The Deepening Crisis of Post-Modern Science

  • Date: 06/04/17
  • Judith Curry, Climate Etc.

‘That we now live in the grip of post-factualism would seem naturally repellent to most physicists. But in championing theory without demanding empirical evidence, we’re guilty of ignoring the facts ourselves.’

Two excellent articles about science, facts, and post-factualism.

Sabine Hossenfelder just published a superb essay in Nature Physics, entitled Science needs reason to be trusted.  Subtitle: That we now live in the grip of post-factualism would seem naturally repellent to most physicists. But in championing theory without demanding empirical evidence, we’re guilty of ignoring the facts ourselves.

Most unfortunately, this essay is behind paywall. [read here via readcube]. Here are some excerpts:

I’m afraid the public has good reasons to mistrust scientists and — sad but true — I myself find it increasingly hard to trust them too.

The reproducibility crisis is a problem, but at least it’s a problem that has been recognized and is being addressed. From where I sit, however, in a research area that can be roughly summarized as the foundations of physics, I have a front-row seat to a much bigger problem.

But we have a crisis of an entirely different sort: we produce a huge amount of new theories and yet none of them is ever empirically confirmed. Let’s call it the overproduction crisis. We use the approved methods of our field, see they don’t work, but don’t draw consequences. Like a fly hitting the window pane, we repeat ourselves over and over again, expecting different results. But my issue isn’t the snail’s pace of progress per se, it’s that the current practices in theory development signal a failure of the scientific method.

In particle physics, jumping on a hot topic in the hope of collecting citations is so common it even has a name: ‘ambulance chasing’, referring to the practice of lawyers following ambulances in the hope of finding new clients. What worries me is that this flood of papers is a stunning demonstration for how useless the current quality criteria are. 

Current observational data can’t distinguish the different models. And even if new data comes in, there will still be infinitely many models left to write papers about. The likelihood that any of these models describes reality is vanishingly small — it’s roulette on an infinitely large table. But according to current quality criteria, that’s first-rate science.  The accepted practice is instead to adjust the model so that it continues to agree with the lack of empirical support.

But in the absence of good quality measures, the ideas that catch on are the most fruitful ones, even though there is no evidence that a theory’s fruitfulness correlates with its correctness.

The underlying problem is that science, like any other collective human activity, is subject to social dynamics. Unlike most other collective human activities, however, scientists should acknowledge threats to their objective judgment and find ways to avoid them. But this doesn’t happen.

If scientists are selectively exposed to information from likeminded peers, if they are punished for not attracting enough attention, if they face hurdles to leave a research area when its promise declines, they can’t be counted on to be objective. That’s the situation we’re in today — and we have accepted it.

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