Trust in AI is never one-size-fits-all, but instead depends heavily on the specific task, context, and level of risk involved. In this new tutorial, learn how scientists calibrate trust in scienceOS depending on the task at hand: from low-risk activities like literature searching and summarizing papers to higher-stakes uses such as drafting research reports.
Drawing on an internal survey with 53 scienceOS users conducted between November 2025 and January 2026, the article shows that trust and perceived risk vary across scientific workflows, with some tasks inspiring broad trust and others remaining highly subjective. It also explains why researchers should evaluate AI tools task by task and be transparent about AI’s role in their work.
Read the full tutorial: How to calibrate trust in AI effectively.
