How to Identify and Mitigate Unconscious Bias in Mentoring Programs

Mentoring programs are designed to use human connection as a pathway for personal and professional development. However, unconscious biases can poison the efficacy of those relationships. Regardless of what your company hopes to accomplish with its mentoring programs, if unconscious biases are ruining relationships, you aren’t likely to see the kind of measurable outcomes you and your leadership hope for.

In this post, we’re going to walk you through several essential questions related to unconscious biases and mentoring:

• What is unconscious bias in mentoring programs?
• Why do unconscious biases seep into mentoring relationships?
• Who is responsible for unconscious biases, and who is impacted by them?
• When do you need to take action to stop it?
• How can automated matching reduce biases in mentoring relationships?

Please note that this post is not about every possible unconscious bias that exists within the workplace. To learn more about the type of unconscious biases that often exist at work, check out our post on 10 Unconscious Bias Examples by Toki Toguri, MentorcliQ’s Director of DEIB Engagement and Education.

What is unconscious bias in mentoring programs?

Unconscious bias (sometimes called implicit bias) refers to the subconscious prejudices or assumptions we hold about others. It’s much like a disease that none of us is immune to. Our brains make snap judgments about people within different contexts based on past experiences or misunderstandings.

The Smithsonian Institute has an interesting (dare I say, fun?) interactive website to help people better understand why context influences biases. The organization’s Bias Inside Us project uses two well-known visual illusions to illustrate the point:

• The Ebbinghaus illusion (also called the Titchener illusion)
• Adelson’s checkered shadow illusion

Both illusions are designed to present the idea that what you see isn’t always what’s true. But your mind can be convinced of a lie because you lack the proper context or the full understanding of what you’re seeing.

This is true with both personal and professional relationships and extends to mentoring programs and mentoring relationships, as well. Our pre-existing biases about people are often colored by misconceptions or half-truths. In the context of a mentoring program, unconscious bias can influence how mentors and mentees perceive and treat each other, often in ways neither party consciously intends.

For example, a mentor might inadvertently treat a mentee as a “label” rather than an individual, focusing on the mentee’s gender, race, or background and the stereotypes attached to those labels. This can poison the mentoring relationship by coloring the mentor’s expectations or communication style from the outset.

Importantly, unconscious biases in mentoring are usually not born of ill will; they operate in the background. A well-meaning mentor could still exhibit biased behavior that affects the mentee’s growth.

• Affinity bias is a common example: a mentor may subconsciously favor someone who reminds them of themselves (same school, same ethnicity, same personality) and thus give that mentee more attention or trust.
• Conversely, a mentor might have lower expectations of a mentee who comes from a different background due to ingrained stereotypes.

Another rather sobering example: If a mentor unconsciously believes that women aren’t interested in STEM fields, they might fail to mention a key engineering project opportunity to a female mentee, whereas they would have told a male mentee about it. This is a bias that is prevalent even among school-aged children, according to a University of Houston study, which found 63% of kids in 1st to 12th grade believe girls are less interested in engineering than boys.

In this context, the mentee is denied an opportunity due to the mentor’s bias, even though the mentor wasn’t aware of acting unfairly. Unchecked, such biases undermine the purpose of mentoring programs. They can erode trust, limit mentees’ experiences, and ultimately prevent the mentoring program from achieving the personal and professional development outcomes it’s designed for.

Why do unconscious biases seep into mentoring relationships?

Our brains’ wiring is to blame for unconscious biases infecting mentoring relationships. Biases are an evolutionary survival tactic. As Sam Goldstein, Clinical Director of the Neurology Learning and Behavior Center, wrote in a 2025 Psychology Today article:

“…humans have developed a strong bias toward assuming causation, even when only a correlation exists.”

We all process enormous amounts of information each day, and to cope, our minds use shortcuts and patterns. Add in social media, and it’s often information overload. We default to what’s easy, and that typically means developing quick biases to shortcut our way around making decisions.

As far as mentoring relationships go, mentors and mentees instinctively sort each other into categories (friend or foe, “like me” or “not like me”) in mere seconds – all without deliberate thought. Psychologically, mentors and mentees may feel a natural gravitation toward those who look, talk, or think similarly to themselves.

Yes, this in-group favoritism happens to everyone. Yes, it bypasses rational thinking. And yes, it can be absolutely destructive to mentoring relationships if we’re not conscious that it happens and take actionable steps to prevent our brains from going toward that default.

