Antitrust solves disruptive innovation and US tech leadership better.

But the effects of such action are highly uncertain. Will a less concentrated tech sector comprised of slightly smaller firms fuel innovation and create openings for a new generation of tech companies? Or will reductions to scale significantly hurt leading tech firms’ ability to leverage the traditional building blocks of AI innovation—like computing power and data—into breakthroughs? The answers to these questions aren’t clear cut but offer a way to begin thinking about how antitrust enforcement could impact artificial intelligence innovation and national security more broadly.

Unlike some earlier national-security technologies, the commercial sector plays an outsize role in AI development. As a result, government access to both AI products and innovation hinges, in large part, on industry. While academia, private research labs, and AI start-ups offer important contributions to AI development, major American technology companies have traditionally led the field. Last year, Microsoft, Facebook, Amazon, Google, and Apple ranked among the ten largest recipients of U.S. artificial intelligence and machine learning (ML) patents.

Changes to the composition of America’s tech sector might boost net AI innovation. From 2013-2018, 90 percent of successful Silicon Valley AI start-ups were purchased by leading tech companies. This is a potentially worrisome trend for AI innovation. After all, incumbent firms and emerging companies can have very different incentives. Entrenched tech giants may be more focused on maintaining market share than disrupting markets altogether.

As Big Tech increasingly moves to acquire AI start-ups, individual firm dynamics also shift. Instead of “building for scale,” start-ups begin to “build for sale,” adopting a mentality that may be ill-suited for moonshot innovations. Would a company like DeepMind (now owned by Google parent-company Alphabet), for example, have developed AlphaGo—the ground-breaking computer program that became the first to beat a human player in Go—if the firm’s primary goal was to be acquired by a bigger player?

Antitrust action could shift these incentives and spur competition, potentially opening the door for new AI innovations—and for a new wave of AI companies. With their smaller statures, some of these firms might focus on more niche AI applications, including defense-related products, as start-ups like Anduril and ShieldAI have done. Today’s tech giants have every financial incentive to cater to foreign markets and the average consumer, not to the U.S. federal government. Indeed, with its global user-base, it is hard to imagine Google tailoring its AI innovation decisions to U.S. defense needs. The same may not hold within an AI ecosystem where some companies built, for example, in the mold of Palantir (a data-analytics company with clear national-security applications) consider government their primary customer and subsequently concentrate on its demands.