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Guide to physician roles in AI training, medical data annotation, and clinical validation of AI systems.
AI clinical evaluation involves physicians providing medical expertise to train and validate AI systems. Leading AI labs and technology companies partner with physicians to develop and evaluate advanced AI systems for medicine-specific research tasks and to simulate real-world medical workflows.
As an AI tutor or medical expert, you might:
- Prompt writing: Craft medical questions and scenarios to test AI capabilities
- Response evaluation: Review AI-generated answers for accuracy, safety, and clinical reasoning
- QA/Quality assurance: Identify errors, inconsistencies, and gaps in AI medical knowledge
- Dataset labeling: Annotate medical data to train machine learning models
- Ground truth generation: Provide expert answers to complex clinical questions
- EMR workflow validation: Review AI-generated content related to clinical documentation
- Scenario development: Create case-based scenarios that simulate real-world clinical workflows
Some projects focus on specific areas like EMR systems (Epic, Cerner, etc.), requiring hands-on experience with clinical documentation and patient record workflows.
These roles are typically fully remote and offer flexible scheduling, making them ideal side gigs for practicing physicians. Most projects allow you to work on your own schedule with a minimum weekly hour commitment (often 10-20+ hours). Engagements range from short-term projects (4-8 weeks) to ongoing relationships.
Unlike data science roles, AI evaluation does NOT require coding skills. The value comes from clinical expertise, not technical ability.
Rates vary widely depending on the project, company, your specialty, and experience level:
For detailed compensation data from real physician experiences, see our AI evaluation compensation survey results.
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