Comment by bioinformatics | Hacker News Reader

Comment by bioinformatics | Hacker News Reader

The ____ (insert scientific community/field here) has a toxicity problem.

It can be said from every single field in science (I am in the natural/health ones):

- peer review is broken - check

- reproducibility problem - check (try to reproduce any miracle cancer cure paper)

- worshipping problem - check, there are kings and no one can take them down.

- diversity problem - check. In my department 80% of the professors and PhD and postdocs are women.

- moral and ethics are set arbitrarily - check. Morals? in Genetics? give me a brake

- there is a cut-throat publish-or-perish mentality - check, tell me something new

- discussions have become disrespectful - check. The time I saw Pavel Pezner giving a keynote lecture at ISMB and instead of showing his work he spend 70% of the time dressing down other people and trashing their work, Science died to me. And this was early 2000’s.

Machine learning won’t be the first field to notice it, and won’t be the last. Science is not scientific anymore.

Is this a new phenomenon?

Max Planck had this famous quote:

> A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die and a new generation grows up that is familiar with it. . . . An important scientific innovation rarely makes its way by gradually winning over and converting its opponents: it rarely happens that Saul becomes Paul. What does happen is that its opponents gradually die out, and that the growing generation is familiarized with the ideas from the beginning: another instance of the fact that the future lies with the youth.

I think this goes beyond science. People don't just change their minds. The only consistent way to get people to change is to wait until they die.

"Science progresses one funeral at a time.”

Not new at all, just more widespread today with all the sacred info and media.

One of the most eye-opening experiences I had as a new grad was sitting near to Bjarne Stroustrup during the OOPSLA 2006 keynote (? It’s been a long time), while 2000-or-so co-attendees repeatedly booed & hissed at him every time C++ was mentioned. It was weird & disconcerting. The only thing that made it bearable was how much Bjarne seemed to enjoy the whole thing.

How would you rephrase it? Does “science have a toxicity problem?”

Academia? Humans in general?

Maybe we can blame the anonymity of the internet.

Eric Weinstein has a theory that it's caused by the embedded growth obligations in our institutions.

I'm not sure it's the answer, but I think there is something seriously amiss with our institutions that causes them to all have a similar set of self silencing momentum. The amount of corruption that has been exposed in institutions over the last 20 years that has gone largely ignored in traditional media and inside this institutions themselves is staggering. Every time we hear institution X has a problem with Y, the story quietly disappears and there is no institutional change enacted.

https://bigthink.com/culture-religion/eric-weinstein-intelle...

My personal experience has been that, once an organization reaches some critical mass in terms of size, the primary goal seems to be to protect the institution itself rather than the stated mission it was created to serve. I’ve often wondered if this is the same mechanism that causes large organizations (e.g., churches, academic institutions) to go astray. I tend to think a diffusion of responsibility tends to go hand-in-hand with growth

"The bureaucracy expands to meet the needs of the ever expanding bureaucracy" or something to that effect.

I blame it on exceeding Dunbar's Number and creating different groups inside of an org, which now have different priorities and tribal affiliations, e.g. Ops vs. Engineering vs. Finance, or sub-teams inside of Engineering fighting holy wars about Tool [X].

I’ve heard it described as a “self licking ice cream cone”

I think the Dunbars number idea is interesting in terms of possibly describing how our organizational scaling has outpaced our biology

If you treat it as hazing the problem becomes more manageable.

Ultimately, scientists want to be understood and accepted by their peers and make friends, they are people after all.

A culture of abuse can start when the notion of exclusivity is accepted and outsiders want to join the group, whether that be in a single research group or within a field of study.

The problem is exacerbated by greedy individuals, and limited pools of funding to carry out research.

In turn, the greediest are the most exclusive, and the most prone to toxic behavior and chronic hazing.

Of all the debates and cries for LeCun's insensitivities and outrage over DeepMind's so-called "not quoting good research due to their deep racial bias", can someone comment on the scientific part? In particular, is PresGAN novel or worth quoting? Is fairness on algorithm instead of on dataset a good research direction?

don't get dragged into that false dichotomy. treating fairness as a merely technical problem is a cop out. in addition to looking at dataset and algo, look at the processes that generate data, how the data is collected/selected for the data set, and how the algo is deployed and to what end.

Can you elaborate on what you mean? I was interpreting “fairness” as “unbiased”, meaning if the process used to generate the data is biased, they are inherently unfair

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