Co-authors: Shivansh Mundra, Gonzalo Aniano Porcile, Smit Marvaniya, Hany Farid A core part of what we do on the Trust Data Team at LinkedIn is create, deploy, and maintain models that detect and prevent many types of abuse. This spans the detection and prevention of fake accounts, account takeovers, and policy-violating content. We are constantly working to...
AI Articles
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Co-Authors: Keren Baruch, Grace Tang, Sakshi Jain, Sam Gong, Alex Murchison, Jon Adams, and Sara Harrington We recently shared our Responsible AI principles which summarized how we build using AI at LinkedIn. These principles guide our work and ensure we are consistent in how we use AI to (1) Advance Economic Opportunity, (2) Uphold Trust, (3) Promote Fairness...
- Topics:
- artificial intelligence,
- AI,
- Policy
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It’s been an exciting few months at LinkedIn, as our engineering and product teams have been working hard to build some new and advanced AI-powered experiences for our members and customers. I have the opportunity to sit at such a unique vantage point where I get to see first hand the work that went into setting the technology foundations - from the technical...
- Topics:
- artificial intelligence,
- machine learning,
- AI
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Co-authors: Sofus Macskássy, Carol Jin, Shiyong Lin, Xiaomin Wei, and Michael O’Neill When we think of skills, we think of the unique...
- Topics:
- AI,
- Skills,
- economic graph
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For our engineering teams, artificial intelligence (AI) is like oxygen - it powers every product we build and every experience we...
- Topics:
- artificial intelligence,
- AI,
- Data
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Co-authors - Blake Lawit and Ya Xu Editors Note: This post originally appeared on LinkedIn's Official Blog. LinkedIn was founded with...
- Topics:
- artificial intelligence,
- machine learning,
- AI,
- Policy,
- Data