From the course: The AI Equity Imperative: Building a More Inclusive Future with AI

Regional disparities in AI development

From the course: The AI Equity Imperative: Building a More Inclusive Future with AI

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Regional disparities in AI development

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- Regional disparities in AI research, development, and innovation impact the ability of AI systems to serve a diverse range of cultures, languages, and even values. Recognizing these imbalances is crucial to begin developing solutions to push for equitable AI. Globally, AI development is centralized in countries such as the United States, China, Canada, and the United Kingdom, as well as other countries in the European Union, including France and Germany. This results in a number of countries in the global majority, also referred to as the Global South, being significantly underrepresented in AI development. This phenomenon has led to what can be characterized as the AI Divide, where unequal distributions in computing power, skilled AI talent, investments in AI startups, and access to datasets benefit wealthier countries, large tech companies, and prestigious academic institutions. Aside from China, global majority countries rank low in their respective concentration and production of AI talent. These numbers rapidly diminish when considering the concentration of top-tier researchers, researchers who publish at prominent AI conferences. They're primarily situated within the United States and China. These disparities in skill talent impact the ability of researchers from the global majority to significantly develop AI models and publish research in top-tier venues. African researchers only contribute 2% of all scientific outputs in research fields, and this is expected to be much less for AI research. Work from the Data Provenance Initiative finds extreme disparities in a global representation in datasets, with less than 0.2% coming from Africa and South America. While research published in the Harvard Business Review shows a growing number of AI talent hotspots in cities like Bangalore, Sao Paulo, Johannesburg, Nairobi, Mexico City, Bangkok, and Lagos, many of these researchers tend to migrate to countries like the US, UK, and Canada, exacerbating brain drain. The introduction of generative AI tools like ChatGPT has driven a worldwide interest in adopting and developing AI-enabled solutions. However, this interest is still far from being reality for countries experiencing deficiencies in internet and telecommunications infrastructure and educational gaps, which AI cannot solely address. These issues highlight a need for greater investment by global majority governments and local AI ecosystems, along with expanded efforts to accelerate philanthropic and private sector partnerships. However, to ensure that AI doesn't divert attention away from addressing basic socioeconomic development challenges in domains like healthcare, education, and infrastructure, global majority governments must balance their respective interest and leveraging AI with the realities and needs of their local populations.

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