A multidisciplinary group of experts will evaluate submissions based on the following equally weighted criteria and will recommend awardees for each phase.

In Phase 1, an expert review panel will score proposals according to the selection criteria. The proposals with the highest scores will advance to the multidisciplinary judging panel, composed of experts at the intersection of AI, climate, and nature. The judges will recommend up to 30 teams to be selected as Seed Grantees. The Bezos Earth Fund will determine the final slate of Seed Grantees, who will each receive $50,000 in funding and an invitation to move onto the next phase of the Grand Challenge.

In Phase 2, judges will evaluate submissions according to the Phase 2 selection criteria and recommend up to 15 awardees. The Bezos Earth Fund will confirm the final slate of awardees. After completing a Bezos Earth Fund grant agreement, each team will each receive up to $2 million to close the gap between concept and viability.

Phase 1

Impact

The extent to which the submission articulates a transformative vision for impact in its target climate or nature focus area.

Viability

The degree to which the submission considers the abilities of modern artificial intelligence and identifies practical opportunities to apply it, while also articulating potential resource gaps, risks, and constraints.

Suitability

The extent to which the submission addresses a problem that artificial intelligence is uniquely suited to solve.

Scalability

The degree to which the submission can be scaled and adapted to different global contexts and environments, multiplying impact.

Societal benefit

The extent to which the submission creates direct societal value, considers accessibility and equity for diverse stakeholders, and provides mitigation strategies against any potential risks or harms.

Phase 2

Impact

The extent to which the implementation plan identifies transformative and quantifiable outcomes for sustained impact in its target climate or nature focus area.

Viability

The degree to which the implementation plan recognizes and accounts for the requirements of modern artificial intelligence, incorporating the resources, expertise, and risk mitigation measures needed to execute the plan.

Suitability

The extent to which the implementation plan addresses a problem that artificial intelligence is uniquely suited to solve.

Scalability

The degree to which the implementation plan demonstrates how the solution will be scaled and adapted to global contexts and environments, multiplying impact.

Societal benefit

The extent to which the implementation plan creates direct societal value, considers accessibility and equity for diverse stakeholders, and provides mitigation strategies against any potential risks or harms.

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