What We're Researching
We are running a paid study to evaluate the quality and accuracy of machine learning model outputs. This work directly informs how AI systems handle complex research tasks and domain-specific prompts. By analyzing these generated responses, we can better understand where current models succeed and where they require further refinement.
How It Works
Participants will review a series of machine learning model outputs generated in response to specific research prompts. You will evaluate these responses for accuracy, relevance, and overall quality using a structured rating system. The project involves approximately five hours of independent work, which you can complete asynchronously. You will also provide brief written justifications for your ratings to help us understand your evaluation process.
Who This Is For
We are looking for subject matter experts across various academic and professional domains with a strong eye for detail. We welcome researchers, data analysts, technical writers, and domain specialists who can critically assess complex information. If you have experience evaluating technical content or research data, you will be a great fit for this project.
What You'll Do
Review machine learning model outputs across a variety of research tasks
Rate AI-generated responses for accuracy, relevance, and factual correctness
Provide clear written justifications for your evaluation scores
Complete approximately five hours of asynchronous evaluation work
Who Should Apply
Professional or academic expertise in a specialized domain
Strong critical thinking and analytical skills
Comfortable reading and assessing complex technical or research-focused text
Ability to commit approximately five hours to complete the evaluation tasks
Compensation
$75 per hour
Ready to participate?
About Terac
Terac is building the world's largest pool of vetted human experts for AI. Researchers, AI labs, and product teams use Terac to recruit, screen, and pay study participants across industries, languages, and skill sets.
Learn more at terac.com or on YouTube at @jointerac.