I was asked this question at a workshop held at The Nine Brussels on how women can navigate male-dominated workplaces, which I co-presented with Robert Baker
Is LinkedIn gender biased?
My initial reaction was in response to whether it was deliberately gender biased via the code. As far as I knew like any platform it reflects the gender bias of the users and the culture we live in rather than a deliberately discriminatory inbuilt code.
I committed to researching further and reverting. I also consulted two of my go-to trusted LinkedIn Experts, Trainers and Consultants to offer their point of view: Kevin D Turner and Mic Adam.
I found that my initial understanding was broadly correct. LinkedIn, like many professional platforms, has been scrutinised for gender bias, both in its design and in how users interact on the platform.
- Kevin. D Turner suggests “If the algorithmic code of this platform was created by predominantly young males then, from experience, we know there is built in bias, just as it exists within AI in general. “
- Mic Adam adds ” Is LinkedIn gender biased? Of course it is, and No, it is not…. LinkedIn tries to do its best to be gender neutral, and whenever something comes up, they do respond to make the platform gender neutral again.
While the algorithm isn’t deliberately discriminatory, there are a number of key areas where LinkedIn has shown or potentially facilitates gender bias we see reflected in our wider cultures.
Gender bias on LinkedIn
In February 2025 Statista showed that the composition of LinkedIn is generally 56.9% men to 43.1% women which is going to skew any gender based results.
1. Algorithmic Bias
LinkedIn’s job recommendation and search algorithms have been found to display gender differences in results
- Research from MIT suggests that men were more likely to be matched with higher-paying leadership roles, while women were shown lower-level jobs, even when they had similar qualifications. This reflects and perpetuates existing workplace inequalities.To address this, LinkedIn implemented an AI system designed to produce more representative results across genders.
- Algorithms often learn from historical hiring data, which is already biased and user behaviour (e.g., more men clicking on leadership jobs) further reinforces this pattern. Recruiters click on women’s profiles less frequently than male profiles, and a disparity in profile views can contribute to a broader issue of gender bias in professional networking and recruitment. Mic Adam confirms this “The algo just collects data and translates that into numbers that influence gender bias”
- The algorithm gives strong priorities to corporate roles and less priority to freelance and self-employed activities. It also penalises career gaps which impacts women more than men.
2. Language and Endorsements
Women’s profiles tend to receive different types of language in recommendations.
- Men are more likely to be described with action-oriented words (“driven,” “strategic”), while women often get soft-skill descriptors (“collaborative,” “supportive”).
- Endorsements for women lean towards communication and administrative skills, while men get endorsed more for technical or leadership skills.
This can subtly influence how recruiters and hiring managers perceive candidates. The pattern can influence perceptions of women’s competencies and leadership abilities and reflects the situation found in our wider cultures.
Women also self-describe and assess their own skills and experience in lower level language and less likely to include leadership experience.
LinkedIn’s own research shows:
- Female profiles contain less information, and their summaries are shorter. This means that they are not going to appear in searches carried out by recruiters as frequently and not near the top of the page. A LinkedIn summary today can be up to 2600 characters.
- In the U.S., women on LinkedIn on average include 11% less skills than men on their LinkedIn profile, even at similar occupations and experience levels. This means that they will appear less frequently in searches for that particular skill. Women need to make sure all their key skills are listed.
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3. Visibility and Engagement
Men’s posts and profiles apparently generally get more engagement, more likes, comments, and shares, leading to greater visibility. This happens for several reasons:
- Network structures: Men often have larger professional networks.
- Perception bias: People may unconsciously view men’s professional insights as more authoritative.
- Quantity: The gender distribution on LinkedIn will play a role.
Even LinkedIn’s own leadership acknowledged that their algorithm historically amplified content from “power users, ” disproportionately male, which made it harder for women to gain similar reach.
Having said that, women’s posts with selfies get five times more traction than a male selfie. In the category of posts with more than 500 reactions, posts authored by women get an average of 17.3% more reactions than those authored by men.
