> "Greater levels of AI use were associated with modest increases in depressive symptoms"

to me ever so slightly implies causality via "increases ...", even though, as they are also very transparent about, this paper isn't about any causal mechanism. I feel like "associated with higher rates of depressive symptoms" might have read more neutrally and would have been in line with the results of their paper.

Not suggesting something intentional by the authors, of course, I just found it interesting how verbs subtly influence the meaning of things, at least for me.

But perhaps I'm also biased because I kind of intuitively believe that the causation is that depressive people enjoy talking to the AI, rather than AI being the cause of anything. I worry that any reverse interpretations will lead to an over-regulation of AI in such contexts.

> The highest estimates were observed among individuals using AI for personal use

and

> Incorporating individual terms for school, work, and personal use, only personal use was significantly associated with PHQ-9 (β = 0.31 [95% CI, 0.10-0.52]), while the other 2 were not

The thing I miss most about work (yes, you really can miss work) is collaborative problem-solving. At Microsoft, we called it “teddy bear debugging”—basically, self-explaining a problem out loud to clarify your thinking. [1]

These days, when I’m stuck, I open Claude Code and “talk it through.” That back-and-forth helps me reason through technical issues and scratches a bit of that collaborative itch that helped keep my depression in check.

[1]: https://economictimes.indiatimes.com/news/international/us/w...

Whereas generative AI is a recent thing. ~27% in 2021.

The correlation therefore is very very low and certainly not causal.

The question 'can AI make it worse' and this study didnt really do that.

Then consider confounders and this study is even weaker. Depression leads into AI usage, not the other way around.