Impact of LinkedIn Algorithmic Assumptions on Job Seekers

LinkedIn just responded to the bias claims. They think they refuted my research. I believe they just confirmed it. Following the recent discussions on whether the algorithm suppresses women's voices, LinkedIn's Head of Responsible AI and AI Governance, Sakshi Jain, posted a new Engineering Blog post to "clarify" how the feed works (link in comments). I’ve analysed the post. Far from debunking the issue, it inadvertently confirms the exact mechanism of Proxy Bias I identified in my report (link in comments). Here is the breakdown: 1. The blog spends most of its time denying that the algorithm uses "gender" as a variable. And I agree. My report never claimed the code contained if gender == female. That would be Direct Discrimination. I have always argued this is about Indirect Discrimination via proxies. 2. Crucially, the blog explicitly lists the signals they do optimise for: "position," "industry," and "activity." These are the exact proxies my report flagged. -> Industry/Position: Men are historically overrepresented in high-visibility industries (Tech/Finance) and senior roles. Optimising for these signals without a fairness constraint systematically amplifies men. -> Activity: The (now-viral) trend of women rewriting profiles in "male-coded" language (and seeing 3-figure percentage lift) proves that the algorithm’s "activity" signal favours male linguistic patterns ("agentic" vs. "communal"). 3. The blog confirms the algorithm is neutral in intent (it doesn't see gender) but discriminatory in outcome (because it optimises for biased proxies). In the UK, this is the textbook definition of Indirect Discrimination under the Equality Act 2010. In the EU, this is a Systemic Risk under the Digital Services Act (DSA). LinkedIn has proven that they can fix this. Their Recruiter product uses "fairness-aware ranking" to mitigate these exact proxies (likely for AI Act compliance). The question remains: Why is that same fairness framework not being applied to the public feed? 👉 What We Are Doing About It Analysis is important, but action is essential. I am proud to support the new petition, "Calling for Fair Visibility for All on LinkedIn". This isn't just a complaint; it’s a demand for transparency. We are calling for an independent equity audit of the algorithm and a clear mechanism to report unexplained visibility collapse. If you are tired of guessing which "proxy" you tripped over today, join us and sign the petition (link in the comments).

Most job seekers have no idea how recruiters scroll through LinkedIn for candidates. Do they scroll like the rest of us? Nope. Here's what's actually happening on the other side of the screen: A recruiter opens LinkedIn Recruiter. They type in a skill, a problem, or an industry, not necessarily a job title. They're not searching "looking for work." They're searching "supply chain optimization" or "cross-functional product launches" or "federal consulting." Then the algorithm decides who shows up. And here's what most people don't realize: LinkedIn's new 360Brew system doesn't just match keywords anymore. It reads your entire profile including your headline, your about section, your posts, even who's engaging with your content. From there it decides whether you're a credible match. That means: → If your headline is just your title and company, you're invisible to the search that matters most. → If your About section lists where you worked in 2012 but doesn't say what problems you solve now, you're getting skipped. → If you haven't posted or commented in months, the algorithm treats you like you don't exist. → If your content is about random topics that don't match your expertise, your credibility score drops. Recruiters aren't looking for people who are "open to work." They're looking for people who look like they're great at what they do. There's a big difference. The question isn't "am I applying enough?" It's "would a recruiter find me and stop scrolling?" ♻️ Share this with someone in a job search who needs to hear it.

