AI widening divide between the haves and have-nots: UN Special Envoy Amandeep Singh Gill

Key Concepts

• Increased Oil Demand: Driven by the energy needs of AI data centers.
• Energy Transition: Characterized as reinforcement rather than replacement of existing energy sources.
• AI Divide: The widening gap between those who benefit from AI and those who are left behind, both globally and within nations.
• AI Governance: The need for international cooperation and inclusive dialogue to shape the future of AI.
• AI Capacity Building: Investing in AI skills and infrastructure in developing nations to prevent them from being excluded.
• AI Regulation: The challenge of keeping pace with rapid scientific advancements and avoiding hasty, suboptimal choices.
• AI Augmentation: Viewing AI as a tool to enhance human capabilities rather than a replacement for human intelligence.

Energy Demand and the AI Revolution

The United Arab Emirates' energy minister anticipates a surge in oil demand for the upcoming year, primarily attributed to the substantial energy requirements of data centers supporting artificial intelligence (AI). This sentiment is echoed by the CEO of UAE oil giant Ednox, who, while acknowledging short-term volatility due to geopolitical factors, remains optimistic about long-term oil demand. Projections indicate that oil consumption will exceed 100 million barrels per day beyond 2040, with oil increasingly utilized not only for mobility but also for materials and petrochemicals. This complex energy landscape suggests an "energy transition" that involves reinforcement of existing sources rather than outright replacement.

The Evolving Energy Industry and Digitalization

Energy leaders convened in Abu Dhabi for the Antipek Energy Conference, highlighting a significant shift in the energy industry. The sector is increasingly defined by digital advancements, necessitating radical reorientations. This transformation was underscored by the attendance of the UN Special Envoy for Digital and Emerging Technologies, Amadiv Sing Singh Gil.

The AI Divide and its Implications

A primary concern raised by Amadiv Sing Singh Gil is the widening "AI divide," characterized by the concentration of wealth and technological power in a few hands and geographies. This leaves vast segments of the global population behind, potentially exacerbating existing inequalities. The risks associated with AI may disproportionately affect these same populations.

Exponential Growth in AI Energy Consumption

The energy requirements for AI are growing exponentially. By 2040, energy consumption by data centers is projected to quadruple. In some countries, these data centers are already consuming more power than households. This trend is expected to impact electricity bills and force governments and utilities to make difficult choices between allocating electricity for other industries versus the tech industry. This necessitates increased power generation, raising questions about the reliance on carbon-free energy versus fossil fuels and the potential reversal of progress made in addressing climate change.

Global Governance and AI

The United Nations is advocating for collective concern and action to prevent individual countries or blocs from implementing self-serving regulations. Progress has been made at the UN in governing AI for humanity, including the establishment of an international independent scientific panel on AI and an inclusive global dialogue on AI governance, ensuring all 193 member states have a voice. The UN is also focusing on the "AI divide" and measures to invest in AI capacity in the 90-200 countries most at risk of being excluded.

Inequality Beyond the Global North-South Divide

The AI divide is not solely a North-South issue. Within societies in the Global North, there is a risk of increased inequality due to rapid shifts in the job market, potentially leaving some individuals in a worse position. This is identified as a collective, shared problem across both the North and the South.

Navigating the AI Rush and Regulation

The current rush by many countries to adopt AI legislation, driven by the fear of being left behind, is seen as unhelpful. This "fear of missing out" can lead to hasty decisions, corner-cutting, and suboptimal choices. It is crucial for nations to "take a deep breath" and consider their specific contexts.

Strategic Choices for Nations

Countries need to make strategic decisions regarding AI development. This includes determining whether to develop their own large language models (LLMs) or leverage existing LLMs developed elsewhere through APIs or open-source options, which can then be fine-tuned on local datasets.

Investment in Talent and Use Cases

Investing in talent is paramount, encompassing AI literacy, AI development skills, and AI deployment skills, particularly for micro, small, and medium-sized enterprises (MSMEs). Retraining the workforce to collaborate effectively with AI tools and applications is essential. Furthermore, identifying and prioritizing the right use cases, such as in government services, citizen-facing services, agriculture, or health, is critical. Successful use cases can build public trust and provide investment signals for companies.

The Biggest Mistakes in AI Deployment

The most significant mistake in AI is a misunderstanding of what AI is, its capabilities, and its limitations. AI, which often approximates human functions, should be viewed as an augmentation of certain human powers. It is crucial not to confuse AI with the multifaceted creativity and intelligence of humans. AI should be deployed to enhance human power, skills, and intelligence, rather than being mistaken for the essence of human beings, which machines cannot replace.