On Mon, Feb 9, 2026 at 11:29 PM Stefan van der Walt via NumPy-Discussion < [email protected]> wrote:
> On Mon, Feb 9, 2026, at 13:58, Ralf Gommers via NumPy-Discussion wrote: > > > > On Mon, Feb 9, 2026 at 6:23 PM Matthew Brett via NumPy-Discussion < > [email protected]> wrote: > > I think it's correct that it's not sensible for policies to reflect > things like dislike of AI's use of energy or the effects on the > environment of AI data centers. However, it seems obvious to me that > it is sensible for policies to take into account the effect of AI on > learning. > > > Why would that be obvious? It seems incredibly presumptuous to decide for > other people what methods or tools they are or aren't allowed to use for > learning. We're not running a high school or university here. > > > The way I read Matthew's comment is not that we should prescribe how > people use their tools, but that we should be aware of the risks we are > facing, > This part is fine in the abstract - but that's also true for the environmental and societal impacts. > and also communicate those risks to contributors who want to use AI tools > to do NumPy development. > This doesn't necessarily make sense to me. If I try to figure out what all the hand waving means concretely - i.e., "where would we want to communicate such possible risks" - I think my answer is: probably nowhere. It doesn't quite fit in a policy on AI tool usage, which I'd hope would be short and to the point. And I don't think we want anything in the contributor guide at this point around AI tools for contributions, except for pointing at the policy? The conversation here is a bit too abstract for me, and mostly arguing against a straw man. Clearly if you outsource most thinking to a machine and do less thinking yourself, you learn less. If you use tools deliberately (one of many ways of doing that, from a blog post referencing that Anthropic paper: https://mitchellh.com/writing/my-ai-adoption-journey), that won't happen. Yes, you need to think about it as an individual using the tool. As is the case for any tool and way of working. If there is a concrete idea/proposal for a docs section, policy content, or anything like that, please clarify. Cheers, Ralf This also presumes that you, or we, are able to determine what usage of AI > tools helps or hinders learning. That is not possible at the level of > individuals: people can learn in very different ways, plus it will strongly > depend on how the tools are used. And even in the aggregate it's not > practically possible: most of the studies that have been referenced in this > and linked thread (a) are one-offs, and often inconsistent with each other, > and (b) already outdated, given how fast the field is developing. > > > It is true that things are moving fast, and while the original METR study > (which has been informally replicated in other settings) is perhaps > outdated, Anthropic's just-released paper shows a broadly similar trend. > Specifically, they show that time-to-solution is faster for junior > developers, but not so much for senior developers. They also show that > knowledge about the library is worse, having done a task with AI vs without. > > I'm sure, over time, we will figure out the best patterns for using AI and > how to avoid the worst traps. > > Best regards, > Stéfan > > _______________________________________________ > NumPy-Discussion mailing list -- [email protected] > To unsubscribe send an email to [email protected] > https://mail.python.org/mailman3//lists/numpy-discussion.python.org > Member address: [email protected] >
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