Global South Grapples with AI Regulation and Data Protection Challenges

Global South Lags in AI Regulation and Data Protection

The Global South is facing significant challenges in regulating artificial intelligence (AI) and protecting data privacy, as revealed at PrivacyNama 2024. Nicolas Grossman, project director of the Global Index on Responsible AI, highlighted that only 49% of nations in the Global South had legally enforceable frameworks for data protection concerning AI, compared to 83% in the Global North 1

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Enforcement Challenges and Economic Priorities

Professor Luca Belli of Fundação Getulio Vargas (FGV) Law School noted that while many Global South countries have general data protection laws, enforcement remains a critical issue. He emphasized that regulators in these countries are often under-resourced and may be reluctant to confront large tech companies 1

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Linh Tong, Deputy Director of CEPEW, pointed out that some countries, like Vietnam, are prioritizing economic development through AI over stringent regulation. This focus on becoming part of the global AI value chain has led to encouraging data use and sharing, potentially at the expense of personal data protection 1

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Non-Personal Data and AI Training Risks

The discussion at PrivacyNama 2024 also highlighted the overlooked risks associated with using non-personal data in AI training. Anwesha Sen, Session Chair for the Data Trusts, Non-Personal Data and AI panel, emphasized that the lack of regulations for data scraping poses significant risks, including potential copyright violations and re-identification of individuals 2

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Amol Kulkarni, Research Director at CUTS International, pointed out the ambiguity in defining personal and non-personal data, especially when large datasets are merged for AI training. This confusion raises concerns about deanonymization and potential misuse of data 2

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AI Sovereignty and Global Collaboration

The concept of AI sovereignty emerged as a key topic, with nations seeking to exert greater control over AI development within their borders. Nehaa Chaudhari, Session Chair for 'AI Sovereignty and Cross Border Data Flows,' noted that this manifests in efforts to develop infrastructure for AI and build localized training datasets 3

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Rostam Neuwirth, Head of the Department of Legal Studies at Macau University, argued that national AI initiatives and global collaboration are complementary rather than contradictory. He emphasized the need for both local efforts and international cooperation to address global challenges effectively 3

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Legitimate Interest vs. Consent in Data Processing

The challenges of obtaining user consent for data processing in AI applications were discussed, with some experts advocating for the use of 'legitimate interest' as an alternative legal basis. Beni Chugh, Head of Future of Finance at Dvara Research, argued that the consent framework puts an undue burden on users, especially those who are new to digital technologies or from low-income backgrounds 4

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Idriss Kechida, Global Data Protection Officer at OpenAI, described consent as a "blunt instrument" and suggested that legitimate interest could be a more refined and mature legal basis for data processing in AI development 4

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As the Global South continues to navigate the complex landscape of AI regulation and data protection, balancing innovation with privacy concerns remains a significant challenge. The discussions at PrivacyNama 2024 highlight the need for tailored approaches that consider the unique contexts and priorities of different regions while striving for global standards in AI governance.