Deep language algorithms predict semantic comprehension from brain activity
nature.com
nature.com
What's the point of Nature?
This article is the pinnacle of modern pseudoscience.
It's run by the same publishers as the journal Nature, but is a significantly lower impact journal.
Was this cross checked against arbitrary Inputs to GPT-2? I gather, with 1.5 Billion parameters, you can find a representative linear combination for everything.
The Bible Code comes to mind (https://en.wikipedia.org/wiki/Bible_code).
If something serious was on the line, with this type of analysis, you'd be fired.
Reading this it feels like we might as well give up on there being any science any more, tbh. For this to appear in Nature -- it feels like the rubicon has been crossed.
How can we expect the public not to be "anti-vax" (etc.), or otherwise scientifically competent in the basic tennets of modern science (experiment, refutation, peer review) -- if Nature isnt?
This just is a crystallization all the pseudoscience trends of the last (> decade): associative statistical analysis; assuming linearity; reification fallacy; failure to construct relevant hypotheses to test; no counterfactual analysis; no series attempt at falsification; trivial sample sizes; profound failure to provide a plausible mechanism; profound failure to understand the basic theory in the relevant domains; "AI"; "Neural"; "fMRI"; etc.; paper participates in a system of financial incentives largely benefitting industrial companies with investment in relevant tech; paper is designed to be a press release for those companies.
If I were to design and teach a lecture series on contemporary pseudoscience, I'd be half-inclined to spend it all on this paper alone. It's a spectacular confluence of these trends.
But likewise, we're in an era when "the man on the street" feels easy appealing to "the latest paper" delivered to him via an aside in a newspaper.
And at the same time, the "scientific" industry which produces this papers seems to have not merely taken the on-trend funding, but scarified its own methods to capture it.
In otherwords, "the man on the street" seems to have become the target demographic for a vast amount of science. From pop-psych to this, all designed to dazzle the lay reader.
Once only on popsci book shelves, now, everywhere in Nature!
> Scientific Reports is an online peer-reviewed open access scientific mega journal published by Nature Portfolio, covering all areas of the natural sciences. The journal was launched in 2011.[1] The journal has announced that their aim is to assess solely the scientific validity of a submitted paper, rather than its perceived importance, significance or impact.[2]
Of that last line, this is quite literally the opposite. The only grounds to accept this paper is how on-trend this topic is. The "scientific validity" of correlating floating point averages over historical text documents, and brain blood flow... is, c. 0%
Note that this is exactly the wrong way to form and attempt to refute a scientific hypothesis. The authors don't start with some new observations that require explanation, they start with a hypothesis already fully-formed ("...these models encode information that relates to human comprehension..."), and then go out and collect observations to confirm this hypothesis.
I'm sure that if asked, the authors would say that they are simply trying to answer a scientific question, but it's obvious that they already have the answer they want and they're just trying to find data to support it. The problem of course is that if one is already convinced of the answer, one can always find evidence to "prove" it. It's a kind of confirmation bias.
To quote the authors: ”We propose that deep neural networks encode a variety of features…”
Run GPT on other inputs, run fMRIs on other inputs: call that dataset, (G, F).
Now consider all possible subsets, (g_i, f_i) in (G, F) ...
How many show correlation in their choice of NN property, and their choice of brain property (ie., blood flow)?
My guess: *many*.
This is trivial to refute if you have any sense of the scientific method. Construct the converse hypothesis and test it. They didnt.
edit: https://mitpress.mit.edu/9780262680530/parallel-distributed-...
If it holds up, you could monitor kids in class, dementia patients.. wild. Start your startup engines.
Extrapolating, this also suggests neurolink should work and you can probably do it with less invasive tech.
From the paper:
”However, whether these models encode, retrieve and pay attention to information that specifically relates to behavior in general, and to comprehension in particular remains controversial”
edit: Mapping from a statistical model directly to one specific individual’s brain may turn out to be intractable for things like brain implants.
But, the chances are pretty good that there will be strides made in unexpected areas.
From the paper: ”These advances raise a major question: do these algorithms process language like the human brain? Recent studies suggest that they partially do: the hidden representations of various deep neural networks have shown to linearly predict single-sample fMRI, MEG, and intracranial responses to spoken and written texts.”
>Manuscripts are not assessed based on their perceived importance, significance or impact https://www.nature.com/srep/guide-to-referees#criteria
It's a good thing for science that not all journals are impact chasers. Scientists are by definition not perfectly reliable evaluators of impact, because science is about exploring the unknown. Publishing work that's only passed a technically focused peer review allows for unexpected impact.
>It's a good thing for science
Maybe, but we should treat them like arXiv.org type e-Print archive. People are posting them to HN and thinking that because it's Nature.com site it's solid science.
When I originally read the comment I had no idea if it was a genuine comment, some kind of summary, or a legit quote from the article. Quotation marks exist for a reason and would have prevented this (and still can: it is possible to edit a comment). I was trying to be helpful, not negative in any way.