AI partnerships: The promise and perils
AI can be a force for good. But challenges include standardssetting, supply chain resilience, talent retention, and data policy
Aperiod that had been broadly described as engagement has come to an end,’ Kurt Campbell, the Indo-Pacific Coordinator at the United States (US) National Security Council, told a virtual audience in May on the subject of US-China relations. “The dominant paradigm is going to be competition.”
On several occasions, Campbell has highlighted that one of the major arenas of this competition will concern technology. This is increasingly reflected in US national security structures. Today, there is both a senior director and coordinator for technology and national security at the White House; the National Economic Council has briefed the cabinet on supply chain resilience; and the focus of department of defense policy reviews have been on emerging military technologies.
The subject of intensifying technology competition is also making its way into new US avenues for cooperation with partners, including India. This could take the form of bilateral cooperation, coordination at multilateral institutions, or through loose coalitions such as Quad. At the virtual summit in March of Quad, the four leaders (of India, Japan, Australia and the US) agreed, among other things, to establish a working group on critical and emerging technologies, which has already convened.
Artificial Intelligence (AI) has emerged as one technology of particular importance because of its role as an accelerator, its versatility, and its wide applicability. Driven by recent breakthroughs in machine learning made possible by plentiful data, cheap computing power, and accessible algorithms, AI is a good bellwether for the possibilities and challenges of international cooperation on emerging technologies. It is also incredibly lucrative, and could generate hundreds of billions of dollars in revenue over the coming decade.
There are some obvious areas of commonality and cooperation among India, the US, and other partners when it comes to AI. For example, there is a similar concern about developing AI in a broadly democratic setting. AI can be used in many positive ways — to foster innovation, increase efficiency, improve development, and enhance consumer experience. For India, AI deployment will be tied closely to inclusive growth and its development trajectory, with potentially positive implications for agriculture, health, and education, among other sectors.
But AI can also be used for a host of undesirable purposes — generating misinformation, criminal activity, and encroaching upon personal privacy. Quad countries and others — including in Europe and North America — generally seek partners amenable to broadly upholding a responsible, human-centric approach to AI.
Additionally, despite the nominally more nationalistic rhetoric (e.g. “build back better”, “atmanirbhar Bharat”), there is a fundamental recognition that international partnerships are valuable and necessary. AI development and deployment is inherently international in character.
Basic and applied research involves collaborations across universities, research centres, and countries. Data can be gathered more easily, a lot of development relies on open-source information, and funding for AI start-ups is a global enterprise. There is also a recognition that countries can learn from each other’s experiences and mistakes, and that the successful deployment of AI would serve as a model for others. India, for example, is one of the few developing countries large enough to marshal considerable resources for AI, in a manner that could be replicated, including in South Asia or Africa.
India and its partners also confront some similar challenges when it comes to the development and deployment of AI. One imperative involves nurturing, attracting, and retaining the requisite talent. According to Macro Polo’s Global AI Talent Tracker, 12% of elite AI researchers in the world received their undergraduate degrees from India, the most after the US (35%) and more than China (10%). Yet, very little top-tier AI research is being conducted in India (over 90% is taking place in the US, China, the European Union, Canada, and the UK).
Beyond talent, additional challenges lie in securing the necessary infrastructure; ensuring resilient supply chains, especially for components such as microprocessors; alignment on standards, governance, and procurement; and ensuring critical minerals and other raw materials required for the development of the necessary physical infrastructure.
Given that governments have only recently established AI policies, and, in some cases, are still formulating them, international cooperation is still very much a work in progress. More detailed efforts will be outlined in the coming months and years.
Nevertheless, the contours of cooperation are already discernible. Some areas are proving relatively easy, such as coordination in the setting of standards at the multilateral level, which is already underway. Other areas will prove more challenging. Supply-chain security and building resilience should theoretically be easier, given the political-level agreement on this issue. However, ensuring bureaucratic and regulatory harmonisation remains complicated. India and its partners may have the most trouble aligning their approaches to data — a particularly touchy subject at the moment — and, in the long-run, incentivising joint research and development.
The future looks bright for organic cooperation on AI — the demand is there and India and its partners all hold relative strengths. But critical decisions made in the near future could have transformative effects for international cooperation on AI, which, in turn, could decisively shape the contours of what some have described as the Fourth Industrial Revolution.