The LifeSciTrainers community invites you to join a special panel discussion exploring how generative AI may be changing learning in short-format professional development.
Much of what we know about the effects of generative AI on learning comes from studies conducted in secondary schools, colleges, and universities. Yet the audiences served by many LifeSciTrainers members differ substantially from learners in formal educational settings. Professional learners often arrive with prior expertise, specific workplace goals, immediate needs, and limited time. As a result, it is not always clear how findings from traditional educational research should be interpreted or applied in these contexts.
This discussion will bring together leaders from several major life science training organizations to examine what we know, what we do not know, and what questions deserve greater attention from the training community.
LifeSciTrainers hosts monthly discussions, talks, and trainings on any topic related to professional skill development for life scientists. Email info@lifescitrainers.org to participate or complete a submission form to sign up to give a short talk or suggest a topic.
Time and Date for Talks
LifeSciTrainers Community Calls – First Friday of the month; 11:00 AM U.S. Eastern/16:00 UTC
- Zoom: Register to attend.
- June 5, 2026 (see in your time zone)
Register on Zoom for our community call or Join our Slack for more details.
YouTube: YouTube Link
June 2026 Talk
Panelists
- Michelle Brazas, Scientific Director, Bioinformatics.ca / Ontario Institute for Cancer Research
- Toby Hodges, Director of Curriculum, The Carpentries
- Geert van Geest, Training Project Manager, Swiss Institute of Bioinformatics
Moderator
- Jason Williams, Assistant Director, Cold Spring Harbor Laboratory DNA Learning Center
Discussion Goals:
- Understand how the context of professional life science learners may differ from learners in formal educational settings.
- Explore how major life science training organizations are thinking about generative AI and its role in learning.
- Identify important unanswered questions about the effects of AI on short-format training and workforce development.
- Discuss what evidence currently exists and where additional research or data collection may be valuable.
- Help shape a community conversation that can move beyond anecdote toward reproducible observations and shared understanding.
Abstract
Generative AI is rapidly changing how people find information, learn new skills, write code, analyze data, and solve problems. However, most discussions about AI and learning have focused on students in formal educational settings. Comparatively little attention has been given to professional learners participating in short-format training.
For members of the LifeSciTrainers community, this distinction matters. Previous work, including the Bicycle Principles, has highlighted that short-format professional development operates in a unique educational environment. Learners often participate voluntarily, bring varying levels of prior experience, seek immediate application of new skills, and must balance learning with professional responsibilities. These characteristics may influence how generative AI supports—or interferes with—learning in ways that differ from traditional classrooms.
As training providers, we face important questions. Are professional learners using AI in ways that enhance learning and skill development? Are there circumstances where AI may create misunderstandings or impede deeper understanding? How should instructors advise learners about AI-assisted approaches? Are changes in training participation related to the growing availability of AI tools, or are other factors more important?
At present, many observations remain anecdotal. Training organizations report changes in learner expectations and, in some cases, participation patterns, but the causes and implications are not well understood. Before communities can develop evidence-based recommendations, it may be necessary to establish clearer definitions, identify meaningful measures, and determine what additional data should be collected.
This panel discussion is intended as an initial step in that process. Through an open conversation among training leaders and community members, we hope to identify key questions, clarify assumptions, and explore how the life science training community can productively study and respond to the growing influence of generative AI.
We encourage all members of the LifeSciTrainers community—and anyone who provides or benefits from short-format professional development in the life sciences—to join the conversation. Please bring your questions, relevant papers, observations, and experiences. Your perspectives will help shape this emerging discussion.