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6. Socioeconomic and Environmental3 - Other

Within-country issues: domestic inequality

Our next problem is the fact that the current AI workforce does not evenly represent world demographics. Men from the US and China, working in the US, for US corporations, are disproportionately highly represented [402, 157, 170, 534]. Realizing the full promise of AI requires that people throughout the world and from all social strata are able to use AI and participate in its design and governance. Solving this problem requires addressing unequal access to AI both within countries and across countries.

Source: MIT AI Risk Repositorymit884

ENTITY

3 - Other

INTENT

3 - Other

TIMING

3 - Other

Risk ID

mit884

Domain lineage

6. Socioeconomic and Environmental

262 mapped risks

6.1 > Power centralization and unfair distribution of benefits

Mitigation strategy

1. Prioritize strategic investment in constructing and maintaining demographically representative AI development and research teams to proactively embed pluralistic perspectives and values into the architecture of AI systems. 2. Develop and implement comprehensive, inclusive AI literacy and skills training programs targeting underrepresented communities and regions (Global AI Majority) to broaden access to, and meaningful participation in, AI's economic and societal benefits. 3. Establish robust regulatory and governance frameworks that enforce algorithmic transparency and accountability, specifically mandating the auditing of datasets for representational bias and the integration of fairness metrics into the AI system design lifecycle.