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Comment by pseudo0 | Hacker News Reader

> I had already presented John’s data at several national conferences, and we were writing a paper I thought would have a huge impact on our field.

Sounds like this person was part of the problem if their idea of "supervision" was flying around taking credit for their postdoc's fraudulent research while being so out of the loop that they didn't notice the postdoc fabricating data whole cloth.

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Professors are basically CEOs for deep-tech start-ups (at least in science and engineering). Yes, they know the theory, technology, tools, etc, (from their own time as PhDs and Postdocs), but they need to delegate much of the work to their team. Like a CEO, the PI's main jobs are to strategize (choose research direction), form partnerships (collaborations), and fund raise (find grant money). This money is used to pay said team (students) to work on the products (research projects). In this analogy, each student is basically a project manager working on their own product, sometimes with a MASc or UG student to help with the labor intensive parts (experiments). When the product is ready for release (publication), the PI helps market it (at conferences) and puts their name on it (as coauthor). This is not stealing credit, this is amplifying the team's success so everyone wins. It builds visibility and credibility for the team members involved, and keeps the ball rolling by allowing the PI to get more funding based on the win. Note that the PI is instrumental in choosing and guiding the work, leveraging their experience to brainstorm solutions when stuck, etc, but nobody thinks they are actually in the lab doing it all.

So, I guess my point is, a good CEO would eventually figure out if work is bogus, but they'll probably be the last to know. BTW, noticing the data problems when working on the draft publication is literally the first opportunity a PI would have to really see all the final data in one place. Conferences are 'low stakes' and it's not unusual to present some preliminary and/or partial data.

I know this opens a HUGE can of worms if you really think about all the repercussions (e.g. who really deserves Nobel prizes and awards?), but that's a story for another day.

So in this analogy, the "startup" is Theranos and the professor is Elizabeth Holmes? That is not very reassuring.

Whoever's at the top has culpability for this type of fraud. Either they knew or they should have known.

Nobody wants to assume fraud in science, unless you have unassailable evidence that someone has committed fraud you really cannot risk your own reputation by dishing out allegations. The solution to this is trust but verify, but verifying data would require twice the amount of work, which not every lab has the funding to do, even if it was breakthrough research.

The sad truth about a lot of science is that science is built on trust. The psychology replication crisis is proof of that, there are so many ways to manipulate data to make it look like you have a result and also so much pressure to get a result that people resort to the former to get the latter.

There are plenty of historical scandals about how scientific fraud has taken way too long to investigate, people like Victor Ninov and Hwang Woo-Suk are two examples of just how far fraud can go before it's found.

The article here is comparatively tame compared to how far Huang and Ninov got.

Academia is funded to the tune of billions of dollars a year. If they don't have the funds to check their own work then it is a damning indictment of the funding process, one that suggests governments are utterly unqualified to be funding research at all.

But in this case funding doesn't seem to be the problem. The author says why she didn't check: she wanted to be famous.

Don't you think its funny that we pay academics a fraction of how much we pay tech workers and yet we expect so much more from them?

No because "we" don't pay academics, universities do. It's their decision to hire more professors instead of paying the existing ones more, it's their decision to create siloed departments etc. The system has plenty of money, but universities and grant agencies allocate it very badly despite being mostly staffed by academics and ex academics.

not really. in your analogy Elizabeth Holmes already the culprit.

Professor would be responsible of fraud if they learn about it and ignore it.

Absolutely his behavior allowed the situation to happen. This is probably the real original sin in all of this. The OP ego was so huge that he considered himself above the actual work —- even critical work —- that defines his trade.

In this case “John” probably understood this about him and was likely just giving him the validation he so desperately craved.

I like how he claims the art of science to be a sacrament yet can’t be bothered with the actual work. A complete bastardization of the actual core of the work.

This doublespeak of loving science in the abstract and totally ignoring it as applied to yourself is everywhere in academia. It’s one of the most profound disappointments of my adult life that the world is filled to overflowing with poser scientists.

Yeah this really stands out to me too. I'm still just a PhD student, and my PI is fairly hands-off (in that he tells me roughly what problems need addressing and their priorities and trusts me to work autonomously), but as a result he's also hands-off with taking credit. He doesn't present my work in detail on his own, typically he tries to have me present to do that myself.

It'd be pretty fair for this person to be held partly responsible if he was presenting it at conferences, which outside of exceptional circumstances (eg the postdoc was supposed to present but had to cancel with very short notice), would justify the assumption that he was familiar enough with the work to speak on it.

I bet that if the government goes after PIs who take federal money and then run a paper mill with inadequate supervision of postdocs, the situation vastly improves.

If you know you can go to jail if your postdocs fabricate data, I bet you will be a lot more thorough in checking all the original data.

The problem of scientific research is misaligned incentives. There is tremendous upside for publishing novel ideas and very little downside for fraud, especially for the PI who can pawn it off on the overworked, underpaid post-doc.

Rather than an post-hoc investigation model, how about promoting reproducibility in publication, with an expectation that others can run the same study with identical equipment, models, codes, playbooks, etc. For PIs getting government funding, true reproducibility should be a requirement, and other researchers should be funded to report pro or con on the reproducibility of studies, and then ethical lapses could be much more visible. Science based solely on faith in the ethics of other researchers is just religion with more complicated rituals.

Reproduction is not valued by the community in any way that matters. There’s no prize for reproducing, or failing to reproduce, others work. Getting a grant to do reproduction is much harder than getting the initial grant. Nobody is citing reproduction papers, so their authors can’t get that sweet sweet citation count.

We as a society don’t actually value the discipline of science or the pursuit of knowledge. We value being first.

> We as a society don’t actually value the discipline of science or the pursuit of knowledge.

The discipline of science is exactly how you get knowledge in a society that doesn't value its pursuit. It's an imperfect process of imperfect individuals that usually nevertheless arrives at knowledge eventually.

Fraud is just another part of this process. Additional checks for fraud or errors cost time and money. Effective checks would basically mean science costs 2x as much. How much fraud can we tolerate? Is it worth spending this much to reduce the amount of fraud compared to investing in more research? Can we slightly change incentives (as opposed to inventing some utopia that cannot be implemented) and thereby reduce fraud more cheaply? The academic discipline has been changing ever since and will continue to change and progress.

Publishing reproducible research would disincentivize fraud by providing a clear way to expose fraud, and could tend to benefit other researchers in the field, by effectively sharing specific methods as well as results.

Incentivizing reproducibility would be hard as a grassroots effort, but would be enforcible if it were tied to funding. Even if only a small percentage of published studies were reproduced, and only a small percentage of them were found to be fraudulent, the disincentive for fraud would be present. We do not need more Andrew Wakefields.

> Effective checks would basically mean science costs 2x as much.

By that logic, we would need to enforce speed limits by having one police cruiser following every driver.

This sounds like your standard “hands-off” PI who doesn’t dig too deeply in the day-to-day research and analysis. That can work, but at least make sure your postdoc has collaborators you trust will keep them honest. If your lab doesn’t have a culture where people give productive honest feedback (warts and all) on work before it’s publicized, then that’s a failure solely of leadership.

There are different tiers of hands-off PIs though. Most can probably be deceived by manipulated data. But you’re on another level if you can’t even catch someone producing groundbreaking data without being physically present in the lab using equipments.

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