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4. Profile Suggestions and Search Results
There have been instances where LinkedIn’s search auto-fill showed men’s names more prominently or suggested male candidates over equally qualified women. This reflects the broader tech issue of “gender default bias.” This seems to have been corrected. I certainly didn’t find it to be the case.
For example:
- Typing “software engineer” yields more male profiles at the top of results. I did not have a female software engineer until Page 4, but this is probably because only 15-22% of software engineers are women.
- “Nurse” or “HR” might show more women, even though men hold those jobs too. Once again this reflects the proportion of women to men in these roles. because they dominate these professions.
5. Pay Transparency and Salary Estimates
LinkedIn includes salary insights for some role, but those can also reflect gendered pay gaps. If users rely on these numbers, women might unknowingly anchor their salary expectations lower than men for the same roles.
This is a cultural, not code issue.
6. Harassment and Unwanted Messaging
A 2023 survey revealed that over 90% of women received unsolicited romantic or sexually inappropriate messages on LinkedIn. Such experiences can deter women’s participation and sense of safety on the platform. It makes them reluctant to share full profile details and engage, all of which contribute to reduced visibility.
LinkedIn are notorious for a lax policy on harassment despite their comments to the contrary. They tend to be slow in responding. I have taken issue with them directly on this and even got as far as a meeting with a Product Manager about this unaddressed issue. But nothing changed.
Kevin D. Turner comments that “LinkedIn had a long history of being a Boy’s Club in its Management and Coders they hired. Only within the last 7 years has embraced more women in leadership.”
These sources provide evidence of the various dimensions of gender bias present on LinkedIn, underscoring the need for ongoing efforts to create a more equitable and professional environment.
7. Algorithmic weighting
The LinkedIn algorithm has faced criticism for allegedly suppressing content related to sensitive issues from all sides. The ones I am frequently involved in are sexism and sexual harassment. Despite the platform’s positioning as a space for professional discourse, users report that posts addressing these critical topics often receive limited visibility, or are removed entirely under vague content moderation policies. I haven’t monitored other topics but I can imagine that hot issues that are not aligned with the zeitgeist of the current US Administration or LinkedIn policy, which reflect the views of its leadership, may also suffer the same fate.
This suppression can discourage open conversations and silence marginalised voices, particularly those sharing personal experiences or advocating for workplace equity. By de-prioritising such content, the algorithm may inadvertently reinforce systemic issues, creating an environment where important discussions are stifled in favour of more “palatable” professional narratives.
Cindy Gallop owner of MakeLoveNotPorn, has been waging this battle very vocally for many years. Please follow her to give her more clout. When I circulated a survey on sexism and sexual harassment recently, my post got 4 (FOUR) views. Remember, although I am not in the stratosphere, I still have 21K followers. So, make that make sense.
8. Career Gaps
There are multiple studies which indicate that if platform members have career gaps in their profile history that these are penalised when Recruiters search for their profiles via LinkedIn Recruiter. If automated ranking/scoring is in play (LinkedIn’s internal relevance scoring, third-party tools that integrate with LinkedIn, or recruiter saved filters), gaps/nontraditional timelines can lower relevance. Evidence shows both humans and machines prefer signals that are easy to interpret and verify.
On average, 28.8% more women list a career break than men globally. Research from LinkedIn “Global Gender Gaps in Career Breaks November 2024” indicates that globally, women are 63.5% more likely to list a career break on their profiles than men, thus penalising themselves in terms of visibility on LinkedIn Recruiter.
This includes Freelance gigs which is gender neutral and LinkedIn’s own Career Breaks tab. And you know what I feel about that phrase and career gap bias.
Is LinkedIn’s algo gender neutral?
Not entirely. While LinkedIn aims for neutrality, its algorithm reflects user behaviour and historical bias in data. We have to remember that AI mirrors user preferences. Mic sums this perfectly. “However, it is people that make the platform gender biased. The technology itself is neutral, but the way individuals design, use, and interact with it can reflect and reinforce existing stereotypes and inequalities. And it is how people train the algorithms with their behaviour that tends to influence how things evolve in terms of gender bias.”
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