Considering the Endless Frontier Act

by Sebastian Benthall

As a scientist/research engineer, I am pretty excited about the Endless Frontier Act. Nothing would make my life easier than a big new pile of government money for basic research and technological prototypes awarded to people with PhDs. I’m absolutely all for it and applaud the bipartisan coalition moving it forward.

I am somewhat concerned, however, that the motivation for it is the U.S.’s fear of technological inferiority with respect to China. I’ll take the statement of Dr. Reif, President of MIT, at face value, which is probably foolish given the political acumen and moral flexibility of academic administrators. But look at this:

The COVID-19 pandemic is intensifying U.S. concerns about China’s technological strength. Unfortunately, much of the resulting policy debate has centered on ways to limit China’s capacities — when what we need most is a systematic approach to strengthening our own.

Very straightforward. This is what it’s about. Ok. I get it. You have to sell it to the Trump administration. It’s a slam dunk. But then why write this:

The aim of the new directorate is to support fundamental scientific research — with specific goals in mind. This is not about solving incremental technical problems. As one example, in artificial intelligence, the focus would not be on further refining current algorithms, but rather on developing profoundly new approaches that would enable machines to “learn” using much smaller data sets — a fundamental advance that would eliminate the need to access immense data sets, an area where China holds an immense advantage. Success in this work would have a double benefit: seeding economic benefits for the U.S. while reducing the pressure to weaken privacy and civil liberties in pursuit of more “training” data.

This sounds totally dubious to me. There are well known mathematical theorems addressing why learning without data is impossible. The troublesome fact nodded to is that is because of the political economy of China, it is possible to collect “immense data sets”–specifically about people–without civil liberties issues getting in the way. This presumes that the civil liberties problem with AI is the collection of data from data subjects, not the use of machine learning on those data subjects. But even if you could magically learn about data subjects without collecting data from them, you wouldn’t bypass the civil liberties concerns. Rather, you would have a nightmare world where even sans data collection you could act with godly foresight in one’s interventions on polity. This is a weird fantasy and I’m pretty sure the only reason it’s written this way is to sell the idea superficially to uncritical readers trying to reconcile the various narratives around U.S., technology, and foreign policy which are incoherent.

What it’s really all about, of course, is neoliberalism. Dr. Reif is not shy about this:

The bill would also encourage universities to experiment with new ways to help accelerate the process of bringing innovative ideas to the marketplace, either via established companies or startups. At MIT we started The Engine, an independent entity that provides private-sector funding, work space and technical assistance to start-ups that are developing technologies with enormous potential but that require more extensive technical development than typical VCs will fund, from fusion energy to a fast, inexpensive test for COVID-19. Other models may suit other institutions — but the nation needs to encourage many more such efforts, across the country, to reap the full benefits of our federal investment in science.

The implication here is that unless the results of federal investment in the sciences can be privatized, the country does not “reap the full benefits” of the federal investment. This makes the whole idea of a massively expanded federal government program make a lot more sense, politically, because it’s a massive redistribution of funds to, ultimately, Big Tech, who can buy up any successful ‘startups’ without any downside investment risk. And Big Tech now runs the country and has found a way to equate its global market share with national security such that these things are now indistinguishable in any statement of U.S. policy.

This would all be fine I guess if not for the fact that science is different from technology in that science is, cannot be, a private endeavor. The only way science works is if you have an open vetting process that is constantly arguing with itself and forcing the scientists to reproduce results. This global competition for scientific prestige through the conference and journal systems is what “keeps it honest”, which is precisely what allows it to be credible. (Bourdieu, Science of Science, 2004)

A U.S. strategy since basically the end of World War II has been to lead the scientific field, get first mover advantage on any discoveries, and reap the benefit of being the center of education for global scientific talent through foreign tuition fees and talented immigrants. Then it wields technology transfer as a magic wand for development.

Now this is backfiring a bit because Chinese science students are returning to China to be entrepreneurial there and also work for the government. The U.S. is discovering that science, being an open system, allows others countries to free ride and this is perhaps bothersome to it. The current administration seems to hate the idea of anybody free-riding off of something the U.S. is doing, though in the past those spillover effects (another name for them!) would have been the basis of U.S. leadership. You can’t really have it both ways.

So the renaming of the NSF to the NSTF–with “technology” next to “science”–is concerning because “technology” investment need not be openly vetted. Rather, given the emphasis on go-to-market strategy, it suggests that the scientific norms of reproducibility will be secondary to privatization through intellectual property laws, including trade secrecy. The could be quite bad, because without a disinterested community of people vetting the results, what you’ll probably get is a lot of industrially pre-captured bullshit.

Let’s acknowledge for a minute that the success of most startups little to do with the quality of the technology made and much to do with path dependency in network growth, marketing, and regulatory arbitrage. If the government starts a VC fund run by engineers with no upside then that money goes into a bunch of startups which then compete for creative destruction of each other until one, large enough based on its cannibalizing of the others, gets consumed by by FAANG company. It will, in other words, look like Silicon Valley today, which is not terribly efficient at discovery because success is measured by the market. I.e., because (as Dr. Reif suggests) the return on investment is realized as capital accumulation.

This is all pretty backwards if what you’re trying to do is maintain scientific superiority. Scientific progress requires a functional economy of symbolic capital among scientists operating with intellectual integrity that is “for its own sake”, not operating at the behest of market conquest. The spillover effects and freeriding in science is a feature, not a bug, and it’s difficult to reconcile it with a foreign policy that is paranoid about technology transfer to its competitors. Indeed, this is one reason why scientists are often aligned with humanitarian causes, world peace, etc.

Science is a good social structure with a lot going for it. I hope the new bill pours more money into it without messing it up too much.