Exacerbating Market Power and Concentration
Major tech companies have also been the dominant players in developing new generative AI systems because training generative AI models requires massive swaths of data, computing power, and technical and financial resources.
ENTITY
1 - Human
INTENT
1 - Intentional
TIMING
3 - Other
Risk ID
mit531
Domain lineage
6. Socioeconomic and Environmental
6.1 > Power centralization and unfair distribution of benefits
Mitigation strategy
1. Implement robust and sector-specific competition policies, including antitrust measures and regulatory oversight, to prevent monopolistic practices concerning key inputs such as specialized compute capacity, high-quality training data, and proprietary model distribution channels. 2. Fund and incentivize research and development of computationally efficient AI architectures, such as Small Language Models (SLMs), and require the open-sourcing of foundational models and training methodologies developed with public resources to lower the financial and technical barriers to entry. 3. Establish national or multi-jurisdictional frameworks to mandate fair, non-discriminatory, and equitable access to high-demand, concentrated resources, specifically advanced semiconductor chips and cloud-based AI infrastructure, for academic, startup, and non-dominant enterprise users.