The Temple and the Network

Scientific institutions are dinosaurs, coronavirus was the asteroid, and the open network is the mammals.

Science isn't doing so great these days. It's worth asking why, and putting some thought into what comes next. I'm honestly kind of bored talking about the problems, but given how deeply entrenched the current organisational model for science is, they have to be addressed in order to motivate discussion of possible solutions, which is the real point of this essay.

Most of the problems in science are cultural.

The scientific community has ossified into a highly formalized institutional system built primarily around university faculties, government research laboratories, and corporate R&D facilities. To become a scientist involves spending many years going through an elaborate training regime in which one ascends through the ranks from B.Sc., to M.Sc., to Ph.D., to postdoc (to postdoc, to postdoc), to fellow, to assistant professor, to associate professor, and so on. This elevation involves jumping through numerous hoops that often have little if anything to do with becoming an effective researcher - the infamous qualifying or comprehensive exams mid-way through American doctoral programs, for instance, or the equally infamous 'weed-out' courses that you endure not because they're relevant to your field of research (they aren't), but because they're hard. Results are disseminated through an unwieldy combination of conference posters, conference talks, and peer-reviewed publications - each of which requires that a scientist essentially obtain permission from an anonymous panel to tell anyone about his work. It can very easily be several months between a scientific result being essentially complete, and its seeing the light of day.

It isn't that a formal rank structure, difficult coursework, or rigorous editorial standards are a problem, per se. I'm a fan of high standards, coming of age trials, and competence hierarchies. The issue is the degree to which the formal structure of scientific institutions has been conflated with science itself, which in turn leads to an uncritical acceptance of everything that emerges from the academy as having the official imprimatur of Science!™. It's peer reviewed! Therefore it must be true.

Scientists themselves don't really believe this. Inside our own narrow sub-fields we're intensely critical of everything that gets published, and tend to take the view that much of what makes it into the peer-reviewed literature is just wrong. Yet at the same time, it seems that many scientists become just as uncritical as the general public when it comes to other fields. Trust the experts, and I'm not an expert, so who am I to doubt? This is basically Gell-Mann amnesia, the phenomenon where when you read a story in the media on something you know about personally, you notice how horrifyingly inaccurate it is, yet when you click through to the next story on a topic you're not familiar with you immediately forget that revelation of journalistic sloppiness and ignorance, and assume the new story must be basically true.

You also get a certain petulance from professional scientists who do encounter skepticism from the lay public. There's an assumption that the years of study they've put in entitle them to the credence of the masses. To be fair, dealing with yet another flat-earther or physics crank whose theory of everything is founded on a misunderstanding of an elementary equation in classical mechanics gets wearying. There is something to be said for genuine expertise in a subject, and it's understandable that professionals who spend most of their time conversing with colleagues can get frustrated, throw up their hands, and say, just take my word for it, damn you.

Still. Institutional science would have a better case to make if it weren't for little problems like the replication crisis, which in some fields can affect something like half of the published literature. Not just the literature in fly-by-night open access journals, either; we're talking the big hitters, Nature, Science, Cell. That isn't all naked corruption, although politically and economically motivated research misconduct is certainly a big problem in some fields¹. A lot of it is just sloppy work motivated by the publish-or-perish imperative. Years ago some physicists ran an agent-based model that showed that if the incentive is to publish rapidly rather than to minimize error, mistakes would proliferate, and very rapidly take over the literature; even work in which the authors hadn't made any mistakes themselves would invariably rely upon previous work that was mistaken, and would therefore be wrong. Eventually the literature becomes one big steaming pile of unreliable garbage.

The other big problem institutional science has is that standards have been getting whittled down for years now. Stamping your foot and exclaiming, It's DOCTOR to the likes of you! is a lot less compelling when you know that a measurable fraction of terminal degree holders got their credentials thanks to affirmative action. That's how you get arrogant females blithely assuming that they must be the smartest person in the room, only to test at the bottom of the heap and get shown up by a soft-spoken soldier who never went to college. It's also why 'impostor syndrome' has gone epidemic in the professoriate: people promoted beyond their ability feel like they're impostors because, well, they're impostors. Contra The Wizard of Oz, getting a piece of paper doesn't mean you have a brain, and contra Dunning and Kruger² most people are actually pretty good at assessing their own intellectual acumen.

The result of this is that attitudes towards science have become sharply bifurcated along partisan lines. On the left, you have the cultists who trust, believe, follow and I-fucking-love THE SCIENCE!™. Scientists are their priesthood, the laboratory is their temple, the computer model is their oracle, the mask their hijab, the PCR test their sacrament, the needle their baptism. On the right people tend to take a more measured, traditional view of science - as a body of knowledge, subject to continuous revision, which should be taken seriously but never on faith ... and maybe taken a little less seriously than in the recent past given the context of the issues I pointed out above.

Almost exactly a year ago a digital ethnograpy of 'antimaskers' was conducted by researchers at MIT. They were hoping to generate insight into why some of us stubbornly refuse to Believe The Science. To their horror, they found that plandemic skeptics weren't a crowd of drooling QAnon trumpsters barking at each other in monosyllables about reptoid biochips, but a sophisticated community of data analysts engaging in a nuanced, careful examination of available information:

Jones says the antimask groups’ “idea of science is not listening passively as experts at a place like MIT tell everyone else what to believe.” He adds that this kind of behavior marks a new turn for an old cultural current. “Antimaskers’ use of data literacy reflects deep-seated American values of self-reliance and anti-expertise that date back to the founding of the country, but their online activities push those values into new arenas of public life.”

...

Lee says their findings point to “a larger rift in how we think about science and expertise in the U.S.” That same rift runs through issues like climate change and vaccination, where similar dynamics often play out in social media discussions.

