in terms of explanation satisfaction, cognitive load, and overall evaluation in the same classification task environment. High AI-literacy participants were largely indifferent to the four methods, whereas low AI-literacy participants favoured the visual map, perceiving it as the least cognitively demanding. Our findings contribute to the evaluation and development of XAI methods for different types of end-users.

The fast-paced life of contemporary society increases people's psychological stress, and a piece of creative digital art may help relieve the stress. The interactivity and dynamics of digital art bring different experiences to us. This article sought to determine if the dynamic digital art image transfer process with different music would influence the stress state. The stimuli were the 4 pieces of congruent audio-visual material to test which type of video has a stress-relieving effect. 100 participants were invited and divided into 5 groups for the experiment. The Trier Social Stress Test experiment was used to stimulate the stress state of the participants, and then 4 groups were shown videos of four emotional types: joy, anger, sadness and fear. The fifth group was the control group. The changes in stress state before and after the test were measured by the State-Trait Anxiety Inventory Questionnaire. The study found that happy and sad videos were more effective in relieving stress. The insights from this work could provide input to the design of digital art in emotion intervention and stress management.