Will the American trade war with China expand to include cutting-edge technology research? If so, how will that impact colleges and universities?
This is a tricky topic, so I’m going to break it down as follows: first, a summary of a new development; second, potential ramifications for higher education; third, some background notes.
WHAT HAPPENED: last week a Trump administration official published a public request for comments about a new policy. Specifically, this is an advance notice of proposed rulemaking (ANPRM) for adding items to the Commerce Control List (CCL) (pdf). The CCL usually covers American products and services deemed to have national security implications, and hence may be subject to federal regulation. In other words, the government sometimes determines that some stuff would be bad for American security if certain entities (national governments, non-state actors) get a hold of it.
What’s on this list of items? An ambitious manifest of emerging technology. The first header is biotechnology, “such as: (i) Nanobiology; (ii) Synthetic biology; (iv) Genomic and genetic engineering; or (v) Neurotech.” Which is impressive enough (hello, CRISPR). But then things really take off in the digital realm. All kinds of AI are in there, along with a range of robotics, 3d printing, quantum computing, brain-machine interfaces, and more.*
To be clear, this isn’t a policy yet. It’s just a call for comments, so it could potentially disappear, or only parts of it end up as federal strategy. It’s an early signal of one future.
WHAT COULD THIS MEAN FOR HIGHER EDUCATION?
First, some number of American faculty members and supporting staff work on these fields, so their professional practices could well be rearranged. They might be encouraged to publish in closed environments rather than open journals, for example, or discouraged from collaborating with researchers from certain nations. And by “certain nations” read “China.” Well, China and its allies, but mostly China. A new policy could find echoes in funding as well as hiring/promotion/tenure processes.
Second, this could alter education. Faculty teaching such topics could well avoid publishing content on the open web (as pages, accessible repository content, actually open MOOCs, etc.) and instead lodge course content in LMS silos. Campuses might receive political pushback (from governments, donors, politicians, commentators, their own population) for recruiting students from targeted nations (again, read China).
Third, teaching and research on these topics might narrow in focus, aimed more closely at certain defense or commercial ends. The free flow of research and development could be trammeled.
Fourth, export controls could weaken researchers’ ability to work, as Karen Hao points out. Chinese retaliation, which is par for a trade war’s course, could cut material and intellectual supplies to American professors. The impact would also hit American firms:
Companies like Apple and Google, for example, which rely on China for a large share of their profits, might scale back their AI development to avoid the famously lengthy export control process. Smaller companies that can’t handle the high compliance costs might write off international expansion.
Fifth, a culture of secrecy might expand on campuses where teaching and/or research occurs on these topics. Taking a class on smart dust, for example, might require extra layers of approval, including background checks. Faculty might rein in any campus publicity or outreach they’d otherwise conduct, keeping this work on the QT. How might such practices change a college or university’s culture?
Moreover, such changes could connect with currently existing campus politics re: Trump. If (for example) quantum computing ends up on the banned export list and a given professor continues her research on the subject in some secrecy, would anti-ICE faculty and staff reach out to them in support, or out them as a sign of Trump’s tyranny? Might campus information professionals be pressed to protect and reveal national security work, even from people in the same program
The immediate context for this is geopolitics: the US-China trade war. China is obviously investing strategically in many of these fields, so the Trump administration seeks to sap their ability to proceed, while attempting to strengthen American efforts. This is an enormous contextual field, as it represents a struggle between the world’s two largest economies.
The military aspect drives further contexts. A chunk of the American geopolitical establishment has been anticipating conflict with Beijing since the Cold War’s conclusion. The argument is that China represents the most effective adversary to American power, especially given its extraordinary economic take-off over the past generation.
Most recently this has taken the form of the so-called Thucydides Trap, which argues that struggle between a rising power (China) and an established hegemon (the US) is very likely. Before that was the struggle over the Obama administration’s Trans-Pacific Partnership treaty, a massive economic attempt to outflank and isolate China. (We can go further back for additional context. In the 1950s the two nations faced off over the conflict between the People’s Republic and Taiwan’s Nationalist remnant. In the 1950s the Korean War saw massive pitched battles between Chinese and American armies. In 1900 the United States joined seven other nations in actually invading China.)
I raise these contexts here not to argue for or against the idea of an inevitable Washington-Beijing war, but instead to show that the roots of this two-page ANPRM run deeply. They involve major currents in geopolitics, and now may more extensively intertwine around American academia.
Once again, I issue a caveat. This is a proposed rule-making. There are many possibilities here – and we should keep our eyes on them as we consider higher education’s future.
*Here’s my extract from the document:
(2) Artificial intelligence (AI) and machine learning technology, such as: (i) Neural networks and deep learning (e.g., brain modelling, time series prediction, classification); (ii) Evolution and genetic computation (e.g., genetic algorithms, genetic programming); (iii) Reinforcement learning; (iv) Computer vision (e.g., object recognition, image understanding); (v) Expert systems (e.g., decision support systems, teaching systems); (vi) Speech and audio processing (e.g., speech recognition and production); (vii) Natural language processing (e.g., machine translation); (viii) Planning (e.g., scheduling, game playing); (ix) Audio and video manipulation technologies (e.g., voice cloning, deepfakes); (x) AI cloud technologies; or(xi) AI chipsets. (3) Position, Navigation, and Timing (PNT) technology. (4) Microprocessor technology, such as: (i) Systems-on-Chip (SoC); or (ii) Stacked Memory on Chip. (5) Advanced computing technology, such as: (i) Memory-centric logic. (6) Data analytics technology, such as: (i) Visualization; (ii) Automated analysis algorithms; or (iii) Context-aware computing. (7) Quantum information and sensing technology, such as (i) Quantum computing; (ii) Quantum encryption; or (iii) Quantum sensing. (8) Logistics technology, such as: (i) Mobile electric power; (ii) Modeling and simulation; (iii) Total asset visibility; or (iv) Distribution-based Logistics Systems (DBLS). (9) Additive manufacturing (e.g., 3D printing); (10) Robotics such as: (i) Micro-drone and micro-robotic systems; (ii) Swarming technology; (iii) Self-assembling robots; (iv) Molecular robotics; (v) Robot compliers; or (vi) Smart Dust. (11) Brain-computer interfaces, such as (i) Neural-controlled interfaces; (ii) Mind-machine interfaces; (iii) Direct neural interfaces; or (iv) Brain-machine interfaces. (12) Hypersonics, such as: (i) Flight control algorithms; (ii) Propulsion technologies; (iii) Thermal protection systems; or (iv) Specialized materials (for structures, sensors, etc.). (13) Advanced Materials, such as: (i) Adaptive camouflage; (ii) Functional textiles (e.g., advanced fiber and fabric technology); or (iii) Biomaterials. (14) Advanced surveillance technologies, such as: Faceprint and voiceprint technologies.