Design students report low trust in GenAI outputs and systematically modify and verify them, with inaccuracy the main deterrent¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? 65% of respondents indicate they do not trust GenAI outputs, and 85% indicate they systematically modify what GenAI produces to suit their needs. → Stefana Broadbent 2026 q2 i? Fear of inaccuracy is the main discouragement from using GenAI, with 70% of respondents highly concerned about inaccuracy. → Stefana Broadbent 2026 (2)

Evidence¶

Stefana Broadbent 2026¶

Stefana Broadbent. (2026). A study of GenAI usage by Design Students: Analysis of Survey Results and Journals of AI practices at the Politecnico di Milano in 2025/2026. Department of Design, Politecnico di Milano. https://arxiv.org/abs/2607.17094 doi:10.48550/arxiv.2607.17094

q2 · i? · associational · r2

Survey attitude items (n=202). Trust item: 27% strongly disagree and 36% somewhat disagree that they trust what GenAI generates; the editing item shows 42% most of the time and 44% always changing outputs.

"the level of trust in the outputs is very low as 65% of the responsdents indicate that they do not trust the outputs. And 85% of respondents indicate that they systematically modify what GenAI produces as output to suit their needs."

Stefana Broadbent 2026 (2)¶

Stefana Broadbent. (2026). A study of GenAI usage by Design Students: Analysis of Survey Results and Journals of AI practices at the Politecnico di Milano in 2025/2026. Department of Design, Politecnico di Milano. https://arxiv.org/abs/2607.17094

q2 · i? · associational · r2

Discouragement item (n=219 responses). The inaccuracy reason was rated 'a lot' by 36.9% and 'a great deal' by 33.8% of respondents, the highest-rated deterrent in the table.

"70% of the respondents are highly concerned about inaccuracy."

Discussion¶

Related Claims¶

• Most design students at Politecnico di Milano use GenAI tools daily or weekly for academic purposes — related
• Limited output accuracy and over-reliance are the most pressing challenges Chinese HSS students report in GenAI use, alongside strong ethical concern — a broader claim this one bears on
• GenAI use involves substantial hidden labor of prompting, verification, and correction that remains invisible in productivity evaluation — related
• Students report negative experiences with ChatGPT including inaccurate outputs, lack of emotional connection, and risk of overreliance, which constrain competence — a broader claim this one bears on
• Students remained cautious about relying on GenAI throughout the creative process, citing imperfect outputs and perceived loss of ownership — a broader claim this one bears on
• Low comment rewriting does not imply a smooth process: students describe the main effort as verifying generated code rather than revising prompts — related
• Most students reported no change in study habits, but students who adapted their study strategies rated GenAI-evaluation assignments as significantly more helpful — related
• Students use self-initiated strategies of verification, skill improvement, post-editing, pre-editing and reliance management to cope with GenAI challenges — related