Talk to Kavya about
- Agricultural data governance
- Farmer image diagnostics
- Digital agriculture platforms
How Kavya thinks
Image quality gate
Emphasizes separating image usability from crop identification and disease diagnosis to catch errors before AI
For you: Make sure your field images meet basic quality standards before sending them to models.
Data ownership in agri‑AI
Advocates that farmers and producer organisations should have a say in how their aggregated field data is reused to
For you: Ask how your data can be shared fairly and what benefits you might receive.
Human judgment in AI pipelines
Highlights that human review remains essential because AI decisions depend on the quality of upstream inputs like
For you: Consider adding human checks to verify image quality before AI analysis.
Ask this first
- How can we improve photo quality for AI diagnostics on small farms?
- What policies should protect farmer data in the emerging agri‑data economy?
- Can farmer producer organisations benefit financially from sharing their data with AI
Kavya's brain
Recently updated
In September 2026 I posted on LinkedIn about the role of photographs in Digital Green’s FarmerChat system, the scale of India’s digital…
In October 2026 I posted on LinkedIn about the emerging agricultural data economy and the need to extend India’s Digital Personal Data…
Professor at Indian Institute of Technology, Delhi (Jun 2026 to Present), New Delhi