While the causative effects are not straightforward to prove, LLMs definitely have addictive qualities... This will definitely have some negative effects to people with certain predespositons.. Also, LLMs tend to isolate more people - many health professionals will confirm that isolation is going to be detrimental for people for mental health.
So the skeptiscism in the comments about the findings is a bit puzzling.
I could not tell from the article whether the use of LLMs was allowed in the peer review. My guess would that it was not since this is unpublished research.
In general, what bothers me the most is the lack of transparency from researchers that use LLMs. Like, give me the text and explicitly mention that you used LLM for it. Even better, if one links the prompt history.
The lack of transparency causes greater damage than the using LLM for generating text. Otherwise, we will keep chasing the perfect AI detector which to me seems to be pointless.
I think it is the direction of the situation, rather than the state of things, that is concerning. The general direction is that everyone is incentivized and rewarded to look after their bottom line and personal gain and then everything else.
IMO, not caring about the wider impact of our actions is something that will keep happening at an increasing rate.
Biological systems have also designs that emerged through evolution. Although the complexity may seem at different scales, the main difference is the measurements you can do. Both biological and electrical circuits are dynamic systems that have designs that gives them emergent functional properties.
As the article describes imagine having the list of radio components instead only instead of their topology (wiring diagram). The problem of figuring out how a radio works with this information, if youbknow little about their design, becomes quite similar with how figuring out how a biological system works.
The absence of a design diagram and our inability to measure components at the molecular level without disturbing the state of a system is the main reason bilogical systems are so challenging to understand.
So the skeptiscism in the comments about the findings is a bit puzzling.