Thread by @TenanATC

I apparently have a bit of a reputation as someone who is anti-machine learning or anti-AI when it comes to human research. This is a bit of misrepresentation of my views, and (I'd argue) a misrepresentation of the issues "statistics people" take with AI/ML as a whole.

(THREAD)

I personally think that AI/ML has a lot to bring to the table to enhance science, health and human performance. The problem is that the AI/ML crowd are over-selling their wares and often being disingenuous about what is current state-of-the art

2/10

Issue 1: CLAIMING EVERYTHING IS MACHINE LEARNING.

Just because AI/ML may use algebra or linear regression, doesn't mean it is AI/ML. Same goes for Nonlinear regression, correlation, logistic regression, or everything else that IS STATISTICS (or information theory, etc.)

3/10

It's cool if you use statistics and statistical concepts properly. Really, we're a big-tent kind of people. Just don't claim you invented something you clearly did not. And no, stringing together multiple correlations in an automated way doesn't make it extra special.

4/10

Issue 2: OMG THE HYPE MACHINE, MAKE IT STOP.

Again, a lot of really good stuff is being trialed with AI/ML. You don't need to oversell the genuinely good work and advances being pioneered. Here's the thing, most "statistics people" are allergic to hype.

5/10

Many human research statisticians work in areas of health where people can die or receive in appropriate treatments if we do our job wrong. It isn't to say we're perfect, but we work hard to be conservative and criticize our models so we're confident in the results.

6/10

This is, I think, the main reason statisticians have issues with the AI/ML crowd: we can smell snake oil. The really good and avant garde AI/ML work gets lumped in with the utter nonsense directed at VC's and the pop media.

7/10

Issue 3: THE SNAKE OIL IS SPREADING (tweet #7)

Again, there is good AI/ML work being done, but most of it is just re-branded statistics or 'stuff' hiding behind the term "proprietary". This snake oil is leaking into government, academia, etc in an attempt to be 'cool'

8/10

We're seeing this salesmanship more-and-more outside of traditional AI/ML technology circles. There are conference presentations or academic papers that call things like principle component analysis AI/ML... it was invented in 1901!
en.wikipedia.org/wiki/Principal…

9/10

Finally, many "stats people" are interested in applying AI/ML techniques and seeing where it can compliment our backgrounds and current work. We just get turned off by the bravado, hype and salesmanship that accompanies AI/ML. So yeah, we'll keep giving it a hard time.

10/FIN.