Session Design Submission Review

Yes

• International

Artificial intelligence (AI) is reshaping surgical education and clinical learning globally—yet implementation, governance, and outcomes vary widely across countries. This interactive panel convenes surgical educators from Brazil, Uganda, Nepal, and Saudi Arabia to surface what’s working now, where risks lie, and how faculty development can equip learners/surgical trainees and supervisors for responsible, high-value AI use.

Panelists will compare national/regional policies and ethical frameworks, highlighting how differing regulatory approaches influence AI use in curricula, assessment, scholarship, and clinical teaching and learning (e.g., documentation training, case preparation, literature appraisal, and research support). Panelists will showcase current educational applications: AI-assisted writing (manuscripts, grants), literature triage and quality checks, assessment and grading support (rubric alignment, formative feedback at scale, integrity safeguards), simulation and skills training with AI-guided feedback, and emerging OR “smart tower” capabilities that augment intraoperative performance. Discussion will explicitly balance opportunities with skepticism and risk management (bias, privacy, academic integrity, “skills atrophy,” and overreliance).

A major focus is faculty development and trainee preparedness: What baseline competencies should be taught in medical school and residency-equivalent programs? Which practical guardrails (syllabi language, policy templates, honor codes) help maintain scholarly integrity while leveraging AI productively? How can programs extend scarce expert feedback with AI-enabled coaching—without replacing human mentorship?

Panelists will also explore global surgery use cases: deploying AI tools to support education and research where resources are constrained, and sharing cross-border playbooks adaptable to local realities. The session includes brief “mini-demos” of practical tools for paper screening and proposal structuring, followed by a short Q&A.

Participants will leave with:

• A concise, country-by-country snapshot of policy and practice,
• A checklist for integrating AI into assessment, simulation, and scholarly work—while preserving core research and clinical reasoning skills.

Differentiate how national policies and ethical standards shape AI use in surgical education, including assessment.

Appraise benefits and risks of AI for writing, assessment, simulation, and clinical teaching and learning, including integrity and bias concerns.

Implement at least one practical AI-supported strategy (e.g., rubric-based feedback or literature-screening workflow) in their local context.

Evaluate whether an AI use case preserves trainees’ core research and clinical reasoning skills.