Faysal AzizAI for Doctors
Practical AI literacy with clinical verification
An introductory workshop for doctors on AI tools, prompting, information synthesis, research exploration, confidentiality and verification.
Why this course
This one-day programme introduces practising doctors and healthcare leaders to practical AI literacy, focusing on general-purpose generative tools and their distinction from specialised healthcare systems. No programming or previous AI experience is required.
Participants practise instructions, context-setting and response refinement for professional writing, education, information organisation and literature exploration. Selected demonstrations use fictitious or appropriately de-identified material; they are not patient-specific diagnosis or treatment exercises.
Hallucinations, bias, outdated information, confidentiality and automation bias are central to the course. Participants inspect sources and citations and retain clinical responsibility. The programme does not teach AI development, clinical-system implementation or healthcare governance in depth.
Learning outcomes
The programme teaches participants to:
- Explain generative AI, language models and multimodal systems in practical terms.
- Distinguish general-purpose tools from purpose-specific healthcare AI and identify realistic professional-support uses.
- Recognise hallucination, bias, information currency and inappropriate certainty.
- Compare selected tools and data-handling arrangements.
- Write and refine prompts with instructions, relevant context, boundaries and output requirements.
- Review AI-assisted summaries, correspondence, teaching material and literature-discovery outputs.
- Verify sources, citations and clinical/scientific claims against authoritative evidence.
- Set personal use boundaries that preserve confidentiality and physician oversight.
Prerequisites
- Practising medical doctors, medical officers, specialists, healthcare leaders or physicians involved in clinical or administrative work.
- No previous artificial intelligence experience required.
- Basic computer and web-browser skills.
- Personal laptop or tablet with Internet connectivity recommended.
- Access to at least one mainstream generative AI platform recommended.
Exercises must not contain identifiable patient information. Any later real-world use requires an appropriately approved system and applicable institutional, legal and professional safeguards.
6 modules
011 — AI in medical and professional work1 topics
Concepts and physician responsibility
- Artificial Intelligence, Machine Learning and Generative AI
- Large Language Models and Multimodal AI
- AI versus Search Engines
- General-Purpose AI versus Medical AI
- Augmented Intelligence and the Role of the Physician
Potential professional-support uses
- Educational clinical-knowledge exploration, with independent verification.
- Medical Information Summarisation
- Literature and Research Exploration
- Professional Communication
- Draft patient-education material for clinician review, not direct unreviewed patient advice.
- Administrative and Documentation Support
- Support for personal learning and professional education; no accredited CME credit is implied.
022 — Limitations, clinical risk and confidentiality1 topics
AI limitations
- Hallucinations and Fabricated Information
- Incorrect or Incomplete Medical Responses
- Bias and Representation
- Knowledge Currency and Information Cut-offs
- Automation Bias and Over-Reliance
- Clinical Judgment and Human Oversight
Responsible data use
- Patient Information and Identifiable Data
- Public AI versus Organisational AI Platforms
- Data Handling Considerations
- Institutional Policies and Governance
- Professional Accountability
- Appropriate Disclosure and Transparency
033 — Choosing tools and writing useful prompts1 topics
Selected contemporary tools
- General-Purpose AI Assistants
- AI Search and Research Tools
- Document and PDF Analysis
- Multimodal features: capabilities, limits and appropriate data handling.
- Voice-Based Interaction
- Tool Selection Based on Task and Risk
Prompt foundations
- Clear Instructions
- Task Definition
- Relevant Context
- Constraints and Boundaries
- Output Requirements
- Audience and Communication Level
044 — Context and iterative improvement1 topics
Provide relevant context
- Providing Background Information
- Defining Professional Perspective
- Establishing Intended Audience
- Supplying Relevant Source Material
- Separating Facts from Instructions
- Managing Long Conversations and Context
Refine and compare responses
- Iterative Prompting
- Follow-Up Questions
- Clarification and Refinement
- Decomposition of Complex Tasks
- Comparing Alternative Responses
- Requesting Structured Outputs
055 — Selected practical workflows and evidence checks1 topics
Illustrative professional workflows
- Summarise prepared fictitious or de-identified medical/administrative examples and check omissions.
- Simplifying Complex Medical Information
- Drafting Professional Correspondence
- Preparing Teaching and Presentation Material
- Organising Clinical and Academic Information
- Brainstorm educational questions and differential considerations for an illustrative scenario; no real-patient diagnosis or treatment decision.
- Supporting Literature Exploration
Verification
- Fact Checking
- Source Verification
- Citation Verification
- Cross-check medical claims against current authoritative evidence and professional judgement.
- Recognising Unsupported Confidence
- Using Authoritative Medical Sources
066 — A personal working method5 topics
- Selecting Appropriate Tasks for AI
- Recognising Tasks Unsuitable for AI
- Building Reusable Prompt Patterns
- Maintaining Physician Oversight
- Identify suitable, approved uses and review requirements before adopting a workflow.
A programme built around your team.
Share your training goals and requirements.