Who is agricultural AI really working for?
Agricultural AI can exclude women, older farmers and people without smartphones. Evidence from East Africa shows how advisory services can be designed more inclusively.
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Journal
Notes from a changing field.
Research, field notes and open questions on how design, data and digital tools can support climate-smart agriculture.
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A growing record of what we are learning.
Follow via RSSWhy Malawi’s lean-season risk can rise after a better harvest
Malawi’s latest IPC analysis projects 2.6 million people in Crisis during the 2026/27 lean season. What the data means for earlier, locally useful action.
Read articleMalawi’s 2026/27 rainfall outlook: from probabilities to farm decisions
What Malawi’s official 2026/27 seasonal rainfall outlook says—and how to combine it with district forecasts, short-term updates and local knowledge.
Read articleDigital farm advice in Malawi: why local data and extension still matter
Why useful digital agriculture in Malawi depends on local evidence, offline access, trusted extension workers and a clear return for farmers.
Read articleGliricidia–maize agroforestry in Malawi: what long-term trials show
What long-running Malawi trials reveal about soil carbon, nutrients and water under gliricidia–maize intercropping—and why the results remain site-specific.
Read articleClimate-smart agriculture in Malawi: why it matters now
An evidence-based introduction to climate-smart agriculture in Malawi: the risks it addresses, the practices it includes and what responsible scaling requires.
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