this post was submitted on 27 Aug 2026
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[–] daannii@lemmy.world 1 points 5 hours ago

Agree. And also. Scientists have been using and running statistical software analysis since like the late 70s. Everyone acts like we don't have tried and true methods already.

Some machine learning might be useful though in research but idk if it's fair to call it "ai". Idk it depends on your definition.

Actually in the research I do, I was looking into papers that measured a lot more variables than what is commonly done. (Usually two things are compared) And the authors used a formula to determine interactive effects based on which factors aligned or didn't align and by how much.

This type of statistics is close to how ai works as it gives "weights" to different inputs.

But this was a method the authors came up with and they fully disclosed how it worked and acknowledged it was only one of many approaches to determining these interactive effects.


The research I'm referring to was about vision. Accommodation and vergence. Which function together. And you can manipulate them so they don't match and see which one has a stronger influence on the perception of depth. However, many other factors effect depth perception. But it's nearly impossible to study how these each contribute when multiples other factors are present. Some matching the true depth. Some giving an incorrect cue. Which cue, when wrong, overrides the correct one? If two matching cure are present, is there one cue that's wrong, but has a stronger impact on the perception ?

These things are difficult to determine without literally thousands of studies.