How verified doctors are bringing expert judgment to the heart of healthcare AI

AI is moving into more specialized applications, increasing demand for expert data that captures professional reasoning and in-depth decision-making.

Healthcare is one of the clearest examples, with OpenAI, Anthropic, and Google having all launched healthcare AI products in 2026. With 32% of adults now using chatbots for health advice, the quality of clinical reasoning behind model outputs is becoming increasingly important.

Healthcare AI teams need reliable access to the professionals who can provide that expertise.

Healthcare experts on Prolific

Prolific gives AI labs and researchers access to over 20,000 credentials-checked doctors, nurses, and other healthcare professionals across more than 35 specialties. This is part of Prolific’s Domain Experts offering, which also includes language experts, coding experts, and specialists in other fields.

With this pool of verified medical experts, you can bring clinicians into healthcare AI evaluation and judge models against the standards professionals would apply in practice. You can also collect expert data showing how healthcare professionals approach complex tasks and make decisions along the way.

“Healthcare AI increasingly depends on understanding how clinicians reason through difficult decisions,” explains Brennan Smith, VP of AI at Prolific. “Our pool of healthcare experts gives AI labs access to verified professionals who can bring that judgment directly into model training and evaluation.”

Verified healthcare expertise before your study starts

Finding somebody online who says they’re a doctor is easy enough, but knowing whether they have the qualifications and specialist experience your study requires is a much harder task.

Every healthcare professional in Prolific’s network undergoes a multi-step verification process before they can participate in healthcare studies.

Healthcare professionals join the pool via invitation only, and fewer than one in seven applicants reach the verification stage.

Once participants have passed Prolific’s 110+ identity and quality checks, we verify their professional credentials against registers such as the General Medical Council in the UK, the National Provider Identifier in the US, or the equivalent professional registry in their country.

Specialties are also checked, with the network currently featuring more than 35 specialties and sub-specialties that cover professionals such as GPs, radiologists, and neurosurgeons.

For AI evaluation studies, clinicians can also be assessed on their ability to judge model behavior in areas including diagnostic reasoning or treatment review. If your research depends on specialist judgment, you need to know the person providing it has the relevant expertise.

Want to see what expert healthcare data looks like? Request a sample.

Why more capable models need more specialized human data

Much of AI’s progress has been built on enormous amounts of general-purpose data. General data has been remarkably effective in equipping models with broad knowledge.

More advanced tasks create a different problem, however. Improving a model is more difficult when the quality of an answer depends on professional judgment.

A model can produce a medically plausible response while overlooking something a clinician would question immediately. Two answers could both be factually defensible, but one may be far more appropriate for the patient or the clinical setting. General internet data won’t always capture the difference, and automated grading can struggle in this area, too.

As AI systems take on more complex work, AI labs need data that shows how specialists make decisions. The signal can be found by observing a clinician’s priorities and understanding why they might reject an answer that initially seemed reasonable.

Evaluation runs into the same challenge. Strong benchmark performance only tell you so much about how a model behaves once an experienced clinician closely examines its reasoning.

How clinicians work through a task

Healthcare experts can evaluate a final model output, but you can also study the decision-making process the expert took to produce an answer.

For example, a clinician and an LLM might both look at an X-ray and identify a broken bone. The clinician can also examine the reasoning behind the model’s conclusion and catch assumptions that could cause problems in future cases, such as the model misreading the patient’s age or weight. AI labs can use that expert feedback to correct the model before the same reasoning is applied to a real patient.

You can compare an AI agent’s decision path with the approach taken by a clinician facing the same problem. Expert behavior can also be collected at different stages of a task, giving models feedback throughout the process rather than only when the final answer appears.

Healthcare studies on Prolific can also focus directly on evaluation.

A clinician might review AI-generated diagnostic reasoning for medical accuracy. Another study could ask healthcare professionals to assess whether patient-facing guidance is appropriate for the situation and identify responses that may cause harm if they reach a patient.

When the model focuses on a particular area of medicine, you can recruit professionals working in the relevant specialty. The output is then reviewed against the expectations of someone who handles the same type of work professionally.

Already using Prolific? Explore Domain Experts in the platform and recruit verified healthcare professionals for your next study.

How healthcare professionals contribute to AI studies in practice

We’ve seen firsthand how verified healthcare professionals contribute to demanding AI research. In one eight-month program, a frontier AI lab worked with us to recruit a bespoke panel of 20 healthcare clinicians, each one individually verified by Prolific.

The clinicians reviewed patient clinical images alongside genuine consumer health conversations, assessing whether each query was relevant and reviewing the quality of the accompanying image before providing their own clinical interpretation.

When more information was needed, they suggested follow-up questions. They also rewrote the AI assistant’s response when they felt the conversation should have been handled differently.

• The program ran across seven review waves, followed by a broader multimodal health study.
• Across the project, 492 study places were filled, and 465 submissions were approved. No submissions were rejected.
• The project maintained a stable panel of clinicians across repeated studies. Prior participation was tracked to ensure the same professionals weren’t overused.

Prolific’s growing Expert Network

Our dedicated pool of healthcare professionals is part of Prolific’s larger Expert Network, which provides AI labs with access to verified specialists when a general participant sample isn’t sufficient for the study. The network also includes professionals working across areas such as STEM and programming. Expertise is checked using professional credentials and skills assessments, or a combination of both, depending on the field.

If you already use Prolific, you can access Domain Experts from the Study setup or Participants page. 

• In Study setup, go to Recruit participants
• Add a screener
• Choose Domain Experts from the Premium tab and select the expertise you need. 
• You can also filter for Domain Experts through the API. 

As models improve their capabilities for more general tasks, further improvements increasingly depend on people with highly specific knowledge. AI labs need participants who understand the work well enough to identify a subtle failure and can demonstrate how a professional would approach the problem.

Healthcare is already a major part of that work on Prolific, with more than 1,200 healthcare-targeted studies run on the platform over the past 12 months. Our Expert Network of healthcare professionals gives you a more structured way to recruit the people you need, and you know every expert has been rigorously verified.

Put your healthcare AI in front of verified professionals

Small differences in medical reasoning can change what happens to a patient, making it difficult to bolt clinical expertise onto AI development at the very end. Prolific’s Expert Network lets AI labs bring real medical professionals into training and evaluation earlier, with studies built around the expertise their model needs.

Request a sample and see the variety of data healthcare experts can provide.