Communications of the ACM
The U.S. Has AI Competition All Wrong
For all its geopolitical complexity, competition in artificial intelligence boils down to a simple technical triad: data, algorithms, and computing power.
Credit: Bart van Overbeeke/ASML/Reuters
The development of artificial intelligence was once a largely technical issue, confined to the halls of academia and the labs of the private sector. Today, it is an arena of geopolitical competition. The United States and China each invest billions every year in growing their AI industries, increasing the autonomy and power of futuristic weapons systems, and pushing the frontiers of possibility. Fears of an AI arms race between the two countries abound—and although the rhetoric often outpaces the technological reality, rising political tensions mean that both countries increasingly view AI as a zero-sum game.
For all its geopolitical complexity, AI competition boils down to a simple technical triad: data, algorithms, and computing power. The first two elements of the triad receive an enormous amount of policy attention. As the sole input to modern AI, data is often comparied to oil—a trope repeated everywhere from technology marketing materials to presidential primaries. Equally central to the policy discussion are algorithms, which enable AI systems to learn and interpret data. While it is important not to overstate its capability in these realms, China does well in both: its expansive government bureaucracy hoovers up massive amounts of data, and its tech firms have made notable strides in advanced AI algorithms.
From Foreign Affairs
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