The global landscape of technological advancement is increasingly shaped by the race for dominance in Artificial Intelligence (AI). The United States and China are at the forefront of this competition, vying for supremacy in enterprise artificial intelligence (AI) development and application.
For many years I have been monitoring this arms race and I recognize that each has its unique advantages. But, what has struck me recently is the increasing role private and public business has in this intriguing rivalry.
The Race for Advancement
The United States has a long history of innovation in AI, with pioneering research institutions like MIT, Stanford, and Silicon Valley driving advancements in the field, supported by tech giants who continue to acquire AI startups and invest heavily in research labs. On the flip side of the coin, China’s vast population and data-rich environment provide a unique advantage for AI development and companies like Huawei, Alibaba, and Tencent are expanding their AI capabilities globally, challenging US dominance in key markets.
China has a clear goal: “to seize major strategic opportunities for the development of artificial intelligence, construct the first-mover advantage of artificial intelligence development in our country,” and “lead the world in artificial intelligence in 13-and-a-half years”. In China, AI has received the commensurate attention, investment, and regulatory landscape to succeed. That last part, the regulatory element, is important. If the United States insists on adopting a regulatory framework that slows the adoption of AI in favor of traditional jobs and industries, then it will be at a material disadvantage. This is because the Chinese government is actively investing in AI startups from chips to software, but it is also actively creating AI environments and infrastructure conducive to the development of AI.
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Command and Financial Success
However, the real challenge for the United States, and the wider Western world, in maintaining its leadership position is one of profit. By that I mean it has been a private industry that has driven innovation and expansion in AI and as Milton Freedman argued, the only social responsibility of a business is to maximize profits.
Here lies the problem.
If the West is to maintain leadership, then private industry must monetize any activities associated with the development of AI. Shareholder expectations further exacerbate this. If you are a privately held company, investors expect a return and a well-monetized exit at some point. Previously in the private sector, investors would look for and expect growth at nearly any cost.
Today that landscape has changed and while investors are expecting growth, it is now profitable growth that they desire. The same is the case in the publicly traded world where shareholders are expecting that same profitable growth, now in the form of reoccurring revenues. Meanwhile, China can continue to make investments in this technology, with no expectation except to become the world’s leader.
The Benefits of Private Sector Investment
Given this background, you might think that I am down on the prospect of the next level of innovation or breakthrough in AI coming from the Western world. However, that couldn’t be further from how I feel about this issue. I am more bullish than ever on the advances of this technology being driven by the private sector.
It is well demonstrated that the Big Six tech companies in the United States: Alphabet (Google), Amazon, Apple, Meta, IBM, and Microsoft continue to invest in and produce advances. If we use the investment community (Private Equity, Venture Capital) as a barometer for interest and excitement in this space, then according to Crunchbase there was nearly $50 b****** of AI and AI-related investment in 2023. And that’s during a year that all other investment sectors were down. Just look at Microsoft’s reported $10 b****** investment in OpenAI and as Crunchbase reported there have been more than 70 rounds of $100 million or more invested in startups.
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The Significance of AI
One of the main reasons for my enthusiasm is that a lot of the advances in Artificial Intelligence have come from areas where AI is best positioned to make significant impacts, specifically the field of staff augmentation. Meaning to help make someone better, faster, and more efficient at what they do. It is getting through trillions of records of disparate information in seconds to easily connect nonobvious relationships, amplifying weak signals and assisting what might be a more junior resource with institutional memory and skills, thus making them more senior.
An often overlooked but critical component of AI is that of justification. This goes beyond transparency and gets at what the algorithm is doing on an atomic level and in a way that is easily understood by the user community. This is far more important in a Western democracy – where companies have to transparently explain their actions as governed by legal norms, such as not discriminating against a particular class of people. Transparency in AI is a regulatory and policy requirement in Western democracies. Performance has to take a back seat to “explainability.” If your algorithm is taking race or s** into consideration, that is generally illegal – also justification becomes even more essential if the technology is involved in any type of kinetic action.
China doesn’t have the same protections so they don’t have the same need for “explainability.” Over time we expect China to see the utility in transparency, but for now, the expectation is that they value performance over the ability to understand a model at an atomic level.
Conclusion
Business leadership in the United States and China is at the forefront of the AI arms race, driving innovation, shaping strategic priorities, and influencing global outcomes. As business leaders in both countries continue to invest in AI research, development, and commercialization efforts, the world watches closely, recognizing the profound impact of their decisions on the future of technology, society, and international relations.
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