Let's talk about the job search frustration I'm seeing everywhere right now. I've seen countless posts about: "I'm being rejected by AI!" 😩 "80% of jobs are never posted!" 😱 Sound familiar? First, let's tackle the "AI rejection" issue. What job seekers are experiencing are knockout questions (pre-set criteria). It's not some sentient AI making a judgment call; it's a rule-based system. The solution? Read the job description CAREFULLY. Don't just spam the same resume everywhere. Second, the "80% hidden job market" myth. This one's been debunked so many times, yet it persists! While networking and referrals are incredibly important (and I highly recommend them), the idea that the vast majority of jobs are secret is simply not true. Companies need to fill roles, and they do post them – on their websites, on job boards, and on LinkedIn. The challenge is standing out. The actual AI revolution is coming, and it's going to change the game even more: AI Agents. Instead of companies posting jobs and waiting for applications, AI agents will proactively scour the internet, analyzing data from LinkedIn profiles, online portfolios, GitHub repositories, and more. They'll identify candidates who match specific skill sets and experience levels, even if those candidates aren't actively looking. This means: 🔴 A poorly filled-out LinkedIn profile is a HUGE missed opportunity. If your profile doesn't clearly showcase your skills and accomplishments, an AI agent might simply overlook you. 🔴 Your online presence matters more than ever. What projects have you worked on? What contributions have you made? Make sure it's visible. 🔴 Passive job seekers might get contacted for roles they never even knew existed. But only if they've built a strong digital footprint. 🔴 You won't even get a rejection email, because you won't be found! The takeaway? Don't get caught up in the myths. Focus on what you can control: 🟢 Optimize your LinkedIn profile: Keywords, accomplishments, clear descriptions. Think like an AI! 🟢 Build your online presence: Showcase your work, participate in relevant communities, and build your network. 🟢 Tailor your applications: Address the specific requirements of each role. 🟢 Network strategically: Build genuine connections with people in your field. 🟢 Keep learning: The skills landscape is constantly evolving. Stay ahead of the curve. Don't fear the AI. Prepare for it. Focus on building a strong online presence that even an AI agent can't ignore!

The AI Assessment Effect Candidates often tend to adjust their answers or behavior to match what they believe the “ideal candidate” profile looks like. A new study published earlier this month found that when candidates believe they’re being assessed by artificial intelligence, they emphasize analytical skills and downplay their intuitive and emotional skills. This so-called “AI assessment effect” stems from the widespread assumption that AI-based evaluations prioritize rational, data-driven attributes over human-centric abilities. Researchers warn that if job seekers tailor their behavior to what they think AI values, their true competencies and personalities may remain hidden, undermining the integrity of the recruitment process. In addition if most candidates assume AI favors analytical traits, the talent pipeline could become increasingly uniform, limiting diversity and reducing the variety of perspectives within organizations. The researchers recommend 1) Radical transparency: Don’t just disclose that AI is used in assessments—be explicit about what it evaluates. Clearly communicate that your AI values a range of traits, including creativity, emotional intelligence, and intuitive problem-solving. Share examples of successful candidates who excelled by showcasing these qualities. 2) Regular behavioral audits: Go beyond demographic bias checks. Look for patterns of behavioral adaptation: Are candidates’ responses becoming more homogeneous over time? Is there a noticeable shift toward analytical self-presentation at the expense of other valuable traits? 3) Hybrid assessment models: Combine AI and human judgment to ensure a more balanced and holistic evaluation of candidates. See research published in the June issue of the Proceedings of the National Academy of Arts and Sciences. https://lnkd.in/ebtD4HBd

