You Can Now Get Paid To Train LinkedIn’s AI

LinkedIn is taking a new approach to building better AI; it’s recruiting members to help label and annotate data.
 

Instead of relying only on anonymous contractors, LinkedIn will invite professionals to apply their industry expertise to create high-quality, human-labelled training data, and yes, you can get paid for it.
 

This isn’t just manual tagging.

LinkedIn says it will vet applicants to make sure their background matches the annotation tasks, using profile details (education, licenses, work history) and an AI-driven conversational interview to verify expertise.
 

Learn more about the program on LinkedIn’s help page.

How the process works

Profile-based vetting and AI interviews

If you express interest, LinkedIn may use an AI-powered conversation to ask about your professional background and assess whether you’re the right fit for specific annotation projects.

The platform uses that information to match you with tasks that need specialized knowledge — for example, medical, legal, or financial labeling.

Annotating industry-specific data

Once matched, you’ll annotate examples so AI systems learn how people in your profession refer to tools, products, outcomes, and context.

This helps AI models provide more accurate recommendations, search results, and professional insights across LinkedIn, and potentially for other companies that license training data.

Why this matters (and why it’s complicated)

Benefits for professionals and AI quality

• Earn flexible, skill-based income by applying domain knowledge.

• Improve AI understanding of niche terms and context, leading to better matches and recommendations.

• Receive personalized feedback, LinkedIn may suggest profile improvements based on the interview.

Ethical and career considerations

There’s a tension here: by training AI, experts could also be helping build systems that automate parts of their own jobs.

The conversation about fairness, pay, and long-term impacts of AI labor is ongoing — see a deeper dive into the industry’s reliance on human labelers in this article from The Conversation.

What to consider before you sign up

• Confirm what tasks you’ll do, and how much you’ll be paid per assignment.

• Understand how your interview data will be used, LinkedIn says it will supplement your profile information to match you to projects and suggest profile updates, and will not use that info for other purposes without permission.

• Think about long-term implications for your role and industry.

LinkedIn’s approach leverages its unique access to professionals across industries to create higher-quality, specialized training data.

For people who want flexible income and enjoy applying domain expertise, it’s an attractive option, but it’s reasonable to weigh the potential trade-offs for your career.