An M&E time machine: Using AI to measure changes in a system across a time period on features which only emerge during it.

Deposited on Figshare in September 2026.</p><p dir="ltr">People involved in project monitoring and evaluation of complex projects are familiar with what we call the ”time machine” problem: the things we want to measure (drivers, outcomes, intervening factors) may emerge and change unpredictably during a project’s lifespan and so cannot be fully specified until project end: but we need to know about them at baseline so we can design appropriate measurement instruments for tracking change.

We demonstrate a novel workflow to help solve this problem which uses an AI-controlled chatbot to interview respondents, and then uses AI to code the transcripts and identify ”causal links” where stakeholders said that one thing influences another. We analyse the resulting causal information for differences across time: tracking evidence for emerging trends on emerging variables. The approach is reproducible, scalable and cost-effective.