Artificial Intelligence (AI) and Machine Learning (ML) are being embraced by greater numbers of individuals, businesses, and governments as rising efficiency and productivity are permitting exponential growth in certain sectors of the global economy. However, the gap in efficiency and productivity between those sectors and businesses benefitting from AI and ML versus those that have not is also growing exponentially. This risks leaving those at the bottom further and further behind with less and less chance of catching up with the leaders.
Most countries have only just begun to think seriously about their own AI future, with the majority of the world’s larger economies having only announced their own AI initiatives in 2017 and 2018.
The others must contemplate a future in which technological, economic, and military supremacy becomes the domain of those few countries with the deepest pockets, the best AI-oriented talent, and a magnitude of state resources that can be directed toward achieving AI supremacy.
The implications of having a small handful of countries controlling cutting-edge AI in the future are profound. On one hand, these technologically advanced countries could become the de facto guardians of AI, ensuring that significant resources are devoted to its development on a long-term basis. It is also certain that leading companies in these countries will achieve and maintain an even more noteworthy lead in the global economic arena, granting them a substantial competitive advantage. The militaries of these countries would also almost certainly become primary beneficiaries of the AI technologies of the future, spurring a global race for superior autonomous weaponry and propelling the world toward dangerous new means of waging war.
The familiar economic model of a single dominant economic pole, a primary technology, and a leading system of governance is slowly being replaced by multipolarity. Companies must increasingly address a plethora of paradigms, technologies, and governance rules. Data highways are becoming the new shipping routes. Cloud storage is gradually taking the place of shipping containers and warehouses. Decentralization and digitization are likewise replacing conventional means of communicating and transacting.
New global economic flows, driven by the exponential progress of silicon, are already creating massive disruptions in economies throughout the world. Online platforms are becoming more important than physical products. For example, the biggest currency repository in the world is driven by cryptocurrencies and has no buildings or physical safes. All are driven by software, which is based on knowledge and processes captured by automation. The globally optimized value chain‒a familiar feature of the current phase of globalization‒will give way to value chains that blend digital technology with older low-cost technologies, allow greater integration across products and services, and leverage the growth of independent global platforms for the exchange of goods and services.
In the era of ML, the greatest near-term challenge we face is how to transition from the current economic model–driven by conventional means of manufacturing and fossil fuels—into a new model driven by technological achievement that was, until recently, merely the realm of science fiction. How will we transition from our collective familiarity and comfort level with tangible, physical goods to a world dominated by what cannot necessarily be seen or felt? We are already transitioning into the cyber world, where virtual reality is not only upon us but is sought after by many of us. We are drawn to this bold new world because it tantalizes us with possibilities. The AI world that awaits us will do much the same.
Conventional wisdom suggests that AI will continue to benefit higher-skilled workers with a greater degree of flexibility, creativity, and strong problem-solving skills, but it is certainly possible – and even likely –that AI-powered robots could increasingly displace highly educated and skilled professionals, such as doctors, architects, and even computer programmers.
Much more thought and research needs to be devoted to exploring the linkages between the technology revolution and other important global trends, including demographic changes such as ageing and migration, climate change, and sustainable development. Many of these topics have either not even been broached yet or have only begun to be the subject of meaningful discussion in global fora.
While it seems clear that the growing ability of AI to autonomously solve complex problems could fundamentally reshape our economies and societies, the impact AI may have on a whole host of issues will remain unknown for many years to come. Even when answers appear to be coming into view, AI is akin to an amoeba that is in a constant state of metamorphosis, forever changing its shape and adjusting to its surroundings.
While the implications of the AI revolution on global order have only begun to be contemplated, it is not hard to imagine a future in which power, resources, and technology become even more concentrated than they already are. The wars of the future may not merely involve land, natural resources, and populations, but may determine the future course of the human race. Rather than serving to flatten the degree of global equality, an AI-dominated future could well result in the greatest concentration of resources and power the world has ever known.
The world cannot afford to simply rely on nature to take its course, or for the world’s governments and corporations to address critical issues associated with governance, regulation, and rule of law regarding AI when it might be deemed convenient to them. The multilateral system has an important role to play in helping to steer the future course of new global economy. It is therefore incumbent that multilateral institutions address how best the craft, and control, our collective AI future through enhanced dialogue, resource allocation, and action.
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This article has been prepared by Daniel Wagner as a contributor to AI & Global Governance. The opinions expressed in this article are those of the author and do not necessarily reflect those of the Centre for Policy Research, United Nations University, or its partners.