Whose knowledge counts?
Models learn from what was recorded and digitized. Participants will look for the people, histories, and forms of knowledge left outside that record.
MIT Critical Data presents
AI as a Catalyst Bangkok
Reimagining Healthcare Innovation
A Thai-language workshop on healthcare AI, local context, and who gets to evaluate the systems that shape care.
A working room
Patients, artists, clinicians, technologists, and community representatives examining healthcare AI together.
AI as a Catalyst Bangkok treats people affected by healthcare systems as co-designers, not an audience. The workshop asks what an AI system misses when it travels across languages, cultures, and institutions.
Participants work in small, mixed groups. Each table compares model responses, names failure modes, and decides what local evidence and human judgment the system still needs.
The day will run in Thai, with translation support for the visiting team. Local facilitators will adapt the exercises and examples to the Thai context.
Part of
Siriraj x MIT Hacking Medicine 2026
In collaboration with
MIT Critical Data
Working language
Thai
Translation support will connect the visiting and local teams.
Planned room
60 to 80 participants
Round tables of six to eight, with one laptop per group.
Questions for the room
What changes in Thai?
Teams will compare similar prompts across Thai and English to see how language, training data, and cultural assumptions change an answer.
Problem or symptom?
Before proposing another tool, the room will ask whether it understands the underlying clinical, social, and institutional problem.
The program
A panel, a hands-on LLM-a-thon, and a shared debrief.
The organizers have confirmed a half-day format. Exact timing and the final room schedule are still being coordinated with the main event.
Workshop day
Monday, October 19
KX Knowledge Center's Auditorium · 7th floor · Bangkok
- OPEN Welcome, table introductions, and the questions guiding the room
- PANEL Opening discussion on AI, medicine, and local knowledge, moderated by Leo Celi
- LAB LLM-a-thon across models, prompts, user groups, and languages
- REPORT Table reflections on failure modes, risks, and practical safeguards
- CLOSE What participants want to test, change, or carry into future work
How the room works
Small tables, mixed perspectives
Groups of six to eight will work around round tables with a facilitator and at least one laptop. Non-technical and community perspectives are part of the evaluation, not an add-on after the technical work is finished.
Thai-led · hands-on · no real patient data
Inside the LLM-a-thon
Compare
Run the same healthcare scenario through several models, then compare what each answer emphasizes, assumes, omits, or gets wrong.
Evaluate
Build criteria that matter to patients, caregivers, clinicians, learners, and communities instead of relying on a single impression of quality.
Safeguard
Identify realistic uses, downstream risks, and the checks people need before a model can support healthcare decisions.
Workshop faculty & mentors
People shaping the Bangkok workshop.
Leo Anthony Celi
MIT Critical Data · Harvard Medical School
Thanasak Hoontrakul
MIT Hacking Medicine
Tiger Chaisutyakorn
MIT Critical Data · Clinical AI research
Nachanon Upariputtanggoon
Faculty of Medicine, Ramathibodi Hospital, Mahidol University
Thanjira Vimonanupong
MS in Narrative Medicine, Columbia University
Raffaele Giancotti
MIT Critical Data · Clinical AI research
Hannes Ill
MIT Critical Data · Clinical AI research
Wallis Mechuchep
Department of Preventive and Social Medicine, Faculty of Medicine, Srinakharinwirot University
Arnun Polsuksiri
Siriraj Informatics and Data Innovation Center (SiData+), Faculty of Medicine Siriraj Hospital
Narawitchz Wareekul
DDS. M.Sc.Digital and AI Technologies in Health Systems
Pornpubeth Harnthamtong
Siriraj Informatics and Data Innovation Center (SiData+), Faculty of Medicine Siriraj Hospital
Pimchanok (Pim) Worawattananon
MIT Sloan ASEAN Office (MSAO)
Jiramaetha Sinsuebchuea
AAAC Bangkok mentor
Siriya Sansri (Sonya)
Biological Science student, Mahidol University International College
Raphael Endaya
Biological Sciences, Mahidol University International College (MUIC)
Sean Ang
Biomedical Engineering alumnus, NUS · Guest Lecturer, NUS Business School
Chantra Satayathum
Doctor of Medicine, Poznan University of Medical Sciences
Duangjai Busayaratanakul
Biological Science, minor in Chemistry, Mahidol University International College
Thatchawanon Nantanaranon
Assistant Program Manager at KX, KMUTT, supporting startup incubation and acceleration
Jessica Vechbanyongratana
Bangkok Patana School · Faculty of Economics, Chulalongkorn University
Official event
Part of the Siriraj x MIT Hacking Medicine 2026 program.
Workshops take place on October 19 at KX Knowledge Center's Auditorium on the 7th floor. The main conference follows on October 20 at Grande Centre Point Lumphini.
Tickets and agenda
Use the official event website for current ticket options, the full agenda, and venue updates.
Open official event site