How LinkedIn Uses Member Data and AI Training

LinkedIn's AI training settings don't affect all users equally. Did you notice that LinkedIn will share UK users' data with Microsoft, but not EEA users? In this video, I look at the background, the broader context, and the details. LinkedIn first floated the idea of training its AI models on users' personal data last summer and has since encountered several bumps in the road. Complaints were submitted to regulators in Ireland and the UK, and the company responded by putting the project on hold for EEA and UK users in September 2024. Incidentally, the EDPB published an opinion in December on the use of "legitimate interests" to train AI models. The Board did not rule out that this could be lawful on a case-by-case basis, with safeguards attached, and people's reasonable expectations taken into account. -- Other social media platforms have met with similar issues. Meta's AI training saga is too complicated to recount here in full, but suffice to say that the company also paused and has now resumed its policy of relying on "legitimate interests" for this processing. X faced court action from the Irish DPC and gave an undertaking confirming that it would not use EU users' data in this way. -- There are some interesting details around how LinkedIn plans to share data with Microsoft: • UK: Profile data and public content may be shared with Microsoft for model training, unless the user opts out. • EU/EEA/Switzerland: The data will be used by LinkedIn itself for AI training, but there's no mention of any sharing with Microsoft. • Canada/Hong Kong: There's a much more expansive approach to sharing data with Microsoft, including for advertising purposes (profile data, feed activity, ad engagement), but there's an opt-out available. • Other countries (including the US): There's no explicit opt-out. If you don't like it, close your account. -- As a LinkedIn user, you have until 3 November to opt out. If you opted out the last time LinkedIn tried this, check your settings. As a data protection professional, you now have another interesting test case about whether "legitimate interests" will stand up for large-scale AI training.

Little surprise ... LinkedIn is using your data to feed its AI models, unless you opt out (explanation below). Since November 3, 2025, LinkedIn has begun using member data in several regions (EU, UK, Canada, Switzerland, Hong Kong…) to train its generative AI models, without asking for explicit consent. 📊 What’s being used: - Your profile info (name, title, education, skills, etc.) - Your posts, comments, and poll answers - Job applications and prompts entered into LinkedIn’s AI features 🚫 What’s not being used (according to LinkedIn): - Private messages (InMail, DMs) - Login credentials, payments, or salary details 🧨 Here’s the issue: This setting is ON by default. You’re automatically included unless you opt out. And here’s where it gets worse - In January 2024, a class action lawsuit was filed in California against LinkedIn. Premium users claim their private InMails were used for AI training before the company updated its privacy policy to reflect this change. The lawsuit alleges that LinkedIn quietly updated its terms to “cover its tracks,” confirming that opting out “does not affect training that has already taken place.” For now, there is no official proof of that. 🧭 How to opt out: Go to: Settings & Privacy → Data Privacy → Data for Generative AI Improvement ➡️ Turn the toggle OFF Note: this only stops future training. Data already used can’t be withdrawn. 💡 In short: ✔ LinkedIn is using your data to train AI by default ✔ A lawsuit already accuses them of mishandling private messages ✔ You can opt out - but few people know about it 🔒 Transparency shouldn’t be optional. If you care about your data, go check that setting right now, and share this post so others can too. #GenAI #Privacy #LinkedIn #DataProtection #GenerativeAI #Ethics

LinkedIn algorithms will deprioritize this post but important to know the data privacy changes that Linkedin announced recently. And what can you do stay safe. 1. LinkedIn will use member data by default starting November 3, 2025, to train generative AI models that power platform features like content creation and job recommendations. Users can opt out in settings. 2. Types of data used for AI training include profile details (job title, skills, education), public posts, comments, articles, group activities, and job application-related data (resumes, screening questions). Private messages and sensitive information (passwords, payment data) are excluded. 3. LinkedIn expanded data sharing with Microsoft and other LinkedIn affiliates for AI development, advertising, and service improvements. Shared data includes profile information, platform usage, and activity data, under updated legal and privacy terms. 4. Users maintain control over their data through privacy settings, including options to opt out of AI training data use and control affiliate data sharing. Regional privacy laws apply, with stronger protections in the EU, UK, Canada, and other jurisdictions. Here's how to Opt-Out: #1 Disable 'Data for Generative AI Improvement' from: https://lnkd.in/gJPaXew9 #2 Disable 'Share data with affiliates and partners' from: https://lnkd.in/g5fF5x7n #AILiteracy #DataPrivacy #LinkedInChanges #OptOut AI&Beyond Jaspreet Bindra

𝗘𝘃𝗲𝗿 𝗪𝗼𝗻𝗱𝗲𝗿𝗲𝗱 𝗵𝗼𝘄 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗨𝘀𝗲𝘀 𝗚𝗲𝗻𝗔𝗜 𝘁𝗼 𝗘𝗻𝗵𝗮𝗻𝗰𝗲 𝗦𝗲𝗮𝗿𝗰𝗵 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 LinkedIn's search engine doesn’t just look for keywords—it 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝘀 𝘆𝗼𝘂𝗿 𝗾𝘂𝗲𝗿𝗶𝗲𝘀, 𝗲𝘃𝗲𝗻 𝘄𝗵𝗲𝗻 𝘁𝗵𝗲𝘆’𝗿𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘅, like "how to ask for a raise?" or "dropout in AI." Here’s a peek into the innovative GenAI-powered content search engine that makes it happen: ------------------ 🚀 What’s New? LinkedIn introduced 𝘀𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝘀𝗲𝗮𝗿𝗰𝗵 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 to go beyond exact keyword matches. This enables understanding the meaning of queries, improving results for complex, natural language searches. ------------------ 🛠️ How It Works 1️⃣ Two-Layer Architecture: 📍 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗟𝗮𝘆𝗲𝗿: Combines keyword-based (TBR) and AI-powered semantic search (EBR) to fetch relevant posts efficiently. 📍 𝗥𝗮𝗻𝗸𝗶𝗻𝗴 𝗟𝗮𝘆𝗲𝗿: Uses advanced models to score and rank posts based on quality and engagement metrics. 2️⃣ AI-Powered Matching: 💥 𝗔 𝘁𝘄𝗼-𝘁𝗼𝘄𝗲𝗿 𝗺𝗼𝗱𝗲𝗹 𝗰𝗿𝗲𝗮𝘁𝗲𝘀 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴𝘀 (conceptual representations) of both queries and posts. 💥 These embeddings are compared to match posts that truly address your query, even if they don’t contain the exact keywords. 3️⃣ Metrics Driving Success: 💡 𝗢𝗻-𝗧𝗼𝗽𝗶𝗰 𝗥𝗮𝘁𝗲: Measures if the content answers the query. 💡 𝗟𝗼𝗻𝗴-𝗗𝘄𝗲𝗹𝗹𝘀: Tracks engagement based on how much time users spend on the content. ------------------ 🎉 Results? 🎯 10%+ improvement in search accuracy and engagement. 🎯 Better answers to complex questions, more relevant content, and enhanced user satisfaction. 💡 What’s Next? ▶ LinkedIn is exploring 𝗟𝗟𝗠-𝗯𝗮𝘀𝗲𝗱 𝗿𝗮𝗻𝗸𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹𝘀 to refine its understanding of user queries and elevate the quality of search results even further. 🔗 Have you noticed better search results on LinkedIn? Let us know your thoughts below! ------------------ Link to the Engineering Blog: https://lnkd.in/gjvKunZh Sarveshwaran Rajagopal ------------------ #GenAI #ArtificialIntelligence #SemanticSearch #MachineLearning #AIInnovation #LinkedInUpdates #NaturalLanguageProcessing