Lots of great discussion here, and glad to see the community engagement around this important topic. I posted some comments on the GitHub PR but wanted to re-share these two links here as I think they are worth the time (sorry, the video is 2hrs 🫠!)
https://garymarcus.substack.com/p/decoding-and-debunking-hard-forks https://www.youtube.com/watch?v=EWvNQjAaOHw Cheers, -- *Allen Lee* Senior Global Futures Scientist School of Complex Adaptive Systems Arizona State University Mail Code: 2701 Tempe, AZ 85287-2701 *p: *480-727-4646 *email: *allen....@asu.edu *git: *https://github.com/alee *orcid: *https://orcid.org/0000-0002-6523-6079 Center for Behavior, Institutions, and the Environment <https://complexity.asu.edu/cbie> Network for Computational Modeling in the Social and Ecological Sciences <https://www.comses.net/> On Tue, Mar 18, 2025 at 5:40 PM Paola Di Maio <paola.dim...@gmail.com> wrote: > I do teach prompt engineering, and would encourage a Carpentries > module/course/lesson > The question really is learning how to use AI intelligently and critically > > Materials on how to use AI for learning to code are already plenty but > how to work with specific platforms and packages may need refining/require > a more specialised LLM > [image: image.png] > > In theory, the LLM can learn from your interaction, so plenty of scope > for Carpentries Instructors to teach the LLM how to code as well :-) > > > On Wed, Mar 19, 2025 at 8:26 AM Reed A. Cartwright <cartwri...@asu.edu> > wrote: > >> My experience with using AI for coding is that if you are not asking it >> questions from an algorithms class or similar, you get a lot of >> hallucinations that do not work, e.g. R packages that don't exist. You can >> ask it follow up questions and it will eventually fix the issues, but that >> requires having a firm mental model and the ability to read code and know >> how it would work in practice. >> >> I can see the utility of a Prompt Engineering Carpentries lesson, but I >> have no idea how to properly teach prompt engineering. >> >> -- >> Reed A. Cartwright, PhD >> Associate Professor of Genomics, Evolution, and Bioinformatics >> School of Life Sciences and The Biodesign Institute >> Arizona State University >> Address: The Biodesign Institute, PO Box 876401, Tempe, AZ 85287-6401 USA >> Packages: The Biodesign Institute, 1001 S. McAllister Ave, Tempe, AZ >> 85287-6401 USA >> Office: Biodesign B-220C, 1-480-965-9949 >> Website: http://cartwrig.ht/ >> <https://urldefense.com/v3/__http://cartwrig.ht/__;!!IKRxdwAv5BmarQ!eK7h6FQJomgaZ0TF4wrpnUvBl0tbFH_vtWOXP7s_vKvM_jV2jEQj951z1w0YCG4WV87pX9F3uxj5he-kAHagHY3Omg$> >> >> >> On Tue, Mar 18, 2025 at 5:04 PM Paul Harrison via discuss < >> discuss@lists.carpentries.org> wrote: >> >>> >>> I wonder if more could be said about *how* to demonstrate the use of >>> LLMs. All the bad things people do with LLMs (and Stack Overflow) are >>> opportunities to demonstrate a better way. >>> >>> So we could show getting some code from an LLM, and then the steps of >>> examining variables and understanding their types, inserting debugging >>> "print" statements, looking up documentation, considering alternative >>> solutions, and explaining our thought process. >>> >>> It's not so different from the skills needed to read other people's code. >>> >>> Since LLM output is random it's hard to script this fully, but that also >>> seems in keeping with the Carpentries workshop format. >>> >>> This list is for the purpose of general discussion about The Carpentries > including community activities, upcoming events, and announcements. 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