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Trust Conditions and Regulatory Protection in AI Based Agricultural Information in Bangladesh

Year: 2026
Type: preprint
Study design: Observational Study
Abstract: AI-supported agricultural information may provide useful guidance while raising concerns about local suitability, accountability and oversight. This study examines stated trust conditions and perceptions of regulatory protection in a Bangladesh survey. The 385 adult, AI-aware records comprise law students, graduates, legal professionals and other respondents; 60 report a location classified as upazila or rural. The file does not identify farmers or establish that respondents use agricultural AI, so findings concern a mixed sample rather than representative rural users. The analysis retains separate questionnaire items and compares paired endorsement of statements on source/provider clarity, regulatory oversight and accountability. It also explores correlations between AI awareness items and two trust-related statements. Of 385 respondents, 310 (80.5%) agreed that clear sources and a responsible provider would increase trust, 255 (66.2%) agreed that regulatory oversight can increase confidence, and 317 (82.3%) agreed that strong accountability increases willingness to use agricultural AI. Source/provider clarity exceeded oversight endorsement by 14.3 percentage points; 210 respondents endorsed both statements. These are differently worded hypothetical propositions, so their contrast is not a ranking of interventions or evidence of causal effects. Associations between awareness and trust conditions were small and do not establish that training changes reliance. The study contributes an item-level distinction between provider transparency, institutional oversight, local adaptation and accountability, and proposes a future design that evaluates specific advisory systems with actual agricultural users.
DOI: 10.21203/rs.3.rs-11704076/v1
Language: English
Open Access status: green
OpenAlex ID: W7225885769
Cites: 3
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