A Book That Will Never Be Read(forbetterscience.com) |
A Book That Will Never Be Read(forbetterscience.com) |
Signals are inherently bound to be distorted. The "legitimate methods" conceived by humans and social signals are easy to manipulate. Because public data like the number of published papers and diplomas act as strong social signals, they end up being distorted. This is known as Goodhart's Law.
The problem is that if this persists long-term, there will eventually be a shortage of personnel to quantitatively evaluate papers, and society probably won't hire these researchers. There is also no incentive to hire them, as verification rarely leads to direct profit. People tend to want to be the starting point of a discipline; they generally do not like checking other people's work.
As a result, academia will increasingly be validated solely by "which lab, which advising professor, and what peer network certified you." The value of the offline world will rise, simply because digital costs have become too cheap.
Soon, research quality and social status will likely merge again, resembling the Middle Ages. Even if we assume someone has actual research capabilities, if evaluators do not invest enough time in verification, the system will inevitably revolve around the more prestigious labs.
I suspect there will be a flood of research applying AI, but the topics of these studies will likely be quite narrow and localized (it would be nice to have statistics on this). I believe the overall diversity of topics explored across academia will diminish.
For this reason, I think existing networks will only grow stronger.
I feel that any solutions to this problem will go awry. I doubt self-purification is even possible anymore. Established researchers protect the monopoly power of publishers, while those existing publishers generally just want to cut costs. The authority of these publishers must be protected by the established researchers who have already secured their positions.
Next, the system that used to manipulate the number of papers will probably shift into a system that manipulates network reputation. The competition to get into good labs and the strategies to secure co-authorships with famous researchers will simply become the new means of competition.
Before it was artisanal non-replicable, p-hacked, publish or perish motivated, politically biased slop. Now we have some AI sugar sprinkled on top.
As an interested outsider myself, it's pretty depressing seeing how high the risk:reward ratio seems to be for people within academia who are driven to clean it up and call out bad actors, and how high the reward:risk ratio is for those who are willing to cut corners (or just plain cheat, if they do it in a minimally competent way).
My impression is that large portions of academia (and not just the most obvious candidates) are too close to the other extreme, with nothing to guarantee that indefinite cargo culting is not a stable equilibrium. And even when people notice this and get mad about it, they're more likely to flip the political sign of the problem than to actually fix it. But I hope this is overly cynical.