Regional Capacity: Coordinated Innovation

Regional Capacity: Coordinated Innovation

Innovation capacity determines whether Africa develops indigenous AI capabilities or remains dependent on imported systems. These proposals create infrastructure for innovation that leverages regional coordination and diversity.

Coordinated Response for AI

Innovation capacity determines whether Africa develops indigenous AI capabilities or remains dependent on imported systems. These proposals create infrastructure for innovation that leverages regional coordination and diversity. Coordinated research programs¹ are particularly important in African contexts, where fragmented funding, small research teams, and uneven institutional capacity make it difficult to sustain long-horizon, multi-country projects without deliberate orchestration.

A-Labs: Applied Innovation Zones

Summary Multi-national innovation zones combining compute, manufacturing, and renewable infrastructure.

Description Each zone specializes (agriculture, health, finance, energy) with open-access policies requiring innovations be deployable across Africa. Achieves economies of scale impossible for individual nations while distributing regional benefits.²

Justification Distributed infrastructure prevents concentration while enabling critical mass; specialization grounds AI in concrete problems.

B-Labs: Basic Research for Moonshots

Summary High-risk, high-reward basic research funding for transformative AI breakthroughs.

Description 5-7 year funding horizons for fundamental questions (novel architectures, learning theory, AI cognition) without predetermined applications. Accepts high failure rates as intrinsic to breakthrough research.³

Justification Transformative innovations emerge from exploration, not incremental improvement. Provides institutional space for intellectual risk-taking that applied research cultures systematically discourage.

C-Labs: Cross-National Consortia

Summary Distributed research networks linking multiple African universities with international partners.

Description Each consortium addresses major challenges requiring sustained effort (multilingual NLP, disease surveillance, climate adaptation). Governance ensures African intellectual leadership and equitable benefit distribution.⁴

Justification Pools fragmented capacity while maintaining distributed participation. Avoids asymmetric partnerships that extract value without building enduring capacity.

Diffusion Labs: Field-Testing & Evaluation

Summary Rigorous empirical evaluation of AI deployments across African contexts.

Description Conducts randomized trials, implementation science, and harm detection for AI systems in education, agriculture, healthcare. Partners with governments to build evaluation into deployment from inception.⁵

Justification Most AI policy proceeds on untested assumptions. Systematic evaluation positions African institutions as knowledge producers while protecting populations from ineffective or harmful systems.

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