TY - GEN
T1 - AlphaDAPR
T2 - 28th International Conference on Intelligent User Interfaces, IUI 2023
AU - Kim, Jiwon
AU - Kang, Jiwon
AU - Kim, Taeeun
AU - Song, Hayeon
AU - Han, Jinyoung
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/3/27
Y1 - 2023/3/27
N2 - Sketch-based drawing assessments in art therapy are widely used to understand individuals' cognitive and psychological states, such as cognitive impairment or mental disorders. Along with self-report measures based on a questionnaire, psychological drawing assessments can augment information about an individual psychological state. However, the interpretation of the drawing assessments requires much time and effort, especially in a large-scale group such as schools or companies, and depends on the experience of the art therapists. To address this issue, we propose an AI-based expert support system, AlphaDAPR, to support art therapists and psychologists in conducting a large-scale automatic drawing assessment. Our survey results with 64 art therapists showed that 64.06% of the participants indicated a willingness to use the proposed system. The results of structural equation modeling highlighted the importance of explainable AI embedded in the interface design to affect perceived usefulness, trust, satisfaction, and intention to use eventually. The interview results revealed that most of the art therapists show high levels of intention to use the proposed system while expressing some concerns about AI's possible limitations and threats as well. Discussion and implications are provided, stressing the importance of clear communication about the collaborative role of AI and users.
AB - Sketch-based drawing assessments in art therapy are widely used to understand individuals' cognitive and psychological states, such as cognitive impairment or mental disorders. Along with self-report measures based on a questionnaire, psychological drawing assessments can augment information about an individual psychological state. However, the interpretation of the drawing assessments requires much time and effort, especially in a large-scale group such as schools or companies, and depends on the experience of the art therapists. To address this issue, we propose an AI-based expert support system, AlphaDAPR, to support art therapists and psychologists in conducting a large-scale automatic drawing assessment. Our survey results with 64 art therapists showed that 64.06% of the participants indicated a willingness to use the proposed system. The results of structural equation modeling highlighted the importance of explainable AI embedded in the interface design to affect perceived usefulness, trust, satisfaction, and intention to use eventually. The interview results revealed that most of the art therapists show high levels of intention to use the proposed system while expressing some concerns about AI's possible limitations and threats as well. Discussion and implications are provided, stressing the importance of clear communication about the collaborative role of AI and users.
KW - AI
KW - Art therapy
KW - Draw-A-Person-in-the-Rain
KW - Drawing assessments
KW - Expert support system
KW - Explainable AI
UR - https://www.scopus.com/pages/publications/85152136206
U2 - 10.1145/3581641.3584087
DO - 10.1145/3581641.3584087
M3 - Conference contribution
AN - SCOPUS:85152136206
T3 - International Conference on Intelligent User Interfaces, Proceedings IUI
SP - 19
EP - 31
BT - IUI 2023 - Proceedings of the 28th International Conference on Intelligent User Interfaces
PB - Association for Computing Machinery
Y2 - 27 March 2023 through 31 March 2023
ER -