Building deployable AI for agriculture means adhering to data protection laws, avoiding algorithmic bias, and ensuring IP clarity. Learn how to safeguard your data pipelines, navigate Kenya’s Data Protection Act, and meet the judging standards for responsible innovation ahead of October's 48-hour build sprint.
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Deploying artificial intelligence in smallholder agriculture requires high technical standards and strict data ethics. From collecting farmer profiles to integrating public and cooperative datasets, innovators must design with privacy, transparent inference, and regulatory compliance from day one.
In this session, our experts unpack how to build legally compliant, trustworthy AI solutions that protect farmer data, respect IP, and align with national digital guidelines.
What We’ll Cover:
Who Should Attend:
Registered hackathon participants, software engineers, data scientists, agronomists, UI/UX designers, and tech founders preparing to build for GIW 2026
Data Scientist
AWS Authorized Instructor
Software Developer
GDG Lead
WTM Lead | Speakers Coordinator Lead
Cloud Lead
Technical Lead
Lead- Design and Creative
WTM Ambassador | Media and Communication Lead
Software Engineer
GDG
Logistics Management
Kisii University
Designer
GDG Kisii
Social Media
