The rapid emergence of generative AI presents novel opportunities and challenges for the physiotherapy profession, and meaningful engagement with this technology requires inclusive discussion and debate within our community. Traditional conference formats, where invited experts present their perspectives, often fail to facilitate this kind of inclusive engagement.
This conference event series aims to promote inclusive discussion on generative AI through participatory activities spanning the timeframe before, during and after the conference. Input will be gathered from a diversity of conference participants, avoiding over-reliance on invited expert opinion.
In the weeks prior to the conference, an initial survey with open-ended questions will be distributed to a small group of thought leaders in physiotherapy practice and education. The goal is to identify a limited set of themes and questions to help focus the upcoming discussions. Given the infancy of generative AI, no one can claim expertise, so gathering preliminary perspectives from a sample of engaged practitioners and educators will provide helpful direction.
The identified themes and questions will next be shared through the conference organisers' social networks and professional communities. This larger-scale survey will collect current thoughts and concerns about generative AI in a broader cross-section of the physiotherapy community, to be used as a foundation for the following events in the series.
These survey results will then inform a pre-conference workshop. Through small group dialogue, debate, and creative activities, participants will expand on the previously identified themes and questions. The workshop will culminate with each group proposing strategies to maximise opportunities and minimise risks from generative AI in physiotherapy practice and education.
Key insights from the pre-conference surveys and workshop will be presented at the focused symposium during the conference itself. This symposium will summarise survey results and workshop outputs, connecting them to produce a synthesis of community perspectives on generative AI. The symposium will also include panel discussions to further explore tensions, trade-offs and open questions.
Post-conference, the organisers will distribute a discussion framework that captures community input from the surveys, workshop and symposium. All conference participants will be invited to provide feedback on this framework through an online discussion platform with the goal of giving attendees a continued voice in the conversation after the conference concludes
This event series design intentionally avoids treating conference speakers as definitive experts on generative AI. Instead, attendees are positioned as co-creators whose experiences and insights can guide the profession's response to this potentially disruptive technology. The series weaves together activities before, during and after the conference to support sustained participation.
In focusing more on inclusive discussion than top-down expertise, this event series aims to empower practitioners to collaboratively steer their profession amidst the uncertainties of technological change. While specific strategies will evolve, physiotherapy's underlying ethic of human-centred, participatory practice can anchor the community through times of transformation.
Chair: Prof. Michael Rowe, Associate Professor for Digital Innovation, School of Health and Social Care, University of Lincoln.
Announcement of further collaborators to follow.

Preparation supported by Prof. Dr. Veronika Schoeb, from the Scientific Committee and Anita Hartmeier from the Programme Committe
References:
Masters, Ken. ‘Ethical Use of Artificial Intelligence in Health Professions Education: AMEE Guide No.158’. Medical Teacher, 13 March 2023, 1–11. https://doi.org/10.1080/0142159X.2023.2186203.
Lomis, Kimberly, Pamela Jeffries, Anthony Palatta, Melanie Sage, Javaid Sheikh, Carl Sheperis, and Alison Whelan. ‘Artificial Intelligence for Health Professions Educators’. NAM Perspectives 2021 (n.d.): 10.31478/202109a. https://doi.org/10.31478/202109a