Trust Conditions and Conditional Willingness to Use AI Legal Information in Bangladesh

Abstract A person can express willingness to use an artificial intelligence (AI) legal service under transparent conditions while remaining cautious about acting on its information. This cross-sectional study distinguishes conditional willingness, trust expectations and verification caution using 385 adult questionnaire records from Bangladesh. We report full response distributions, paired comparisons and exploratory adjusted models of willingness attributed to transparent explanations. The willingness statement was endorsed by 337 respondents (87.5%); trust conditional on clear sources was endorsed by 260 (67.5%) and trust conditional on qualified professional oversight by 266 (69.1%). Within respondents, willingness endorsement exceeded these two trust conditions by 20.0 and 18.4 percentage points, respectively (both Holm-adjusted p < 0.001). Of the 337 respondents who endorsed conditional willingness, 233 also endorsed the professional oversight condition. In the adjusted original-rating model, perceived access utility (b = 0.275, 95% CI 0.111 to 0.439) and verification caution (b = 0.154, 95% CI 0.060 to 0.248) were positively associated with conditional willingness (both adjusted p = 0.003). Neither association met the adjusted threshold when willingness was dichotomised. The findings distinguish openness to a transparent service from confidence in an answer or readiness to act on it. They motivate separate evaluation of source checking, professional escalation and service use. The study does not identify the causal effect of transparency or estimate actual adoption or national prevalence.