Dear Jim, Thanks for starting this stimulating discussion and everyone else for contributing.
In my experimentation with some models I have found - like yourself and other people replying - that these tools may be helpful for certain "non-critical" tasks to, indeed, increase the efficient use of human time (but, even then, there might be arguments to the contrary) but may also silently introduce problems which may be hard to spot. Like you, I do see the potential for these tools and I am very open to the idea of them helping in my work. Going to your more general initial points about the implications of AI and whether we'll all soon just write prompts to perform analyses (which is the most stimulating part of the conversation), I can think of at least three factors that make that problematic in the short run. 1. Most users who want to perform empirical analyses do not have the in-depth knowledge required for spotting problems in code, let alone in what's happening under the hood of a ready-made AI "app" 2. Often existing software relies both on peer-reviewed papers and on the domain expertise of scientist coders who developed the tools. Essentially, most users will trust software partly because of the academic accomplishments of the people who wrote it. It is an interesting topic and we may discuss about whether "it is right" but, to the point, at this stage it is unclear whether one can say these "AI models" have "expertise" and who is "accountable" (in a broad sense) for what they produce 3. There is a non-deterministic component in the behaviour of these models as they are today. For instance, providing a prompt worded differently may return different outputs. This raises all sort of issues in terms of reproducibility, trustworthiness and ability to actually describe what has been done (which is critical for things like drafting manuscripts and going through peer review as we know it today). To my understanding of these tools - which is admittedly quite limited - some of these issues stem from the nature itself of these models (e.g., the language component, the fact that they do have a context window that gets filled at some point, and so on). So, while I think they are very useful tools, I don't think they will be - in the very near future (say, one or two years) to replace existing software. On the longer term, maybe, who knows! Just my two cents, Carmelo Carmelo Fruciano Department of Biological, Geological and Environmental Sciences University of Catania https://www.fruciano.org/ ________________________________ From: '[email protected]' via Morphmet <[email protected]> Sent: Wednesday, 25 March 2026 03:07 To: Joe Felsenstein <[email protected]> Cc: Morphmet2 <[email protected]> Subject: Re: [MORPHMET2] Thoughts on morphometric software and AI Right, but the trend seems to be towards decreasing the efficiency of software/scripts/prompts execution and increasing the efficient use of human time. Human time may be more valuable (or just have a rapidly decreasing attention span). Oh, I did not have the foresight to save any of those old IBM 650 manuals. Too busy learning new stuff to think about the day when those might be fond memories. Of course, they are now all online (IBM 650 Manuals<https://piercefuller.com/collect/650man/index.html>) and available for the day I might be feeling nostalgic. Thanks for the reminder! Jim F. James Rohlf Distinguished Professor, Emeritus and Research Professor Depts: Anthropology and Ecology & Evolution Stony Brook University On 3/24/2026 3:10:21 PM, Joe Felsenstein <[email protected]> wrote: This is the first time you received an email from this sender ([email protected]). Exercise caution when clicking links, opening attachments or taking further action, before validating its authenticity. Jim noted that AI was: "Computationally less efficient (so much faster computers are required) but easier for humans to use with even less technical knowledge of how computers actually work." It is computationally less efficient if one has to do the AI interaction for each data set. But if it is just making Python or R code and giving you that, then not computationally much less efficient than just doing your own R or Python. (Reading Jim's list of successive stages, I was reminded of much past pain. I didn't quite start with the IBM 650 (instead iof CDC 1604 in 1961), but I have saved, from Jim Crow's lab, the user manuals for the 650.) Joe ---- Joe Felsenstein, [email protected]<mailto:[email protected]>, [email protected]<mailto:[email protected]> Department of Genome Sciences and Department of Biology, University of Washington, Seattle ---- PS Please do not use [email protected]<mailto:[email protected]>. It is an alias and mail systems often recognize that and think it is spam. -- You received this message because you are subscribed to the Google Groups "Morphmet" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]<mailto:[email protected]>. 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