[jacoblyles]

The truth machine is broken. How do we fix it?

And why is it that whenever I see a list of the "top 10 most important problems" to solve, this isn't on it? Most educated people take the veracity of published science as given, and we clearly know that's a false assumption.

I know we need more transparency in science - sharing of data and code, and negative results. But institutionally, I don't know how we get there with the tools we have.

Part of the reason the current system stays in place, despite failing at its charter mission, is billions of dollars of annual subsidies. Changing the way research dollars are allocated would change the structure of the academic enterprise, but that is incredibly hard to do. Few systems have as much momentum.

[pdonis]

Most educated people take the veracity of published science as given

That's the root problem right there.

[dnautics]

It's not just the subsidies, but how they are awarded - right on with the "structure of the academic enterprise".

Consider: To get promoted to professorship, you have to selected by slighly hoarier professors; to be selected, you have to have published works, which are (anonymously) reviewed by other professors, and be awarded grants with (anonymous) review committees of other professors. You probably went to grad school under the tutelage of professors in the same circle... And at least in the past scientists were sufficiently generalist that you had a wide pool of fellows who were reviewing your work at all stages; now we have siloed subdisciplines (like "chemical biology" - which, mind you is not the same as "biological chemistry" or "biochemistry"), and the emergence of "interdisciplinary research" which somehow instead of encouraging generalism, instead promoted dilettantes who couldn't hack it in either of their parent fields...

Is there any wonder why research is increasingly unreliable?

[pnathan]

So there's an interesting topic hidden in your comment. What is truth? I don't mean to ask that in a flippant way. I mean to ask it in a way that has an answer - or at least a reliable set of answers. Of course this is a philosophical debate of long standing, but it has a lot of relevance for today.

What do you mean by truth? How do you attain to truth?

Is truth what is objectively perceived? If so, how do you determine what is the shared subjective perception of the exterior world? Is truth possible to attain to? Should we instead focus on finding and sharing working(up to tolerance) models of the reality we encounter?

This is sort of a big debate in philosophy of science circles. You can see traces of it in Popper, Feyerabend, and a few others you can rummage up on Wikipedia. These are the questions that frame how you do research, how you present research, and the expectations of reliability of research.

[aharrison]

In my experience, when most engineering-oriented people use the word truth, they (wittingly or unwittling) mean the pragmatic definition of "allows us to make stronger-than-previous predictive models about something". Most of the argument in philosophy of science circles strikes me as meta-interesting, not eminently relevant to the practice of science.

Especially when dealing with psychology, a lot of those "what, exactly, is an electron" sort of deeply epistemological statements are not really asked, because we have enough trouble with the simplistic models we have.

So yeah, my recommendation (for what it is worth) is to always assume "most predictive model available" when someone says truth, and be aware that you are making that assumption and that simplification.

[pnathan]

That's a reasonable approach when talking with people who have sort of day to day experience with data and systems. Unfortunately, this doesn't per se hold true when talking with people from other disciplines. Some people hold truth as a platonic thing: it's either true or not true, and new research disproving old things implies falsehood, not a less accurate model. Tackling the elephant in that room, I'm not even talking about religious discussions, just normal discussions on physics research being found out.

A historian could speak more pertinently to this, but my understanding is that in 50s-60s "middle" USA, scientists were pretty much treated as oracles of divinity by a great deal of the common population.

[aharrison]

I agree and have run into that problem myself. Unfortunately, fixing that impression takes time and to my knowledge there isn't any real way to explain the problem with "Platonic truth" as a tangent off of a discussion around research journals, for instance. It requires a full step back and a couple hours of discussion to explain it at all, if you haven't been exposed to it before.

If anyone has any recommendations on that front, I am all ears.

[jerf]

Actually, I don't think we have to go down that rabbit hole. The current journal system is built such that a published paper is essentially a claim that this result is reproducible and statistically significant in some sense. A philosopher can and should then go and question what exactly that means in practice, whether it's the best standard, etc etc, but in the meantime, it is also acceptable to take the system's claims and observe that they do not match the reality of the journal system on its own terms, without any particular need to dig into philosophy.

In fact, I'm personally not convinced it's the best standard, but, nevertheless, it is a good start to hold journal papers to the standards they proclaim.

Worry about what the best theory is when they show some ability to implement any theory!

[frogpelt]

Truth is discovered. The process of arriving at the discovery of truth is where the perceptions and subjectivity play a role.

For example, water has certain properties based on the conditions surrounding it. These properties exist whether you know about them or not. If you can, through observation and/or measurement, discover these properties, you have discovered truth. If you never discover these properties, it does not affect the existence of the properties.

[Brakenshire]

> The truth machine is broken. How do we fix it?

> And why is it that whenever I see a list of the "top 10 most important problems" to solve, this isn't on it?

The truth machine has always been substantially broken, what has distinguished the scientific process is that it works at all. Our historical view of science suffers from absolutely enormous selection bias, in general we are only ever interested in following the stories which trace the threads of truth as they track through an absolute maelstrom of error, caused by nepotism, cronyism, prejudice, or a thousand other uncorrected human faults. 'Publish or perish' is only a modern progression of faults which have always been there.

That's not to say that finding improvements to the scientific process is not a hugely important question, but we should spare ourselves the drama of thinking our age has broken the system in some uniquely terrible way.

[snowwrestler]

We remember the big results of science: Newton's gravity, Einstein's special relativity, Darwin's natural selection, the Alvarez hypothesis of dinosaur extinction, etc. In doing so we forget the orders of magnitude more research results which were eventually proven wrong, or inconsequential.

Most of the papers that are wrong today will be caught eventually, or simply won't matter in the long run. The truth machine is not broken, it's just bigger and slower than most people realize.

[shanac]

Move to a bayesian approach for experiment design?