Satoru Shibuya

Satoru Shibuya

This study investigates deep self-disclosure toward generative AI by examining perceived non-humanity and structural similarity as psychological factors beyond anthropomorphism. Perceived non-humanity may reduce evaluation apprehension, whereas structural similarity refers to the perceived logical alignment between a user's thinking and AI responses. Using cross-sectional survey data from 2,400 participants collected in 2025, this study analyzed associations with both the occurrence and depth of self-disclosure. Logistic regression indicated that the group high in both perceptions (Segment D) showed a significantly higher likelihood of disclosure than the baseline group (Segment A; OR = 11.35). ANOVA further showed significant between-group differences in disclosure depth. The findings suggest that trust-related behavior in deep self-disclosure may involve factors other than anthropomorphic perception. Because the study is exploratory and based on self-reported survey data, the results should be interpreted as associative rather than causal, and future longitudinal or experimental research is needed.

Kenji Saito, Rei Tajika, Satoru Shibuya et al.

This paper reports a survey of generative AI use among 83 MBA thesis students in Japan (target population 230; 36.1% response rate), conducted after thesis examiner evaluation. AI use was nearly universal: 95.2% reported at least some use and 77.1% heavy use. Students engaged AI across the full research-writing workflow - literature review, drafting, and consultation when stuck - reporting benefits centered on clearer argument and structure (82.3%), better revision quality (73.4%), and faster writing (70.9%), with a mean perceived quality improvement of 6.27 out of 7. Concerns about output accuracy (75.9%) and citation handling persisted alongside these gains. Among respondents who rated GAMER PAT, a research-specialized agent, against other AI, preferences significantly favored it for inquiry deepening and structural organization (both p < 0.05, exact binomial). A preliminary qualitative analysis of follow-up interviews further reveals active epistemic vigilance strategies and differentiated tool use across thesis phases. The central implication is not adoption itself but a shift in the educational challenge toward verification, source governance, and AI tool design - with GAMER PAT offering preliminary evidence that research-specialized scaffolding matters.