An odd little detail in a Physics World piece on Microsoft’s claim to have made a working topological qubit:
Regardless of the debate about the results and how they have been announced, researchers are supportive of the efforts at Microsoft to produce a topological quantum computer. “As a scientist who likes to see things tried, I’m grateful that at least one player stuck with the topological approach even when it ended up being a long, painful slog,” says [Scott] Aaronson.
“Most governments won’t fund such work, because it’s way too risky and expensive,” adds [Winfried] Hensinger. “So it’s very nice to see that Microsoft is stepping in there.”
In drug development, defence technologies, and life sciences research, to name a few, we’ve seen the opposite: governments fund the risky, expensive part for many years, often decades, until something viable emerges. Then the IP moves to public and private sector enterprises for commercialisation, sometimes together with government subsidies to increase public access. With pharmaceuticals in particular, the government often doesn’t recoup investments it has made in the discovery phase, which includes medical education and research. An illustrative recent example is the development of mRNA vaccines; from my piece in The Hinducriticising the medicine Nobel Prize for this work:
Dr. Kariko and Dr. Weissman began working together on the mRNA platform at the University of Pennsylvania in the late 1990s. The University licensed its patents to mRNA RiboTherapeutics, which sublicensed them to CellScript, which sublicensed them to Moderna and BioNTech for $75 million each. Dr. Karikó joined BioNTech as senior vice-president in 2013, and the company enlisted Pfizer to develop its mRNA vaccine for COVID-19 in 2020.
Much of the knowledge that underpins most new drugs and vaccines is unearthed at the expense of governments and public funds. This part of drug development is more risky and protracted, when scientists identify potential biomolecular targets within the body on which a drug could act in order to manage a particular disease, followed by identifying suitable chemical candidates. The cost and time estimates of this phase are $1billion-$2.5 billion and several decades, respectively.
Companies subsequently commoditise and commercialise these entities, raking in millions in profits, typically at the expense of the same people whose taxes funded the fundamental research. There is something to be said for this model of drug and vaccine development, particularly for the innovation it fosters and the eventual competition that lowers prices, but we cannot deny the ‘double-spend’ it imposes on consumers — including governments — and the profit-seeking attitude it engenders among the companies developing and manufacturing the product.
Quantum computing may well define the next technological revolution together with more mature AI models. Topological quantum computing in particular — if realised well enough to compete with alternative architectures based on superconducting wires and/or trapped ions — could prove especially valuable for its ability to be more powerful with fewer resources. Governments justify their continuing sizeable expense on drug development by the benefits that eventually accrue to the country’s people. By all means, quantum technologies will have similar consequences, following from a comparable trajectory of development where certain lines of inquiry are not precluded because they could be loss-making or amount to false starts. And they will impinge on everything from one’s fundamental rights to national security.
But Hensinger’s opinion indicates the responsibility of developing this technology has been left to the private sector. I wonder if there are confounding factors here. For example, is Microsoft’s pursuit of a topological qubit the exception to the rule — i.e. one of a few enterprises that are funded by a private organisation in a sea of publicly funded research? Another possibility is that we’re hearing about Microsoft’s success because it has a loud voice, with the added possibility that its announcement was premature (context here). It’s also possible Microsoft’s effort included grants from NSF, DARPA or the like.
All this said, let’s assume for a moment that what Hensinger said was true of quantum computing research in general: the lack of state-led development in such potentially transformative technologies raises two (closely related) concerns. The first is scientific progress, especially that it will happen behind closed doors. In a June 2023 note, senior editors of the Physical Review B journal acknowledged the contest between the importance of researchers sharing their data for scrutiny, replication, and for others to build on their work — all crucial for science — and private sector enterprises’ need to protect IP and thus withhold data. “This will not be the last time the American Physical Society confronts a tension between transparency and the transmission of new results,” they added. Unlike in drug development, life sciences, etc., even the moral argument that publicly funded research must be in the public domain is rendered impotent, although it can still be recast as the weaker “research that affects the public sphere…”.
The second is democracy. In a March 2024 commentary, digital governance experts Nathan Sanders, Bruce Schneier, and Norman Eisen wrote that the state could develop a “public AI” to counter the already apparent effects of “private AI” on democratic institutions. According to them, a “public AI” model could “provide a mechanism for public input and oversight on the critical ethical questions facing AI development,” including “how to incorporate copyrighted works in model training” and “how to license access for sensitive applications ranging from policing to medical use”. They added: “Federally funded foundation AI models would be provided as a public service, similar to a health care private option. They would not eliminate opportunities for private foundation models, but they would offer a baseline of price, quality, and ethical development practices that corporate players would have to match or exceed to compete.”
Of course, quantum computing isn’t beset by the same black-box problem that surrounds AI models, yet what it implies for our ability to secure digital data means it could still benefit from state-led development. Specifically: (i) a government-funded technology standard could specify the baseline for the private sector to “match or exceed to compete” so that computers deployed to secure public data maintain a minimum level of security; (ii) private innovation can build on the standard, with the advantage of not having to lay new foundations of their own; and (iii) the data and the schematics pertaining to the standard should be in the public domain, thus restricting private-sector IP to specific innovations.[1]
[1] Contrary to a lamentable public perception, just knowing how a digital technology works doesn’t mean it can be hacked.