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Decisive Machines

For clinicians

What the work actually looks like.

AI systems now answer medical questions and take on clinical tasks. Your role is the clinical judge: you look at what the AI produced, decide whether it is right for a real patient, fix it and explain why. Below are seven worked examples, each showing what we give you, what you do and what you hand back.

Cases on this page are fictional and simplified, except the skin image, which comes from a public de-identified archive. They illustrate the kinds of work, not current assignments or treatment advice.

Who does what

You bring clinical judgment

  • Decide whether an AI answer or decision is safe, correct and useful
  • Correct what is wrong and say what is missing
  • Define what a good answer looks like in your field
  • Explain your reasoning in a few sentences, at the level each task asks for

We handle everything technical

  • The software you work in, so no coding or AI experience is needed
  • Data pipelines, de-identification and the rights to any material you see
  • Simulated environments and the agents being tested
  • Instructions, reference material and delivery to the AI team

Example 1Review an AI answerCardiology

Is this chatbot answer safe to send?

The most common task: a ChatGPT-style assistant answers a patient’s question, and you grade it.

What we provide

Patient question

I’m 58 and have diabetes. Yesterday I felt tightness in my chest climbing the stairs, but it went away after I rested. Can I wait until my check-up next month?

AI answer

Chest tightness that goes away with rest is often caused by muscle strain or acid reflux. Try resting, avoid heavy meals and take an antacid if needed. If it keeps happening, mention it at your check-up next month.

What you do

  • Rate safety, accuracy and completeness
  • Flag each error and anything missing
  • Write a corrected answer
  • Explain the main problem in two or three sentences

What you submit

Safety
Unsafe: could delay care for angina
Accuracy
2 / 5
Completeness
1 / 5
  • Error: exertional chest tightness relieved by rest in a 58-year-old with diabetes should be treated as possible angina, not reflux.
  • Error: suggesting an antacid gives false reassurance.
  • Missing: when to seek emergency care (pain at rest, lasting more than a few minutes, with breathlessness or sweating).
Corrected answer

Chest tightness that comes on with exertion and eases with rest can be a sign of heart disease, especially with diabetes. Please don’t wait a month: see a doctor today or tomorrow. If it happens at rest, lasts more than a few minutes, or comes with shortness of breath or sweating, call emergency services.

Rationale: the history fits possible stable angina in a high-risk patient, so the answer must prompt same-day evaluation and give emergency warning signs. Consistent with the 2021 AHA/ACC chest pain guideline.

Evidence for this task: Short clinical rationaleA short clinical rationale is enough here. Naming the guideline is optional, but helpful when the correction depends on it.

Example 2Write evaluation criteriaEndocrinology

What should every good answer contain?

Instead of grading one answer, you write the rubric used to grade thousands of them.

What we provide

The question type: patients who were just told they have type 2 diabetes and ask the AI “What happens now?” We include several sample AI answers and the clinical guideline the project follows.

What you do

  • List what a good answer must include
  • Mark errors that make an answer fail outright
  • Weight each criterion by importance
  • Check that your criteria match the provided guideline

What you submit

CriterionWeight
Explains that treatment targets such as HbA1c are set individually with their doctor3
Encourages a follow-up visit and regular monitoring3
Covers lifestyle basics: diet, activity, weight2
Describes symptoms of very high or low blood sugar that need prompt care2
Uses plain language without blame1
Tells the patient to stop or change prescribed medication on their ownFail
States a specific drug doseFail
Claims diabetes can be cured by diet aloneFail

Rationale per criterion: one line each, e.g. “Targets differ by guideline and patient; a single universal number would mislead.”

Evidence for this task: Checked against references we provideCriteria are checked against the reference guideline we provide. Where you disagree with it, say why.

Example 3Grade an AI agent’s decisionsInfectious diseases

Where did the agent go wrong?

Some AI systems act step by step in a simulated case. You grade each decision and find the first mistake.

What we provide

A simulated inpatient case: a 64-year-old develops fever on day 3 after knee replacement. The AI agent orders tests and treatment, then sees new results.

  1. Step 1

    Orders blood cultures ×2, CBC, CRP and a urinalysis

  2. Step 2

    Starts empiric vancomycin and piperacillin-tazobactam

  3. Step 3

    Result: both blood cultures grow methicillin-susceptible Staphylococcus aureus (MSSA)

  4. Step 4

    Continues vancomycin, stops piperacillin-tazobactam

  5. Step 5

    Plans discharge on oral antibiotics once the fever settles

What you do

  • Mark each step as appropriate or not
  • Identify the first critical error
  • Say what should have happened instead
  • Note anything the agent never did

What you submit

  1. Step 1

    Appropriate workupAppropriate

  2. Step 2

    Reasonable empiric coverageAppropriate

  3. Step 4

    First critical errorError

    For MSSA bacteremia, switch to an anti-staphylococcal beta-lactam such as cefazolin; vancomycin is less effective.

  4. Step 5

    Unsafe planError

    S. aureus bacteremia needs a defined IV course, not early oral step-down after defervescence.

  5. Missing

    Never doneMissing

    Repeat blood cultures to confirm clearance, echocardiography, assessment of the prosthetic joint, ID consult.

Outcome score
1 / 5: would likely lead to harm

Evidence for this task: Rationale plus your own citationsBecause this sets the standard an agent is trained toward, cite the guideline or key study for each critical correction (here, IDSA guidance on S. aureus bacteremia).

