What’s Happening with LinkedIn’s Algorithm?

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    <h2>LinkedIn Gender Experiment Raises Questions About Algorithm Bias</h2>

    <p id="speakable-summary" class="wp-block-paragraph">In November, a product strategist, whom we'll refer to as Michelle (a pseudonym), logged into her LinkedIn profile and switched her gender to male, changing her name to Michael. This was part of an experiment called #WearthePants, designed to explore potential biases in LinkedIn's algorithm against women.</p>

    <h3>The #WearthePants Experiment: Testing Algorithmic Bias</h3>

    <p class="wp-block-paragraph">Michelle was participating in a growing trend where women sought to verify claims of algorithmic bias on LinkedIn. The test came in response to observations by frequent users who noted decreased engagement and visibility on their posts, coinciding with recent algorithm updates.</p>

    <h3>Engagement Imbalances: A Closer Look</h3>

    <p class="wp-block-paragraph">With over 10,000 followers, Michelle ghostwrites for her husband, whose profile has about 2,000 followers. Surprisingly, both received similar engagement despite the follower disparity. “The only significant variable was gender,” she pointed out.</p>

    <h3>User Reports of Gender-Based Visibility Changes</h3>

    <p class="wp-block-paragraph">Users like Marilynn Joyner also noted stark differences after changing their gender on LinkedIn. After switching to male, she reported a 238% increase in post impressions within just one day. This trend was echoed by many, leading to discussions surrounding gender bias within the platform.</p>

    <h3>The Response from LinkedIn: No Bias, No Problem?</h3>

    <p class="wp-block-paragraph">In response to these claims, LinkedIn stated that its algorithms do not rely on demographic information to determine visibility in users’ feeds. Yet, experts have noted that implicit biases may still persist within the system.</p>

    <h3>Understanding the Algorithm: Complexity and Bias</h3>

    <p class="wp-block-paragraph">According to data ethics consultant Brandeis Marshall, LinkedIn's algorithms are complex and may inadvertently favor certain communication styles. This complexity makes it difficult to pinpoint specific causes for visibility variations.</p>

    <h3>Roots of the #WearthePants Movement</h3>

    <p class="wp-block-paragraph">The #WearthePants initiative originated from entrepreneurs Cindy Gallop and Jane Evans, who questioned if gender was influencing engagement levels. By having men post similar content, they highlighted stark discrepancies in reach.</p>

    <h3>Algorithmic Transparency: A Call to Action</h3>

    <p class="wp-block-paragraph">While some participants demand accountability from LinkedIn regarding potential bias, the company's secrecy about algorithm operations complicates the issue. Marshall emphasizes the need for platforms like LinkedIn to address biases that might stem from the way their AI systems are trained.</p>

    <h3>User Experiences: Mixed Reviews on Engagement</h3>

    <p class="wp-block-paragraph">Many users across genders express frustration with the new algorithm. While some see increased impressions, others struggle to achieve engagement levels similar to those prior to the changes.</p>

    <h3>The Search for Clarity and Fairness</h3>

    <p class="wp-block-paragraph">The algorithm's opaque nature means that users are left confused and seeking clarity. “I want transparency,” Michelle stated, encapsulating the broader demand for accountability in social media platforms.</p>
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Here are five FAQs regarding LinkedIn’s algorithm:

FAQ 1: What does LinkedIn’s algorithm prioritize in user feeds?

Answer: LinkedIn’s algorithm prioritizes content that encourages engagement, such as likes, comments, and shares. It looks for posts that are relevant to your interests, industry, and connections, promoting high-quality, meaningful interactions over irrelevant content.

FAQ 2: How can I improve the visibility of my posts on LinkedIn?

Answer: To enhance the visibility of your posts, focus on creating engaging, original content that sparks conversation. Use relevant hashtags, tag connections, and post during peak hours when your audience is most active. Consistent interaction with your network also boosts your overall visibility.

FAQ 3: Are videos prioritized over text posts?

Answer: Yes, the algorithm tends to favor video content, as it often generates higher engagement rates. Incorporating video into your LinkedIn strategy can help attract more views and interactions compared to traditional text posts or images.

FAQ 4: Does commenting on others’ posts affect my own reach?

Answer: Absolutely! Engaging with others’ posts can expand your network and enhance your own visibility. When you comment on posts, your name is visible to the original poster’s connections, potentially increasing your reach and encouraging reciprocal engagement.

FAQ 5: How does LinkedIn determine what’s “high-quality” content?

Answer: LinkedIn assesses content quality based on user engagement metrics, relevance, and whether it fosters conversation. Posts that result in meaningful discussions, high interaction rates, and positive feedback from users are considered high-quality and are more likely to be promoted in feeds.

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What’s Driving the Headlines on Massive AI Data Centers?

