Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant

>Masks work (CDC/FDA discouraged, then flip-flopped

Discouraging them early on was meant to avoid supply runs on quality masks. I agree it was a misstep on their part to promote the falsehood that masks do not prevent the wearer from being infected, and they never sufficiently walked this back, only perpetuating further myths like masks only protect others and not the wearer.

>Asking about "Hey if I got COVID before, that immunity is as robust if not more than vaccine, what evidence supports I need the vaccine?"

I also agree that over-reliance and perhaps overselling of vaccine effectiveness was a misstep, largely designed to get societal buy-in for ignoring COVID and "getting back to normal" as quickly as possible. The point that makes suspect those who were in favor of things like vitamins and exercise and so adamantly against measures like vaccines is that they did not go on to support other mitigations to promote health, like mask mandates and improvements in indoor air filtration and ventilation, which would have been more effective at reducing disease and promoting health. On the contrary, such activists were only interested in removing all measures and promoting increased disease.

> "they've always been wrong before"

In my opinion, they've almost always been right.

In the past two decades, we've seen the less-tech-savvy middle managers who devalued anything done on computer. They seemed to believe that doing graphic design or digital painting was just pressing a few buttons on the keyboard and the computer would do the job for you. These people were constantly mocked among online communities.

In programmers' world, you have seen people who said "how hard it could be? It's just adding a new button/changing the font/whatever..."

And strangely, in the end those tech muggles were the insightful ones.

I'd say the new problem is knowing when understanding is important and where it's okay to delegate.

It's similar to other abstractions in this way, but on a larger scale due to LLM having so many potential applications. And of course, due to the non-determinism.

ChatGPT got me over my imposter syndrome.

Back when it came out, it was all the rage at my company and we were all trying it for different things. After a while, I realized, if people were willing to accept the bullshit that LLMs put out, then I had been worrying about nothing all along.

That, plus getting an LLM to write anything with meaning takes putting the meaning in the prompt, pushed me to finally stop agonizing over emails and just write the damn things as simply and concisely as possible. I don't need a bullshit engine inflating my own words to say what I already know, just to have someone on the other end use the same bullshit engine to remove all that extra fluff to summarize. I can just write the point straight away and send it immediately.

You can literally just say anything in an email and nobody is going to say it's right or wrong, because they themselves don't know. Hell, they probably aren't even reading it. Most of the time I'm replying just to let someone know I read their email so they don't have to come to my office later and ask me if I read the email.

Every time someone says the latest release is a "game changer", I check back out of morbid curiosity. Still don't see what games have changed.

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.