In a mentoring scenario, unconscious biases can manifest as:

• A mentor “clicking” with a mentee who shares their background, while unconsciously keeping another mentee at arm’s length. Because these judgments happen subconsciously, people often don’t realize when bias is creeping into their decision-making and behavior.
• A mentor giving more enthusiastic feedback to a mentee they perceive as a “go-getter,” while offering only lukewarm encouragement to another mentee, not recognizing that this difference stems from subtle biases about personality or culture.
• A mentor recommending opportunities or career advice to certain mentees based on comfort and familiarity (e.g. “I feel like we have a lot in common, so I’ll take them under my wing”).
• A program administrator manually matching mentors and mentees based on external similarities, such as race, gender, or religious beliefs.

As noted, the issue is typically a lack of awareness by mentors, mentees, and program admins making the matches. Since these biases operate below conscious awareness, mentoring program participants and admins who haven’t actively examined their assumptions will simply act on “autopilot.” Everyone tends to assume their perceptions are objective, so without training or self-reflection, biased behaviors go unchecked.

If a company’s mentoring program relies on manual matching or personal recommendations, it may inadvertently amplify individual biases. (A manager might always pair mentees with mentors of the same gender or similar background, for example, because it just “feels” like a good fit.) Without safeguards, the subtle biases of those running the program or participating in it will naturally find their way into mentoring relationships.

Who is responsible for unconscious biases, and who is impacted by them?

The simple answer here is that everyone involved in a mentoring program is responsible for their own unconscious biases, and everyone is impacted when these biases go unchecked at the program management level. Given we all have these biases built into the core of our brains, it takes a significant amount of self-reflection and conscious action to work past them, or undo them. That said, however,

Mentors, mentees, and program managers all have a role in acknowledging and mitigating bias. It’s not a matter of blaming people for having biases. We’ve already established that developing biases is altogether natural, involuntary, and often necessary. However, everyone involved in creating, running, and participating in mentoring programs and mentoring relationships must take ownership of their own biased perceptions.

For example, a mentee who senses that their mentor has lower expectations of them (perhaps due to gender or cultural bias) might lose confidence and disengage, missing out on growth opportunities. This not only harms the mentee’s development but also wastes the mentor’s and organization’s investment in the relationship.

Biases can also affect mentors: if a mentor subconsciously writes off a mentee’s potential, the mentor misses the chance for authentic reciprocal learning and fails to flourish themselves. Moreover, biased mentoring perpetuates broader workplace inequalities. If certain groups of employees (such as women, minorities, or older workers) consistently receive poorer mentoring due to bias, they will be overlooked for development and advancement, reinforcing the very diversity gaps companies are trying to close. In this way, the adverse effects ripple out; the team or organization fails to fully develop all talent.

At the organizational level, unconscious bias can quietly sabotage the key business goals that underlined starting a mentoring program in the first place.

Mentoring is meant to develop and elevate employees, but bias skews who gets the best development opportunities. As multiple studies have shown, bias can directly impact who gets hired, developed, and promoted. This drills down even to people’s names, as noted in the study on racial biases in hiring, “Are Emily and Brendan More Employable than Lakisha and Jamal?” by Marianne Bertrand, Chris P. Dialynas Distinguished Service Professor of Economics.

Mentoring is part of that “development” puzzle that isn’t immune to such implicit and subtle biases. So if biases are ruining mentoring relationships, high-potential employees might not advance, teams might not perform as well, and the culture remains exclusionary. In short, the entire organization is impacted when unconscious bias taints mentorship: you end up with less skill growth, lower employee engagement, and a failure to see the kind of measurable outcomes (like diversity in leadership, retention improvements, or performance gains) that a good mentoring program can deliver.

Considering we know your C-Suite wants to see results, the results you need to show quite literally rely on unbiased matching and relationships in your mentoring programs.

When do you need to take action to stop biases from ruining mentoring relationships or programs?

The short answer: as soon as possible.

In fact, the best time to address unconscious bias in mentoring is before it has a chance to do any damage. Companies should take proactive steps at the very outset of a mentoring program. This means:

• Training mentors (and mentees) about unconscious biases during program launch or mentor orientation
• Setting expectations that bias awareness is part of the mentoring process.
• Identifying and confronting potential biases early on to build respectful, productive, relationships
• Having mentors reflect on any preconceptions they might hold once they’re paired with a mentee
• Having both parties discuss ground rules or create mentoring agreements to ensure open-mindedness.
• Rviewing the mentor-mentee matching process for fairness before pairs are finalized (more on that later in the “How” section).

Of course, bias can surface at any point, even despite early prevention efforts. Ongoing vigilance is key. You need to take action whenever bias is observed or reported in a mentoring relationship. That means addressing it on day one with the same intensity that you’d address it on day 100.