The biggest mistake LinkedIn ever made for job seekers- Making unemployment visible,The “Open To Work” badge was supposed to help professionals,Instead, for many people, it became a public stigma badge. A Harvard Business School Review study once discussed how public unemployment signals can unconsciously trigger “risk perception bias” in recruiters and peers,Not because the candidate is less skilled. But because humans often associate “actively looking” with “less in demand.” The moment that green frame appears: • Replies slow down • Recruiters ghost more often • Engagement drops • People subconsciously assume “desperate” instead of “valuable” And nobody wants to openly admit this. But almost everyone on LinkedIn has seen it happen. According to multiple hiring behavior studies and recruiter surveys globally: • Recruiters spend only 6–8 seconds scanning a profile initially • First-impression bias heavily impacts callback probability • Public perception markers unconsciously influence hiring confidence Now combine that with LinkedIn’s algorithmic visibility system. If a professional: → recently lost a job → is posting less confidently → gets lower engagement → receives fewer responses …the platform starts reducing their visibility even further. It becomes a psychological downward spiral. Lower engagement → lower confidence → lower activity → lower opportunities. And this is happening during one of the worst white-collar employment cycles in years. In 2026 alone: • Tens of thousands of layoffs hit tech, consulting, startups, media, and operations globally • AI automation started replacing entry-level and repetitive knowledge roles • Even experienced professionals with 10–15 years experience struggled for callbacks Yet LinkedIn’s most visible solution was: “Put a green badge on your face.” Imagine if Instagram publicly labeled: “Recently Heartbroken.” Or if banks tagged customers: “Financially Struggling.” That’s exactly how absurd this looks psychologically. A person searching for work does NOT need public labeling. They need: • stronger recruiter matching • anonymous opportunity signals • better reach • interview access • confidence preservation LinkedIn should immediately remove the public “Open To Work” profile frame and make it recruiter-visible only. Because career transitions should not feel like public social downgrades. And honestly…many talented professionals are already suffering silently because of it. Looping in Product team of LinkedIn Gyanda Sachdeva Hari Srinivasan Ajay Datta LinkedIn for Marketing

"Why am I suddenly seeing posts from a few weeks ago?" "Why is there a reduction in impressions on my new posts?" "Is the machine out to get me?" Don't worry, you're not going crazy! A number of updates were rolled out last month to the LinkedIn algorithm (one has since been reversed), which means the way your feed works has changed. What you might notice: 👉 You're seeing Relevance over Recency. The algorithm is better at identifying high-quality, relevant content and keeping it in the feed longer. 👉 It's Prioritizing Expertise. The algorithm now rewards content from experts in their field. Posts that offer deep, authentic insights get a boost. 👉 Authenticity is key. The algorithm can detect and penalize generic, AI-generated content that lacks a unique, human voice. 👉 Meaningful Engagement matters more than ever. The algorithm now values thoughtful comments and replies that spark a genuine, back-and-forth discussion over simple likes and reactions. 👉 Native Content is King. The algorithm favors content created directly on LinkedIn (text posts, native video, etc.) over posts that simply link out to an external site. 𝐒𝐨, 𝐰𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐞𝐚𝐧? If you're posting: ✅ Focus more on value vs virality as this is what the algorithm is rewarding. Create content that is genuinely helpful, sparks conversation, and is unique to your professional experience. ✅ If you're sharing an article, summarize the key takeaways in a text post and put the link in the comments to give it a better chance of being seen. ✅ Be cautious with AI. The algorithm is now better at detecting and penalizing generic or AI-generated posts. If you're scrolling: ✅ Engage authentically. Your interactions tell the algorithm what you want to see more of, personalizing your feed to your professional interests. ✅ By engaging with thoughtful comments and contributing to the discussion, you signal that the content is valuable. I hope you find this useful. Let me know what you think in the comments! #linkedin #ai #jobsearch

The LinkedIn rules changed. Most job seekers missed the memo. Here’s what hasn’t changed. LinkedIn still wants a “complete profile”. That means filling out: Headline About Experience Skills Education Location Profile photo If those are incomplete, you are invisible. Full stop. But here’s what has changed. A “complete” profile is no longer enough. LinkedIn rebuilt its algorithm. It now reads for meaning, not motion. Clarity, not activity. Alignment, not noise. Which means: - A keyword-stuffed headline does nothing if it says nothing. - An About section that lists responsibilities instead of direction gets ignored. - Random posting hurts more than it helps. LinkedIn is no longer asking, “Are you active?” It’s asking, “Do we understand who this person is for and where they belong?” That is the difference between being seen and being skipped. If you are job searching in 2026, this matters more than ever. LinkedIn is no longer just a platform. It is a matching engine deciding who gets surfaced to recruiters and hiring managers. The professionals winning right now are not louder. They are clearer. They are intentional about: What role they are targeting What problems they solve What lane they want to be known for That is what the algorithm is rewarding. So yes. Fill out the 7 sections. But do not stop there. Because in this new LinkedIn landscape, completeness gets you indexed. Clarity gets you chosen. If your reach dropped or recruiters went quiet, it is positional and can be fixed.

