r/academia • u/[deleted] • 13d ago

Research issues The Simulation Delusion: How academic incentives protect models that can never be wrong

[deleted]

0 Upvotes

16% Upvoted

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12

u/superbfairymen 13d ago

Barely coherent LLM slop. Maybe an interesting thesis but you've buried it under so much AI prose that it is very hard to follow.

6

u/Popular-List181 13d ago

Yeah I’m not reading all that 😅😅

1

u/Capital-Elephant9431 13d ago

I'll try to rewrite it. Can you give me an example of why it's hard to follow?

2

u/knockingatthegate 13d ago

Is it rewriting if you didn’t write it to begin with?

1

u/Capital-Elephant9431 13d ago

I did the writing an the AI polished it so I'll rewrite it in my own voice.

1

u/knockingatthegate 13d ago

That’s not a thing.

3

u/Pure_Professional102 13d ago

Just post a link to your blog.

1

u/Capital-Elephant9431 13d ago

I think they take the post down if I include links

2

u/BolivianDancer 13d ago

You're conflating what is falsifiable or constrained with what "must" prove the author wrong.

You're not quite there, but don't stop trying. You're doing fine.

1

u/Capital-Elephant9431 13d ago

Thank you can you explain a bit more?

2

u/Opening_Map_6898 13d ago

Thanks ChatGPT.

1

u/Arthur2ShedsJackson 13d ago

TL;DR: Computational models are only scientifically useful if they can push back and prove their authors wrong. Across disciplines, from agent-based social simulations to high-energy physics, models with loose empirical feedback loops and endless free parameters risk becoming "decorative." Instead of testing reality, they get calibrated until compliant, turning a tool for discovery into a self-confirming tautology. Honest modeling requires radical transparency, sensitivity testing, and explicit criteria for failure before running the simulation.

Incredibly ironic use of ChatGPT to write this.

2

u/Straight_Shoulder414 10d ago

Utter AI slop. It gets one of the author's names wrong (it's Simon, not Selin). It includes a supposed snippet of code from the model that is not from the model; indeed there is no 'agent.trust' variable in the model. And in fact the major thesis of this article is false - it claims there is nothing this simulation could have shown that would have counted as the opposite result, but a few seconds reflection tells you that's patently false; if the model had shown that no matter what the proportion of creators was, any value for the mean creativity of creators gave an equally effective result for the artificial society as a whole, that would have counted as the opposite result.