HUMAN DATA FOR FRONTIER AI

The next leap in AI
starts with you.

Create expert demonstrations, evaluate model responses, and challenge AI reasoning with problems from your field.

A few minutes to apply.
YOUR PERSPECTIVE IS THE DIFFERENCE.
Human dataModel evaluationExpert reasoning
THE WORK

Better training data
starts with expert judgment.

Contribute reference answers, assess reasoning, and surface failure cases. Turn specialist knowledge into useful data for AI training and evaluation.

What expert review looks likeIllustrative examples

Software engineering

Async execution
An answer to examine: “forEach waits for every async callback before continuing.”

What an expert notices: It doesn’t await the returned promises. The surrounding code can run before the work finishes.

Reference for Software engineering (opens in a new tab)

Writing & language

Meaning & precision
An answer to examine: “Only the analyst reviewed the report” means the same as “The analyst only reviewed the report.”

What an expert notices: Moving “only” changes its scope: who reviewed the report, or what the analyst did.

Scientific research

Interpreting evidence
An answer to examine: “A p-value of 0.03 means there is a 97% chance the hypothesis is true.”

What an expert notices: A p-value does not give the probability that a hypothesis is true. The inference goes beyond the result.

Reference for Scientific research (opens in a new tab)

Written to illustrate the work. Your application does not depend on these examples.

Where you can contribute.

Start with your strongest field. Project requirements and availability vary.

Remote, project-based opportunities. Share your availability when you apply.

YOUR APPLICATION

Apply to contribute
to human data projects.

Tell us about your field, your experience, and the time you can contribute.

Start your application No application fee. No CV upload.
01

Build your expert profile

Share your expertise, contact details, professional background, and availability. Review everything before you submit.

02

Get considered for relevant work

Relevant projects may require a skills assessment focused on your field and the type of data being created.

03

Decide what works for you

Review the scope, schedule, and compensation before accepting a project. Project work depends on your qualifications and current availability.

Before you apply.

A few things worth knowing.

Bring your experience to Clera.

Start with what you know.

Join the expert network