How to Take Control of Your Career Instead of Following the Algorithm

Every day, millions of professionals open LinkedIn and scroll through job recommendations, career advice, trending posts, and hiring announcements. It is easy to assume that what appears in your feed represents the best opportunities available.

It does not.

LinkedIn is an incredibly powerful platform for networking, learning, and discovering opportunities. However, the content and jobs it presents are primarily shaped by algorithms that respond to previous behavior—not by your long-term career goals. Understanding this distinction can significantly improve the quality of your job search and career decisions (Covington et al., 2016; LinkedIn Engineering, 2023).

Algorithms Optimize for Engagement, Not Career Growth

Recommendation systems are designed to predict what users are most likely to click, engage with, or spend time viewing. They analyze previous searches, applications, profile activity, connections, and content interactions to personalize what each user sees (Covington et al., 2016).

While personalization improves user experience, it can unintentionally reinforce existing patterns instead of helping professionals explore new directions. If you have spent years working in a specific field, LinkedIn is likely to continue recommending similar roles—even if your goal is to transition into a completely different function.

Research on recommendation systems has repeatedly shown that personalization can narrow exposure to alternative opportunities, a phenomenon often referred to as the "filter bubble" effect (Pariser, 2011; Nguyen et al., 2014).

Your Past Experience Shouldn't Define Your Future

Career transitions rarely happen because an algorithm suggests the perfect role.

They happen because professionals intentionally redefine their positioning.

Changing industries, moving into leadership, entering product management, shifting from HR to operations, or transitioning from technical to commercial roles all require proactive career positioning. These moves depend on how effectively you communicate transferable skills, measurable achievements, and future potential—not simply on the recommendations presented in your feed.

Career construction research suggests that successful career development is driven by adaptability, self-direction, and intentional decision-making rather than passive responses to external opportunities (Savickas, 2013).

Visibility Is Different from Opportunity

One common misconception is that if a role appears frequently in your feed, it must be the best available opportunity.

In reality, many excellent positions are never surfaced by recommendation algorithms.

Some are filled through referrals.

Others through targeted networking.

Many are discovered through direct outreach, industry communities, recruiters, alumni networks, or conversations that never become public job postings.

Research consistently shows that professional networks play a significant role in career mobility and access to new opportunities (Granovetter, 1973; Forret & Dougherty, 2004).

A strong job search strategy therefore combines online visibility with deliberate relationship building and targeted outreach.

Build Your Strategy Before You Follow Recommendations

Instead of allowing recommendations to define your search, define your search first.

Ask yourself:

• What type of work actually motivates me?

• Which industries align with my long-term goals?

• What business problems do I enjoy solving?

• Which transferable skills create value beyond my current title?

• What type of company fits my strengths and preferred way of working?

  
  

Once these answers are clear, your LinkedIn activity becomes intentional rather than reactive. The platform becomes one tool within a broader strategy—not the strategy itself.

Practical Takeaway

Before applying for another recommended position, pause for a moment.

Evaluate whether the opportunity supports the career you want to build—not simply the experience you already have.

Review your profile regularly, expand your network beyond your current industry, engage with professionals in your target field, and search proactively using keywords that reflect where you want to go rather than where you have already been.

Career growth comes from making deliberate decisions, not simply following algorithmic suggestions.

How I Help Professionals Build a Career Strategy

Many professionals come to me after months of active job searching with very little progress. Often, the issue is not their experience or qualifications—it is the lack of a clear strategy.

Through personalized career consulting, I help professionals define their positioning, identify transferable strengths, optimize their LinkedIn profile and resume, develop targeted networking strategies, and create a structured job search plan aligned with their long-term goals. The objective is not simply to increase applications, but to improve the quality of opportunities and conversations that lead to meaningful career moves.

References

Covington, P., Adams, J., & Sargin, E. (2016). Deep Neural Networks for YouTube Recommendations. Proceedings of the ACM Conference on Recommender Systems.

Forret, M. L., & Dougherty, T. W. (2004). Networking behaviors and career outcomes: Differences for men and women? Journal of Organizational Behavior, 25(3), 419–437.

Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360–1380.

LinkedIn Engineering. (2023). How LinkedIn Uses AI and Machine Learning to Improve Member Experience.

Nguyen, T. T., Hui, P.-M., Harper, F. M., Terveen, L., & Konstan, J. A. (2014). Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity. Proceedings of the 23rd International Conference on World Wide Web.

Pariser, E. (2011). The Filter Bubble: What the Internet Is Hiding from You. Penguin Press.

Savickas, M. L. (2013). Career Construction Theory and Practice. In S. D. Brown & R. W. Lent (Eds.), Career Development and Counseling: Putting Theory and Research to Work (2nd ed.). Wiley.