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A United Nations scientific panel released a preliminary report stating that uneven AI adoption could increase disparities between countries. The document offers guidance on infrastructure, literacy, and safety measures while noting concentration of capabilities in a few nations.
A United Nations scientific panel released a preliminary report stating that uneven development of artificial intelligence could increase global inequality. The document proposes a shared framework for responsible AI use as adoption and investment accelerate at different rates across regions.
The report states that access to AI tools alone does not produce equal benefit. Countries relying on foreign models, cloud infrastructure, and data pipelines may gain access while losing practical control over standards, safeguards, and local fit.
Current adoption patterns More than a billion people now use AI weekly, yet adoption across the global south lags behind the global north. The United States and China lead in development of leading AI models and investment in compute infrastructure.
The panel noted that concentration of AI capabilities in a small number of firms and countries could enable authoritarian capture and undermine democratic accountability. It advised countries lagging in development to consider investment in computing and data infrastructure.
Risks and recommendations The report described risks including use of AI by bad actors for fraud and election influence, alongside opportunities in agriculture and education. It recommended developing local data centers, improving AI literacy in schools and the workforce, building safety institutes, and creating strategies to combat disinformation.
The panel also noted environmental costs of data centers, including large energy and water consumption and potential greenhouse gas emissions. Most countries lack technical expertise to assess frontier models or participate in their governance, the report stated.
Differences in language and internet access compound the divide. Generative AI tools perform well in English and other widely used languages, while most languages are excluded or show much lower performance. The report cited an example of machine translation of Tigrinya that mixed up smallpox with syphilis and the phrase about intravenous antibiotics with one about insecticides.
More than 2 billion people remain completely offline, according to the International Telecommunication Union.
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