Workshop
From Data to Action: Systems Thinking & AI Driving Green Transformation in Education and Agriculture
Bridging Two Worlds
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Students in an AI-for-agriculture program collaborated with farmers to measure soil moisture using sensors.
The collected data was applied in both classroom learning and real farming practices.
This is an example of a “system learning loop”: learn – act – feedback – improve.
Discussion
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What makes a system learning loop effective?
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How can we maintain the connection between schools and communities?
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If expanded to a regional scale, what elements are needed for system sustainability?
Suggestion
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Continuous connection among data, people, and real-world actions.
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Establish two-way feedback mechanisms and fair benefit sharing.
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Require open digital infrastructure, supportive policies, and a collaborative culture.
Homework
→ Propose one community project that combines AI and system thinking for local development.
