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AI Transparency in LinkedIn's Hiring and Learning Solutions

A look into our AI development, data privacy, and compliance practices for LinkedIn Recruiter, Jobs, Hiring Integrations and Learning.

Responsible AI Principles ↓

AI Safety and Governance ↓

AI in Talent Strategy ↓

Resources & Product Spotlights ↓

Our commitment to building a trustworthy platform

Powered by the world’s most dynamic talent network, AI at LinkedIn unlocks new ways for customers and members to connect to opportunity with clarity, confidence, and control.

Guided by our Responsible AI Principles, we are committed to building AI systems that are trustworthy, safe, and human-centered.

These core Responsible AI Principles guide all our work at LinkedIn:

Advance Economic Opportunity
Uphold Trust
Promote Fairness and Inclusion
Provide Transparency
Embrace Accountability

Advance Economic Opportunity

Our products leverage a skills taxonomy to promote equal treatment—focusing on what members can do, not where they come from.

Uphold Trust

We take a proactive approach to privacy, security, and safety— ensuring our AI products earn trust through rigorous assessments, safeguards, and defense in depth strategies.

Promote Fairness and Inclusion

LinkedIn’s cross-functional Responsible AI team designs solutions and guardrails (e.g. our fair model analyzer and mitigation trainer) to ensure generative AI tools proactively address potential bias and discrimination.

Provide Transparency

We empower our customers with transparency and education, so they can make informed choices about how they engage with generative AI.

Embrace Accountability

We embed robust governance from the start– cross-disciplinary assessments and human oversight ensure our AI systems stay accountable, trustworthy, and aligned with our Responsible AI.

Looking for more information about our development practices?

Visit our Engineering Blog

Enterprise grade safety and governance

Building trustworthy AI at LinkedIn means mindfully innovating. From rigorous model testing to strong governance and legal compliance, we strive to build reliable and responsible AI tools for our customers.

Model Testing

LinkedIn's AI models undergo rigorous and recurring evaluations – including jailbreak, harmful or illegal content, hallucinations, stability, latency, and output quality – to track fulfillment failure rates and analyze user feedback signals to refine and enhance the AI experience.

Equal Treatment Testing

Responsible AI standards have been stood up at LinkedIn to address potential model bias. Any models used in our products are audited internally on a recurring basis and undergo testing to help ensure the security of our models in compliance with our policies.

Governance

Our comprehensive data access management policy includes a quarterly review of access rights to production environments based on roles, continuous monitoring for abnormal activity, an independent annual SOC 2 audit, and penetration testing.

Compliant with AI Regulations

LinkedIn complies with applicable law in the jurisdictions where our products are offered and we always seek to enable our customers to comply with their legal obligations when using our products.

Members Control their Data

LinkedIn members control their personal data to train generative AI models for content creation, anytime, right from LinkedIn. Additionally, we test our models and applications against potential unintended data extraction attacks.

Customer Story

"LinkedIn's security, trust, and seamless integration made company-wide buy-in easy – non-negotiables for us."

ATS Partner Story

How LinkedIn and Employ built an integration defined by responsible AI.

Read the LinkedIn + Employ story →

Responsible AI in Talent Strategy

As AI adoption speeds up, so can the risks. Establishing responsible AI principles that unify talent acquisition professionals around a shared purpose - prioritizing the candidate experience in every decision - can help ensure ethical, equitable, and harm-free hiring practices.

Watch the highlights between LinkedIn’s Legal Team and AMS’s Chief Innovation Officer at Talent Connect 2025 to explore ways to govern AI with transparency and accountability.

Watch the highlights →

Key takeaways:

AI is here to stay for both recruiters and candidates.
There is an opportunity cost to not using it.

Ethical AI principles are fundamental to successful talent strategies. Learn how to put them to work for your organization.

Hiring with impact requires the perfect blend of artificial + human intelligence.