Compare AI against the adequate non-AI process before: What conclusion is best supported?
An adequate non-AI alternative and incomplete impact evidence make comparative assessment necessary before adoption.
The question
A research office proposes AI to screen grant applications. A transparent rules-based process already meets the required turnaround time, but reviewers say AI might identify nuanced merit more consistently. Evidence about fairness and added benefit is incomplete, and automation could affect funding access. What conclusion is best supported?
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- Use AI because nuanced merit may improve selection.A possible benefit does not establish that AI is necessary or that its uncertain impacts outweigh an adequate existing process.
- Pilot AI for one discipline using reviewer feedback alone.A limited pilot may generate insight, but reviewer feedback alone cannot compare impacts, fairness, and benefit against the existing alternative.
- Adopt rules-based screening and prohibit future AI evaluation.The evidence supports comparison before adoption, not a permanent conclusion that future AI assessment lacks value.
- Compare AI against the adequate non-AI process before adoption. ✓The existing alternative, uncertain incremental benefit, and potential access impacts require contextual comparison before selecting AI.
The trap
An existing adequate process changes the question from capability to demonstrated incremental value and impact. How to remember it
An adequate non-AI alternative and incomplete impact evidence make comparative assessment necessary before adoption.
How many of these would you get right?
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