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AI in Agriculture: What the Evidence Says and What It Misses
AI in agriculture is often assessed by one question: Does the model work?
But as Zeba Siddiqui (Consultant, Athena Infonomics) points out – is that the right question?
Drawing from a rapid review commissioned by Foreign, Commonwealth and Development Office, University of Birmingham, and International Initiative for Impact Evaluation (3ie), Zeba reflects on what the evidence around AI in agriculture is really telling us. While there’s growing momentum around precision agriculture, pest detection, and crop productivity, far less attention is being paid to poverty reduction, livelihoods, and who holds decision-making power.
If we’re serious about impact, we need to measure what truly matters, not just what’s easy to measure.
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