With support from the Atlantic Council’s GeoTech Center, this initiative helps farmers and suppliers in food insecure regions feed more people, quickly, with the following guiding tenets.
- Community centered: Local experts make the key decisions, and Kijani-AI provides resources. Expertise, technology, and equipment is shared from farmer to farmer
- Data driven: Providing data trusts and AI innovations will enable countries with hungry populations to increase food yields, expand cultivatable land, and make distribution more efficient.
- Sustainably focused: By incorporating sustainable agriculture and conservation principles into AI- and data-driven systems, Kijani-AI promotes a more efficient, longer lasting, and less wasteful food system.
- Employ high-resolution satellite and drone imaging to capture and share soil conditions and vegetation cover in real time
- Encourage precise application of fertilizer, herbicides and pesticides to minimize waste and maximize environmental sustainability
- Educate on the use of automated tractors and sprayers to increase overall efficiency and productivity
- Ensure small farms reap the benefits of precision agriculture, by motivating large farms to help them by providing technical expertise, sharing equipment and other technical resources
- Develop an open source, precision agricultural data model for farmers in developing countries
- Encourage both small and large farms to have a huge positive impact on the environment – proportionate to their size – by promoting green, sustainable farming practices and developing innovative wildlife conservation techniques
- Locals lead
Kijani-AI provides resources. It does not make local decisions about farming or food distribution. Local technology experts play a key role in all tech efforts, augmented by international companies, scientists, engineers, and business leaders.
- Scale matters
Kijani-AI works top-down while also wanting to empower the edge, focusing on large-scale farms first because these farms can have the greatest immediate impact on food supply. Kijani-AI requires that the farms it supports have a Community Responsibility Program (CRP) where initiatives that share information, expertise and equipment with neighboring farms are favored.
- Data drives
Data collection, curation and application is central to Kijani-AI. All data efforts focus on enable farming operations in countries with hungry populations to increase food yields, expand cultivatable land and make food distribution more efficient.
- Sensemaking together
Today’s agriculture challenges cannot be met by single farming operations acting alone as we must make sense together across different systems and activities globally. Kijani-AI facilitates the exchange of data, methods resources, and best practices among large-scale farming operations, and ultimately with farming operations of all sizes, according to locally generated trust standards.
- Trust builds bridges
Because the latest autonomous tech systems require great stores of data, it is now in the interest of all agricultural operators to pool data—with appropriate trust safeguards—to produce robust, AI-ready data sets. Hunger is not a short-term problem. For arable land to produce food year after year, it must be part of a healthy ecosystem, and must constantly restore its basic elements of soil, water, and organic life.
- Sustainability through precision
Data-driven systems, particularly when coupled with AI vision and self-learning, can enable agriculture operations to become much more efficient. Benefits include waste reduction (in many areas); improved weeding and plant thinning; early warnings about pests, disease, weather effects and soil conditions; and improved synchronization between producers and markets.