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Short summary (a scientist erred/falsified results in heart disease treatments, up to 800,000 died):
Full Vox link
I find the Vox article somewhat disturbing. They spend most of the article talking about whether criminalization is the answer. 800,000 dead, or some number in the high thousands and they feel it's necessary to spend so much time justifying and proposing? Why should they be carefully peeping their heads over the parapet, wary of sniper fire? If ever there was someone to cancel and demonize, it's this guy.
I have an internal feeling of justice that calls for extremely severe penalties for these people. I guess I'm in the minority, since it doesn't happen. The EcoHealth gang, Daszak and the Bat Lady of Wuhan are still living the high life. Meanwhile, scientists who dare to have sex with coworkers get their lives derailed.
I suppose that most people have their feelings of justice heavily weighted towards direct things like killing with knives, selling faulty goods or being mean. That makes sense, we didn't evolve to care about the probabilistic harms caused by institutional malpractice over many years. This is why I think we should have extra-strong prohibitions on this kind of non-obvious harm. Even a hardened EcoHealth researcher might have qualms about massacring 10-20 million people with guns and blades. It's a lot easier to do exciting, fun research and be a little slack on all those tedious safety checks. It doesn't feel so wrong, which is why they need to feel fear to counter it.
In the past I've made this sort of argument and been rebuffed by some people on the grounds that if we imposed very severe punishments then people would just double down on lying and blaming others to escape liability. Plus it would disincentivize people from taking up important roles.
However, when it comes to mechanical engineering, we've learned to build bridges that stay up. We appreciate that some kind of consequence should fall upon you if you adulterate food with plastic or replace the concrete with cardboard (or cardboard derivatives). Back in the early Industrial Revolution nobody particularly cared about safety, there were plenty of bridge failures. We slowly had to evolve systems that corrected these problems but we got there in the end.
Indeed, negligence is a big part of law. Mostly it works on the assumption that the harm-causing party is a big corporation or someone with lots of money. From a broad evolutionary point of view, that makes a lot of sense. Proving guilt and getting to the bottom of things takes a lot of effort, you want to be sure that there will be a pay-off. It's like how creatures might evolve fangs to pierce flesh and get at that juicy meat. Entities that can cause lots of harm tend to have lots of resources.
However, academia gives us cases where there are no clear, direct, short-term links between the cause of harm and the victims. The cause of harm might be a few moderately well off scientists. The harm itself might be hazy, there might be no ironclad proof of the magnitude and exact nature. Think how long it took to prove that cigarettes caused cancer. We had the statistical proof long before the exact causal mechanism was ironed out and the costs of delay were phenomenal. Biology is the most obvious case where this happens. There was another case where Alzheimer's research was thought to be fraudulent, wasting many years and billions of dollars. I say slash and burn, take their money away, give them humiliating tattoos and make them work at McDonalds somewhere far away from all their friends, or worse. Normal criminals couldn't do that much harm in a lifetime.
AI likely falls into the same category, though it can probably be dealt with via more traditional negligence systems since it's mostly advanced by big companies. I am worried that it will take far too long for people to realize the danger posed by AI or those who wield them, there isn't enough time to develop seriousness.
Anyway, I think it would be wise to develop ways to target and severely punish biologists who fraudulently or negligently allow harm (perhaps also praising and granting boons to those who uncover their fraud). This would be a positive incentive for singularitarian scenarios and virtuous in itself. We need to get out of the mindset of waiting for our market-Darwinist-legal system to fix things and attack problems pre-emptively. Or at least with a minimum of megadeaths.
Samesies.
I'm not saying to impose the death penalty on the guy.
But i'm not not saying it.
What always impresses me is how the system seems to have evolved into such a highly polished and lubricated machine that you can sling blame all you like, it won't stick to any individual component.
Almost everyone in the chain of decisions that led to the outcome can just say "Well its not MY fault, I was just relying on [other link in chain], which is what the best practices say!"
Maybe even the guy who produced the fraudulent research can say "I was relying on inexperienced lab assistants/undergraduates who produced faulty data!" I don't know.
But there has to be some method of accountability. Like you say:
The (apocryphal) story about Roman Architects being required to sleep under bridges or arches they built is on point here. Bridges stay up (except when they don't) because there's a close enough loop between the decisionmaker and the consequences for failure. It maybe doesn't have to be quite as tight as "you must be directly harmed if your decisions harm others" like with the bridge story, but it has to be make them afraid, on some level, of being punished if they screw up.
I'm not entirely sure how to bring the consequences for screwing with academic research into medical treatments into a tight loop. One might hope it would be enough to say "If you ever end up in a hospital needing treatment, YOUR RESEARCH is going to be used to treat you." And thus they should have some concern about getting it right. But that's a very distant, uncertain threat. What would be a (proportional) threat you could make to bring down punishment on them the very instant the misconduct is uncovered? And how can you trust the entity that claims to have uncovered misconduct?
Prediction Markets offer one way to put more skin in the game, but it doesn't quite satisfy me that it would be a significant deterrent for others attempting fraudulent research.
And if we set up some organization whose specific objective was punishing those whose academic fraud causes harm to others, that institution would simply become another target for capture by vested interests. I think it has to be something a bit more 'organic.'
He does say that. In general, who 'produces' a given piece of research is very difficult to nail down, because the head of the lab (the guy in the article) hasn't done labwork for twenty / thirty years and the work will have been done by many PhD students who come and go within four years. The recipients of Nobel prizes have often done none of the physical work that produced the result, or the analysis, or the write-up. Sometimes they didn't even come up with the theory.
Sorry, I think I'm spamming this thread, but it's a topic close to my heart.
I think the point of having a principal investigator, is that he is aware of what is going on.
If they are not in the loop of the research process, they is no point for them to be on the paper and they are just academic rent-seekers.
Granted, at some level, you have to trust in the non-maliciousness of your grad students. If a smart and highly capable PhD candidate decides to subtly massage their data, that could be difficult to impossible to catch by their supervisor. The way to avoid that is not to incentivize faking data (e.g. no "you need to find my pet signal to graduate"). The PhDs who would fake data because they are lazy are more easily caught, producing convincing fake data is not easy.
Of course, in this case, we are not talking about terabytes of binary data in very inconvenient formats, but about 170 patients. Personally, I find it highly unlikely that the graduate student found that data by happenstance, and his supervisor was willing to let them analyse it without caring for the pedigree of the data at all. I think the story that he provided the data in the first place, years after it was curated by another grad student whose work he did not check is more likely.
In my field, physics, I don't generally feel that is the case. For one thing, people tend to get their Nobels much later than their discoveries. From my reading of wikipedia, when Higgs (along with a few other groups) published his paper on the Higgs mechanism, he was about ~35 and had just had his PhD for a decade, and a job as a Lecturer (no idea if this implies full tenure) for four years. Not exactly the archetype of a highly decorated senior researcher whose gets carried by tons of grad students towards his Nobel.
In the traditional British system of academic titles, "lecturer" is the lowest of four grades of permanent academic staff (lecturer/senior lecturer/reader/professor) which loosely correspond to the tenure track in the American system. American-style tenure doesn't exist, because all UK employees benefit from protection against unfair dismissal after two years full-time work on a permanent contract. Taking 14 years to be promoted from lecturer to reader (per Wikipedia) was quite normal at the time for academics who were not seen as superstars by their colleagues.
So if we are going to draw a direct equivalent to the US system, Higgs was 4 years into his first tenure-track job when he published his Nobel paper, but the importance of the paper wasn't recognised for another decade+.
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