AI programming tools may mean rethinking compsci education

Analysis While the legal and ethical implications of assistive AI models like GitHub's Copilot continue to be sorted out, computer scientists continue to find uses for large language models and urge educators to adapt. Brett A. Becker, assistant professor at University College Dublin in Ireland, provided The Register with pre-publication copies of two research papers exploring the educational risks and opportunities of AI tools for generating programming code. The papers have been accepted at the 2023 SIGCSE Technical Symposium on Computer Science Education, to be held March 15 to 18 in Toronto, Canada. In June, GitHub Copilot, a machine learning tool that automatically suggests programming code in response to contextual prompts, emerged from a year long technical preview, just as concerns about the way its OpenAI Codex model was trained and the implications of AI models for society coalesced into focused opposition. In "Programming Is Hard – Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generation" [PDF], Becker and co-authors Paul Denny (University of Auckland, New Zealand), James Finnie-Ansley (University of Auckland), Andrew Luxton-Reilly (University of Auckland), James Prather (Abilene Christian University, USA), and Eddie Antonio Santos (University College Dublin) argue that the educational community needs to deal with the immediate opportunities and challenges presented by AI-driven code generation tools.