LinkedIn isn't designed to get you hired. It's designed to keep you scrolling. Their own engineers published a paper stating their goal directly: "The focus for organic jobs is to optimize seeker engagement." (source in comments) 𝑻𝒉𝒊𝒏𝒌 𝒂𝒃𝒐𝒖𝒕 𝑳𝒊𝒏𝒌𝒆𝒅𝑰𝒏 𝒍𝒊𝒌𝒆 𝒊𝒕'𝒔 𝒂 𝒅𝒂𝒕𝒊𝒏𝒈 𝒂𝒑𝒑. If Tinder got you into a great relationship, you'd delete the app. So what's their incentive? Keep you swiping. LinkedIn works the same way. If you found a job in a week, you'd stop using the platform. So what do they optimize for? Keeping you engaged. They'll show you jobs you find attractive. Give you the thrill of Easy Apply. Keep you scrolling for that next opportunity. But don't expect the algorithm to actually GET you hired—that's not what it's built for. 𝑺𝒐: 𝒘𝒉𝒂𝒕 𝒄𝒂𝒏 𝒚𝒐𝒖 𝒅𝒐? Don't over-rely on LinkedIn as your single source for job searching. The platform's incentives aren't aligned with yours. DO use LinkedIn to connect with real humans—people whose incentives ARE aligned with helping you (or at least aren't oriented towards keep you trapped in a scroll). And watch out for "swipe-syndrome": endlessly browsing and easy-applying without a strategy. If you find yourself spending hours here, check in: is this actually moving you toward a job, or just keeping you busy? 𝑯𝒆𝒓𝒆'𝒔 𝒘𝒉𝒂𝒕 𝒕𝒉𝒊𝒔 𝒍𝒐𝒐𝒌𝒔 𝒍𝒊𝒌𝒆 𝒑𝒓𝒂𝒄𝒕𝒊𝒄𝒂𝒍𝒍𝒚: ❌ Don't: Apply to 50 jobs via Easy Apply in 2 hours ✅ Do: Research 3 companies deeply and reach out to real people there ❌ Don't: Scroll your feed for "inspiration" for 30 minutes ✅ Do: Send 5 personalized connection requests to people at target companies Your brain wants the engagement hit. Your career needs strategic effort. Stay aware of which one you're serving 🙌

𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗱𝗿𝗼𝗽𝗽𝗲𝗱 𝗮 𝗻𝗲𝘄 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 𝗿𝗲𝗽𝗼𝗿𝘁, and the changes are big, subtle, and everywhere. This is the clearest roadmap we’ve had for how the feed actually works. Here are the 6 findings that matter most. 1. 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗶𝘀 𝗻𝗼𝘄 𝗮 𝘁𝗼𝗽𝗶𝗰 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 • It cares 𝘮𝘰𝘴𝘵 about what you talk about. • Your posts, comments, and profile get sorted into topic clusters. • Your reach = your topics. 2. 𝗬𝗼𝘂𝗿 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝘁𝗿𝗮𝗶𝗻𝘀 𝘁𝗵𝗲 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 • Every like, comment, follow is a signal. • You’re programming your reach. 3. 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 𝗯𝗲𝗮𝘁𝘀 𝘃𝗶𝗿𝗮𝗹𝗶𝘁𝘆 • Random content confuses the system. • Stay on topic, and the model learns w̲h̲e̲r̲e̲ to surface your content. 4. 𝗧𝗲𝘅𝘁 𝗶𝘀 𝘁𝗵𝗲 𝘀𝘁𝗿𝗼𝗻𝗴𝗲𝘀𝘁 𝗿𝗮𝗻𝗸𝗶𝗻𝗴 𝗳𝗮𝗰𝘁𝗼𝗿 • LinkedIn’s AI reads your words. Not your videos. • Your headline, About section, posts, and comments shape your discoverability. 5. 𝗦𝗺𝗮𝗹𝗹 𝗰𝗿𝗲𝗮𝘁𝗼𝗿𝘀 𝗮𝗻𝗱 𝗷𝗼𝗯 𝘀𝗲𝗲𝗸𝗲𝗿𝘀 𝗴𝗲𝘁 𝗮 𝗯𝗼𝗼𝘀𝘁 • The system now helps sparse networks. • You don’t need a big following to grow. 6. 𝗬𝗼𝘂𝗿 𝗽𝗿𝗼𝗳𝗶𝗹𝗲 𝗶𝘀 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗿𝗮𝗻𝗸𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺 • Skills, industry, job titles, certifications  • They all contribute to your reach. So what do you do with this? 🔸 𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗖𝗹𝗲𝗮𝗻 𝘂𝗽 𝘆𝗼𝘂𝗿 𝘁𝗼𝗽𝗶𝗰 𝘀𝗶𝗴𝗻𝗮𝗹𝘀. → Engage with posts in your expertise. → Your feed trains your reach. 𝗦𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝗲𝗻 𝘆𝗼𝘂𝗿 𝗰𝗼𝗻𝘁𝗲𝗻𝘁. → Write clearly. Use niche language.  → Dial down the corporate mush. 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗳𝗶𝗹𝗲. → The more data LinkedIn has, the more accurately it can surface you. 🔸 𝗖𝗿𝗲𝗮𝘁𝗼𝗿𝘀 & 𝗠𝗮𝗿𝗸𝗲𝘁𝗲𝗿𝘀 𝗙𝗿𝗼𝗻𝘁-𝗹𝗼𝗮𝗱 𝘆𝗼𝘂𝗿 𝗽𝗼𝘀𝘁𝘀. → The first 40–60 words carry the most weight. → Lead with value. Not throat-clearing. 𝗦𝘁𝗶𝗰𝗸 𝘁𝗼 1–3 𝘁𝗼𝗽𝗶𝗰𝘀 𝗺𝗮𝘅. → Let the algorithm lock onto your expertise. 𝗘𝗻𝗴𝗮𝗴𝗲 𝗱𝗲𝗹𝗶𝗯𝗲𝗿𝗮𝘁𝗲𝗹𝘆. → Commenting in your niche strengthens your authority and widens your audience. 🔸 𝗝𝗼𝗯 𝗦𝗲𝗲𝗸𝗲𝗿𝘀 𝗨𝗽𝗱𝗮𝘁𝗲 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗳𝗶𝗹𝗲 𝗰𝗼𝗻𝘀𝘁𝗮𝗻𝘁𝗹𝘆. → Courses. Certifications. Projects. → Fresh profiles get priority. 𝗖𝗼𝗺𝗺𝗲𝗻𝘁 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝗳𝘂𝗹𝗹𝘆 𝗼𝗻 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗰𝗼𝗻𝘁𝗲𝗻𝘁. → This signals relevance to recruiters 𝘢𝘯𝘥 to the algorithm. 𝗨𝘀𝗲 𝗸𝗲𝘆𝘄𝗼𝗿𝗱𝘀 𝘁𝗵𝗮𝘁 𝗺𝗮𝘁𝗰𝗵 𝘁𝗵𝗲 𝗷𝗼𝗯𝘀 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁. → “Passionate about…” won’t get you surfaced. → “Program Manager, Workforce Development, AI-Skilled” will. 🎯 𝗧𝗵𝗲 𝗯𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲 This isn’t about gaming the system. It’s about understanding how the system understands 𝘺𝘰𝘶. Align your profile, content, and engagement around the same topics. And get discovered faster. 💬 Which finding surprised you the most? ♻️ Share this to help your network. 🔔 Follow Tonya for creator-friendly AI insights.