Michael Rowe

Trying to get better at getting better

Rejected AMEE abstract (workshop) | ChatGPT and its implications for health professions education

See this brief post on my reasons for sharing rejections.

Background

The release of ChatGPT in November 2022 was accompanied by an explosion of interest in both mainstream and academic media. It has simultaneously been described as the saviour of higher education, and the beginning of the end. The fact is, it could be both. ChatGPT can produce plausible responses to very challenging questions. These responses are clear, concise, and articulate. But sometimes, it’s wrong. Very wrong. And it can take a lot of time and expertise to untangle which threads of the response can be trusted. And this is the problem. While we know that human beings can also be wrong, we trust that they’re guided by a mental model that more-or-less aligns with our own. But ChatGPT has no such underlying philosophy, and we should therefore have little reason to trust its responses. This isn’t to say that ChatGPT has no value. On the contrary; chatbots and their foundational large language models (LLMs) have the potential to revolutionise health professions education. Just not in the way you may think.

Who should participate

This introductory workshop is aimed at educators interested in the implications of large language models, like ChatGPT, on health professions education.

Structure of workshop

  1. The workshop will begin with a short presentation on large language models (LLMs), and how they relate to the broader field of artificial intelligence research. The presentation will then narrow in on GPT-3, one of several high-profile LLMs, and its public-facing chatbot, ChatGPT.
  2. Participants will then have an open-ended session of experimentation with ChatGPT, guided by a range of prompts, designed to demonstrate where ChatGPT shines, and where it fails.
  3. Finally, participants will discuss the results of this experimentation, and identify how, if at all, ChatGPT might enhance their practice.

Intended outcomes

The outcomes of the workshop will be for participants to:

  • Leave with an entry-level understanding of how large language models generate their responses.
  • Explore ChatGPT responses. Specifically, to probe ChatGPT with prompts designed to demonstrate its strengths and expose its weaknesses.
  • Identify 3–5 ways in which ChatGPT may enhance our teaching, and support student learning.

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