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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.
As some background for people, scientific labs usually have a three-level structure:
Looking over the academic investigation, it seems like a classic fudge: the PI says the data was compiled by a graduate student who never formalised it and took the original creation methodology with them when they left (entirely possible). The writer (a graduate student) is in hiding and refused to talk to the committee but gave various unconvincing reasons in writing why the false database can't be theirs (e.g. their database was a different file format). A bunch of graduate students were involved with the project, and their papers also seem to be dodgy in various ways.
Quoting the investigation committee:
Most likely explanation is that it's some combination of graduate students signing up to work with a prestigious PI, being put under huge pressure to produce results, and taking the low road rather than destroying their career. By the sounds of it, the data was passed around enough times that nobody was sure where it came from, and so didn't consider themselves to be doing anything more fraudulent then trusting their colleagues. It's entirely possible that the PI didn't know - or didn't want to know - that this was happening. His name is on most of the papers but that's standard for a PI and doesn't prove he did anything except fund the work.
Should the PI be punished, in the absence of positive evidence they did something wrong? Possibly. Probably, even. I can certainly see the argument for it and it might help. But at some point you have to do something to make academia less soul-destroying, otherwise it's like beating a horse and then killing it when it kicks.
You can of course control all of this to some extent by regulating how work is done and how data is handled, and in the last twenty years we mostly do. A big part of what the PI is getting dinged for in the original report is not following the appropriate guidelines. But academic labs aren't big pharmaceutical companies with lots of money to spend on compliance, so research output takes a big hit when this regulation becomes strict.
Secret data but more importantly secret code (any programs, algorithms, statistical techniques, data cleaning, etc.), would never cut it in the professional world. If you're a data scientist or a product manager proposing a change to a company's business processes you need to have your work in source control and reviewable by other people. There's no reason academics can't do the same. Make the PI responsible by default unless they can show fraud in the work their underling did. If they didn't review their underling's work then the PI is fully responsible. This would have the added benefit that researchers would learn useful skills (how to present work for review) for working in industry.
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Perhaps that should change, and perhaps one of the ways we could make it change would be to penalize the names on the papers for fraudulent work.
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