They view the framing of the MIT paper not just as bad science, but as a dangerous social tool that uses brain data to "consign people" to being less worthy or "stupid" for using cognitive aids. It flags the paper's alarmist findings as "pseudoscience" designed to provoke fear rather than provide rigorous insight. They highlight several "red flags" in the study's design: lack of a coherent scientific framework, methodological errors like typos, and reliance on invented, undefined terms such as "cognitive debt". They challenge the interpretation of EEG results, explaining that while the paper frames a 55% reduction in connectivity as evidence that a user's "brain sucks," such data could instead indicate increased neural efficiency, an alternative explanation the authors ignore. (EEG measures broad, noisy signals from outside the skull and is better understood as a rough index of brain state than as a precise window into specific thoughts or “intelligence.”)

The hosts condemn the study’s "bafflingly weak" logic and ableist rhetoric, and advise skepticism toward "science communicators" who might profit from selling hardware or supplements related to their findings: one of the paper's lead authors, Nataliya Kosmyna, is associated with the MIT Media Lab and the development of AttentivU, a pair of glasses designed to monitor brain activity and engagement. By framing LLM use as creating a "cognitive debt," the researchers create a market for their own solution: hardware that monitors and alerts the user when they are "under-engaged". The AttentivU system can provide haptic or audio feedback when attention drops, essentially acting as the "scaffold" for the very cognitive deficits the paper warns against. The research is part of the "Fluid Interfaces" group at MIT, which frequently develops Brain-Computer Interface (BCI) systems like "Brain Switch" and "AVP-EEG". This context supports the hosts' suspicion that the paper’s "cognitive debt" theory may be designed to justify a need for these monitoring tools.

It's a podcast, it goes back and forth between high and low density content. I tried listening to it while working and sometimes had to pause it because it got deep into e.g. explaining EEG, and then it's back to laughing at random stuff.

Summary using Claude 3.7 Sonnet:

"Your Brain On Chat GPT" Paper Analysis

In this transcript, neuroscientist Ashley and psychologist Cat critically analyze a controversial paper titled "Your Brain On Chat GPT" that claims to show negative brain effects from using large language models (LLMs).

Key Issues With the Paper:

Misleading EEG Analysis:

The paper uses EEG (electroencephalography) to claim it measures "brain connectivity" but misuses technical methods EEG is a blunt instrument that measures thousands of neurons simultaneously, not direct neural connections The paper confuses correlation of brain activity with actual physical connectivity Poor Research Design:

Small sample size (54 participants with many dropouts) Unclear time intervals between sessions Vague instructions to participants Controlled conditions don't represent real-world LLM use Overstated Claims:

Invented terms like "cognitive debt" without defining them Makes alarmist conclusions not supported by data Jumps from limited lab findings to broad claims about learning and cognition Methodological Problems:

Methods section includes unnecessary equations but lacks crucial details Contains basic errors like incorrect filter settings Fails to cite relevant established research on memory and learning No clear research questions or framework The Experts' Conclusion:

"These are questions worth asking... I do really want to know whether LLMs change the way my students think about problems. I do want to know if the offloading of cognitive tasks changes my own brain and my own cognition... We need to know these things as a society, but to pretend like this paper answers those questions is just completely wrong."

The experts emphasize that the paper appears designed to generate headlines rather than provide sound scientific insights, with potential conflicts of interest among authors who are associated with competing products.