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    <h2>Silicon Valley's AI Infrastructure Investment Surge: What You Need to Know</h2>

    <p id="speakable-summary" class="wp-block-paragraph">This week, Silicon Valley dominated the news with jaw-dropping investments in AI infrastructure.</p>

    <h3>Nvidia's Massive Commitment to OpenAI</h3>
    <p class="wp-block-paragraph">Nvidia announced plans to <a target="_blank" href="https://techcrunch.com/2025/09/22/nvidia-plans-to-invest-up-to-100b-in-openai/">invest up to $100 billion in OpenAI</a>. This investment marks a significant leap in AI capabilities, with the potential to reshape the industry landscape.</p>

    <h3>OpenAI's Expansion with New Data Centers</h3>
    <p class="wp-block-paragraph">In response, OpenAI revealed plans for <a target="_blank" href="https://techcrunch.com/2025/09/23/openai-is-building-five-new-stargate-data-centers-with-oracle-and-softbank/">five new Stargate AI data centers</a> in collaboration with Oracle and SoftBank, set to vastly increase their processing capacity over the coming years. To fund this ambitious project, Oracle disclosed it <a target="_blank" href="https://techcrunch.com/2025/09/24/oracle-is-reportedly-looking-to-raise-15b-in-corporate-bond-sale/">raised $18 billion in bonds</a>.</p>

    <h3>The Bigger Picture: A Race for AI Capability</h3>
    <p class="wp-block-paragraph">Individually, these deals are remarkable, but collectively, they illustrate Silicon Valley’s relentless drive to equip OpenAI with the necessary resources to train and deploy advanced versions of ChatGPT.</p>

    <h3>Deep Dive on AI Infrastructure Deals</h3>
    <p class="wp-block-paragraph">On this week’s episode of <a target="_blank" href="https://techcrunch.com/podcasts/equity/">Equity</a>, Anthony Ha and I (Max Zeff) explore the real implications behind these substantial AI infrastructure investments.</p>

    <p>
        <iframe loading="lazy" class="tcembed-iframe tcembed--megaphone wp-block-tc23-podcast-player__embed" height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://playlist.megaphone.fm?e=TCML4042279995"></iframe>
    </p>

    <h3>OpenAI's Innovative New Feature: Pulse</h3>
    <p class="wp-block-paragraph">In a timely move, OpenAI launched <a target="_blank" href="https://techcrunch.com/2025/09/25/openai-launches-chatgpt-pulse-to-proactively-write-you-morning-briefs/">Pulse</a>, an intelligent feature in ChatGPT designed to deliver personalized morning briefings to users. This functionality operates independently, offering a morning news experience without user posts or advertisements—at least for now.</p>

    <h3>Capacity Challenges for OpenAI Users</h3>
    <p class="wp-block-paragraph">While OpenAI aims to broaden access to these innovative features, they are currently constrained by server capacity. Presently, Pulse is exclusively available to Pro subscribers for $200 a month.</p>

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                    <span class="inline-cta__date">October 27-29, 2025</span>
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    <h3>The Big Question: Are These Investments Justified?</h3>
    <p class="wp-block-paragraph">As the debate simmers, can features like Pulse truly justify the hundreds of billions being funneled into AI data centers? While Pulse is intriguing, the stakes are exceptionally high.</p>

    <h3>Stay Tuned for More Insights</h3>
    <p class="wp-block-paragraph">Tune into the full episode for an in-depth discussion on the monumental AI infrastructure investments shaping Silicon Valley, TikTok's ownership dilemmas, and the policy shifts affecting the biggest tech players.</p>

    <figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><p></p></figure>
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Sure! Here are five FAQs with answers related to the topic "What’s behind the massive AI data center headlines?":

FAQ 1: What is driving the expansion of AI data centers?

Answer: The rapid growth in artificial intelligence applications, particularly in machine learning and deep learning, has led to an increasing demand for computing power. This expansion is driven by the need for large-scale processing of data, enabling more sophisticated AI models and faster training times.

FAQ 2: How do AI data centers differ from traditional data centers?

Answer: AI data centers are specifically designed to optimize the performance and efficiency of AI workloads. They typically employ specialized hardware, such as GPUs and TPUs, which are more capable of handling the high computational demands of AI tasks compared to traditional servers that often rely on standard CPUs.

FAQ 3: What are the environmental impacts of massive AI data centers?

Answer: The growth of AI data centers raises concerns about energy consumption and carbon footprint. These facilities require substantial amounts of electricity, contributing to greenhouse gas emissions. However, many companies are exploring sustainable practices, such as using renewable energy sources and improving energy efficiency, to mitigate these effects.

FAQ 4: Are there any challenges associated with the rapid development of AI data centers?

Answer: Yes, challenges include the need for significant capital investment, ensuring reliable cooling systems, managing high energy demands, and addressing security concerns. Additionally, there is a scarcity of skilled professionals in AI and data center management, complicating operational efficiency.

FAQ 5: What is the future outlook for AI data centers?

Answer: The future of AI data centers looks promising, with ongoing advancements in technology and architecture expected to further enhance capabilities. As AI continues to integrate into various industries, the demand for more efficient and powerful data centers will likely grow, leading to increased innovation in this space.

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