In other words, on the one hand you've got institutional science believers, who adopt the position that everyone should more or less just believe what comes out of the formalized, professional scientific establishments. On the other are an anarchic group of anons for whom science is a participatory process.

The fascinating thing about the last couple of years has been the dramatic shift in credibility and public attention from institutionalized science to open network science. The institutions have shown themselves to be completely untrustworthy. They've gotten everything about SARS-CoV-2 wrong: origin, rate of spread, infection fatality rate, the efficacy of lockdowns, the efficacy of masks, the efficacy and safety of treatments (erring in the direction "ineffective and dangerous" for the perfectly effective and safe, and "safe! and effective!" for the ineffective and dangerous). Whether it was sheer incompetent groupthink or craven servility to globalist power politics is almost irrelevant³: the simple fact is, they failed, comprehensively and totally, with such reliability that one can adopt the heuristic "the institutions are saying X, therefore the truth is not-X", and have a good chance of being right without having to put any further thought into the matter.

Meanwhile, there's that open source, anarchic network of renegade scientists and schizo anons the MIT researchers were looking at. That network has absolutely run rings around institutional science, having proved itself more accurate, more nimble, more agile, and more interesting.

What we're seeing is the birth of an entirely new way of doing science.

In this model, no one cares about what letters you have after your name (or what you have between your legs, or what colour your skin is): all that matters is, are you capable of doing the work, and are you interesting? Those that are both gather an audience.

There's no formal system of peer review. Results are published as soon as they're ready, and the critiquing process begins immediately in the comments section, on other blogs, and on social media. The barriers to entry are effectively non-existent, while the publication/review/replication duty cycle is extremely rapid. Any given 'paper' (insofar as that term is even meaningful in this model) will be a lot less polished⁴, but the overall quality of the ideas being propagated through the network gets much higher. The network acts as a far more ruthless arena for agonistic knowledge-testing than is currently possible in the academic sewing circle⁵.

I expect this will ultimately lead to a much better public understanding of science, for at least two reasons.

First is that this model is fundamentally participatory. No one needs to spend years of their lives and tens of thousands of dollars becoming a hyperspecialized academic in order to contribute to the conversation. Sure, that training might help develop the skills and acquire the knowledge base necessary to do so competently and compellingly; but formal training isn't a requirement, it's really just one path, because all that matters is that somehow or other you've learned what's necessary.

Second, in order to succeed in this environment, a scholar has to be entertaining and accessible. That means avoiding the jargon that tends to proliferate like algal blooms and mosquito larvae in the stagnant swamps of isolated sub-specialities. It means writing in clear, direct prose, using the active voice ("I did this, I got this result, therefore I think that....") and abhorring the committee-written feel of the passive voice ("This was done, this result was obtained, therefore it is thought that....") It means adding a bit of humour and colour to enliven otherwise dry technical descriptions, thereby mixing in enough humanity to keep the audience from nodding off.

Independent scholars need to be entertaining to get and keep those precious eyeballs that send them superchats on livestreams, sign up for paid Substacks, and support them on Patreon. Entertaining information is more easily assimilated by the student. The always-open option of direct participation in the scientific process provides a ready avenue to get the hands-on experience required for deep learning of any given subject.

Right there, you've got all the necessary ingredients for a self-sustaining pedagogical/investigative loop that can perform the core scientific functions of discovery, interrogation, and dissemination of knowledge. All without the cumbersome, expensive, torpid bureaucracy of universities, grant agencies, and peer-reviewed journals. What's more, there's every reason to believe that this open network approach will perform all of those functions to a higher standard than that achieved by the legacy institutions. We've got the last two years as proof of concept.

In a lot of ways this is just a return to the roots of science. The formalized system of degrees is a fairly recent innovation, dating more or less to 19th century Prussia. Peer-reviewed journals are even more recent, dating to the post-WWII era and the establishment of large national scientific funding agencies (which demanded peer review because they wanted accountability to the taxpayer or something). Go back to the 19th century and before, and science was largely a leisure pursuit for aristocratic dilettantes who funded their own research because they thought it was fun, and who published their results in scientific journals that had a very informal style, the old-timey equivalent of "Bro! Check this out, this was awesome!"

Finally, to be absolutely fair to those scientists (including myself) who continue to operate essentially within the legacy institutions, this open network model is really just the maturation of a model that scientists have been developing themselves. Amongst our immediate colleagues, we don't communicate our results using the peer-reviewed literature: we use e-mail, like anyone else. Crowd-sourcing data analysis, often referred to as citizen science, has been a thing in certain fields for a while. It's especially popular in astronomy, where you can find web sites inviting the public to help identify exoplanets in satellite data, or classify galaxies, or characterize different kinds of stellar variability. It's been recognized for some time by astronomers that a large and interested public is a fantastic way to help sort through the torrential datastream generated by automated surveys, particularly if you can make it fun.

The coronavirus debacle has demonstrated pretty convincingly that this basic model can be extended much more widely. As the lumbering dinosaurs of academia, already suffering dementia from the parasitic load of ideological capture, succumb to starvation of funds and attention in the wake of the COVID asteroid, this will be how science continues. It will evolve. There’s no need for a long march to recapture the institutions; we’ll simply build our own, faster, smarter, and better⁶. We’re already doing it.

1. Looking at you, biomed and sociology, you shifty, no-good grifters.

2. Oh hey another high-profile result that failed to replicate.

3. It was both.

4. Although, believe you me, I have seen some absolutely abhorrent prose in the formal literature. Editorial standards are not what they used to be.

5. Especially given that academia has adopted feminized standards of discourse whereby some idiot talking nonsense is no excuse to hurt the idiot's feefees.

6. With blackjack! And hookers!