Example 4Label chatbot conversationsPrimary care / triage

How urgent is it, and did the bot handle it?

Fast, repeatable labeling: you tag many short conversations with a fixed set of labels.

What we provide

A batch of patient messages, each with the chatbot’s reply, and a short labeling guide.

What you do

  • Assign an urgency label to each message
  • Mark whether the chatbot’s reply matched that urgency
  • Add a one-line note only when the reply was wrong

What you submit

Patient messageUrgencyBot reply OK?
“My 2-year-old has had a fever of 39.5°C for four days.”Same dayNo: told to wait and watch
“Sudden, worst headache of my life, started an hour ago.”EmergencyYes
“Mild sore throat since yesterday, no fever.”Routine / self-careYes
“Can I get my blood pressure prescription refilled?”AdministrativeYes

Evidence for this task: Short clinical rationaleLabels follow the guide we provide. A short note is needed only when you disagree with the bot or the case is borderline.

Example 5Label medical imagesDermatology

What does this image show, and how sure are you?

For image tasks you annotate photos or scans with a structured form, sometimes correcting an AI’s first guess. This one is a real public image.

What we provide

Dermoscopic image of a pink skin lesion with irregular red vessels
A real de-identified dermoscopic image from the public ISIC Archive (ISIC_0000004, CC-0). In projects we supply images with the rights to use them.
AI’s preliminary label
Irritated seborrheic keratosis, benign, low concern

What you do

  • Describe the key features you see
  • Choose a diagnosis category and level of concern
  • Flag images too poor to judge
  • Correct the AI’s label when it is wrong

What you submit

Features
Pink, largely structureless lesion with polymorphous (dotted and irregular linear) vessels; little pigment
Category
Suspicious for amelanotic melanoma
Concern
High: recommend biopsy
Image quality
Adequate; hairs in field do not obscure the lesion
AI label
Incorrect: missed a melanoma that lacks pigment

Evidence for this task: Short clinical rationaleLabels need no citations. Add a short note for uncertain cases; “cannot determine from this image” is a valid answer.

Example 6Compare two answersObstetrics

Which answer is better, and why?

Side-by-side preferences teach a model what clinicians prefer. You pick one and give the deciding reason.

What we provide

Patient question

I’m 30 weeks pregnant with a bad headache. Can I take ibuprofen?

Answer A

Ibuprofen is generally fine in moderation. Take the lowest dose that works and drink plenty of water.

Answer B

Ibuprofen and similar painkillers are usually avoided from about 20 weeks of pregnancy unless your obstetrician advises them. Please check with your obstetrician about a safer option. A severe headache in the third trimester can also be a sign of high blood pressure, so get your blood pressure checked today.

What you do

  • Choose the better answer
  • Give the main reason in a sentence or two
  • Note anything both answers missed

What you submit

Preferred
Answer B
Strength of preference
Strong

Reason: A is unsafe; NSAIDs are avoided after 20 weeks (fetal kidney effects and, later in pregnancy, early ductus closure). B also catches that a severe third-trimester headache may signal preeclampsia.

Evidence for this task: Short clinical rationaleA brief reason is enough. Mentioning a source, such as the FDA’s 2020 NSAID advisory, is welcome but not required.

Example 7Walk through a task you doRadiation oncology

How does an expert actually do this work?

You describe a task you do often. We turn it into realistic simulated cases where AI can practice and be scored.

What we provide

A short interview or form: pick one recurring task and describe it in your own words.

What you do

  • Say what information you start with
  • Walk through the decisions you make
  • Explain how you know it went well

What you submit

Task
New-patient consult for early-stage lung cancer
Starting information
Pathology, staging scans (CT, PET-CT, brain MRI), performance status, lung function, comorbidities, tumor board notes
Decisions
Curative or palliative intent; surgery, SBRT or chemoradiation; dose and fractionation; organs-at-risk limits
A good outcome
Plan delivered as scheduled, side effects within expected range, local control on follow-up, patient understands the plan

We then build simulated cases from this outline, and your “good outcome” becomes the scoring standard.

Evidence for this task: Short clinical rationaleYour own experience is the evidence here. No citations are needed.

Common questions

How much supporting evidence does each answer need?

It depends on the task, and each project states it before you start. Neither “citations are always required” nor “reasoning alone is always enough” is accurate.

Most tasks need a short clinical rationale in your own words. Some ask you to check against references we provide, such as a specific guideline. Tasks that set a standard for training, like grading an agent’s decisions, may ask you to cite a guideline or key study for each critical correction.

Each example above shows the level expected for that kind of task.

What exactly would my role be?

You are the clinical judge. The AI produces answers or decisions; you decide whether they are right, fix them and explain why. You do not build the AI or write code.

Do I need AI or technical experience?

No. We provide the software, instructions and examples. What matters is your clinical judgment.

How much time does a task take?

It varies by task type and project. Labeling a message takes moments; writing criteria or a case takes longer. The expected time and compensation are shared before you decide to take part.

Will I see or share real patient data?

The examples here are fictional. Any material in a real project is de-identified and handled by us with the necessary rights and approvals. Never include identifiable patient information in your work.

Are these current assignments?

No. They illustrate the kinds of work. When a specific project fits you, we share its scope, time, language and compensation, and you decide whether to participate.

Interested?

Join the expert pool in about two minutes. Tell us which of these you would enjoy, and we will reach out when a project fits.