As the U.S. seeks to limit China’s access to semiconductors and hinder their AI development, it will have unintended consequences on the global semiconductor supply chain that will hamper U.S. innovation and drive up costs across the chip industry.
IBM defines artificial intelligence as a system that “leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind”. At its core the field of artificial intelligence is the art of combining computer science and robust data sets to solve problems (IBM, 2004). Advanced AI systems can be applied to a multitude of problems and AI is woven into every aspect of our daily lives and nearly every facet of the global economy. Although AI has nearly unlimited uses and applications, it is becoming increasingly relevant within the national security sphere. Underscoring its importance in 2017, Vladimir Putin famously stated that “Artificial intelligence is the future… whoever becomes the leader in this sphere will become the ruler of the world” (Vincent, 2017). Recent developments in AI are proving one of the most cunning and vicious leaders of the 21st century correct and illustrate the need for the U.S. to address AI’s role as it engages in strategic competition with China (NSCAI, 2021).
Semiconductors are not only the lifeblood of the modern economy and digital world but the crucial hardware that AI systems develop and run on (Williams, 2021). The two leading state actors in this field, China, and the United States, are racing to out develop each other while begrudgingly recognizing the interdependent relationship they have in the development of semiconductor chips, the crucial hardware necessary for AI development and the basis of innovation and modern-day computing power (Miller, 2022).
This thesis explores the intersection of semiconductors and AI through a geopolitical lens and identifies the crucial player as U.S. semiconductor companies. Their dominant market share, enormous R&D budgets and global network of suppliers places them in the middle of the U.S.-China strategic competition and the ongoing global race towards rapid AI development and implementation.
Peter Connolly (PPS ’23) is a Public Policy Undergraduate at Duke University’s Sanford School of Public Policy. This content does not represent the official or unofficial views of the Sanford School, Polis, Duke University, or any entity or individual other than the author.
Additional Resources:
Peter Connolly (PPS '23): "Did Moore's Law Die with Gordon Moore?"
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