> The abstract is a word salad.

I strongly disagree with your statement. in fact the two sentences you quoted are quite clear. They aren’t written for a lay audience, true, but you don’t expect such in Cell. They don’t use any jargon at all.

Your own comment is also clear, but you wear your allegiance on your sleeve. The two sentences you quote make it clear that the paper is about people not technology — and wouldn’t even call the paper itself “AI skeptical”.

You may well be right that “AI skeptics will wildly cite this paper on social media”. But that is orthogonal to the paper itself.

It is a fairly well writen paper. Every field has its jargon, which to anyone who is unfamiliar with it, may sound like word salad. You could say the same thing about most ML paper for example.

I understood all the words there.

There is a big difference between jargon and, in general - presenting things using unnecessarily complicated language. Give this abstract to any editor, and I reassure you - they will rewrite it.

Even a simple GPT4o prompt ("Rewrite the following abstract for grammar, clarity, and readability.") gives

> This perspective highlights how epistemically unfounded and ethically harmful paradigms are reintroduced into scientific literature through machine learning (ML) and examines the connections between these two areas of failure. We use the resurgence of physiognomic methods, enabled by ML, as a case study to illustrate the damaging effects of ML-promoted junk science. We summarize and analyze several studies, focusing on how flawed research can lead to social harm. Additionally, we investigate various factors contributing to poor practices in applied ML. Finally, we provide resources on best research practices for developers and practitioners.

and for Claude 3.5 Sonnet:

> This perspective examines how scientifically unfounded and ethically problematic paradigms are reintroduced into scientific literature through machine learning (ML) techniques. We explore the connections between these two aspects of failure. Using the resurgence of physiognomic methods facilitated by ML as a case study, we demonstrate the harmful consequences of ML-legitimized pseudoscience. We provide a summary and analysis of several such studies, focusing on how unsound research can lead to social harm. Additionally, we investigate various factors contributing to poor practices in applied ML. Finally, we offer resources and recommendations for best research practices to guide developers and practitioners in the field.

Both versions are just an iteration; a human editor could do it better.

For context, I authored quite a few papers in quantum information theory. It takes work to present work in the simplest form possible.

For context, you have a consulting business, and spoke at a conference about AI in administering justice organized under auspices of recently ousted illiberal government of Poland.

Here's an abstract to one of your "papers": "The paper presents selected tools, as described by their developers. The list includes Hello Quantum, Hello Qiskit, Particle in a Box, Psi and Delta, QPlayLearn, Virtual Lab by Quantum Flytrap, Quantum Odyssey..."

Et patati et patata - no way to tell what you're about with your review other than enumeration and platitudes. Yet you criticize authors of a review paper (detail revealed by immediate next sentence, one you curiously decided to omit from quoting) that clearly state their angle first and at least have something to say. It's just not aligned with your opinions, nothing to do with writing.

You by the way demand "results" of a review paper. What were the research results of you playing quantum web games?

> I guess AI skeptics will wildly cite this paper on social media.

What is an AI skeptic? The context clues make it feel like a derogatory term.