For example, if a mentee starts showing signs of disengagement or expresses that they feel stereotyped by their mentor (even subtly), program managers and leaders should intervene immediately. This could mean coaching the mentor on the issue, facilitating a conversation to clear misperceptions, or in severe cases reassigning pairs. The moment you suspect that unconscious bias might be “poisoning” a mentorship (we’ve used that term liberally for a reason) that’s when to act. Leaving it unaddressed even for a while can let resentment or misunderstandings grow.

Integrate bias mitigation from the beginning, and treat every instance of bias (no matter how small) as something to correct in real time. “When” to stop bias is really a continuous mandate: right now is always the right time to double-check that bias isn’t creeping in.

How can automated mentor matching reduce biases in mentoring programs?

The mentor-mentee relationship is a critical factor in the success of a mentoring relationship. Most of the work that goes into developing a successful mentoring program is ensuring that your mentors and mentees are a good match without the infection of implicit biases. The emergence of mentor matching software is an innovative solution that can remove biases commonly found with manually-matched participants.

Other key benefits to using matching tools include:

• Significantly reduce administrative time burden
• Create opportunities for more dynamic and comprehensive matches
• Allow for faster and more efficient program scaling

Before you dive too far into manual matching as a solution to your program’s bias woes, make sure you have a full understanding of what these tools are, and why they’re beneficial for your program.

Mentoring matching engines can significantly reduce matching and relationship biases

A mentor matching engine (or software, or application; it has many names) is an algorithm-based tool that matches mentors and mentees together. While it’s 100% software (so no internal moving parts or combustion engines needed), it works much like a machine: insert your fuel (data on your mentors and mentees) to generate power (matches) and output your results (metrics).

I know what you’re thinking here: Wait, that output is usually just toxic fumes. That doesn’t sound like a good result for a mentoring program that’s fixing my bias problem.

Yes and no. The output of any engine heavily depends on two things:

1. The type of engine you’re using
2. The type and quality of the fuel you put into it

Some mentor-mentee matching tools are more like traditional combustion engines. They pull together various fossil fuels like gasoline, and their output is often worse for the environment than the fuel that went into it. E.g., they don’t fix your bias problem because the way they match doesn’t match using unbiased criteria.

Others, however, are more like hydrogen internal combustion engines. You input a plentiful natural resource (hydrogen is the most abundant element in the universe), and your output is good for the environment.

That extended metaphor takes us to this important point: Employees look at mentoring as an essential part of their career journey. An edX survey found that 80% of employees would stay longer if their company offered learning and development opportunities. And 53% of executives want to provide upskilling and training at scale.

If that mentoring relationship is poisoned (yes, we said it again) by biases, the results will be less-than-ideal; maybe even counter-productive. Algorithm-based mentor matching engines do both, creating a win-win scenario for employees and executives.

How mentor matching engines work

As noted above, a mentor matching engine is, at its heart, an algorithm-based tool designed to pair mentors and mentees together. Good ones, like MentorcliQ’s mentoring software, match based on interests instead of surface-level external similarities. There are rather complex functions that go into making that work, but here’s a high-level understanding of what’s needed:

1. A large enough population size. The algorithm that powers mentor matching engines works best when the input (the population size) is large enough to support high-quality matches. E.g., if you only have around 20 employees, the diversity of interests and needs may not produce quality matches. Alternatively, if you have 5,000 employees, you’re far more likely to get better match results because the diversity of personality types, interests, goals, and other criteria is more likely to lead to high-quality matches.
2. Survey data and matching criteria: A mentor matching engine only works with adequate data. For matching mentors and mentees, that data comes down to the surveys participants complete upon enrollment, and the criteria you set that give the matching algorithm its guidelines.
3. Customization: Matching engines should be as automated as possible, but that doesn’t mean you should have no control over the behavior. These engines get the best results when administrators can adjust the matching logic to get results that matter to their organization.
4. Visualized matching scores: This is the part of the matching engines that most admins find the most engaging and fun. When you insert the requisite data and let the algorithm run, you quickly get visualized results with percentage-based match scores. The higher the score, the better the match, and the more likely the relationship will be free-flowing, positive, and fruitful.

A mentor matching engine is an excellent tool for solving real-world problems for mentors and mentees paired in skill-based relationships or buddy systems where mentors and mentees are at a similar tenure level. But even more than that, it’s the single-best solution to helping make sure your matches don’t start off on a biased footing.

Matching based on what matters most will give your mentors and mentees a better chance at connecting authentically. Biases may still exist, but that’s where practical anti-bias training comes into play. Mentoring software will give you the unbiased matches you need to create effective relationships, while your team training will reduce the impact of implicit biases that exist when your mentors and mentees first meet and see each other for the first time.

Additional benefits of using a mentor matching engine

The following is a glimpse of the common benefits that companies enjoy when using a mentor matching engine:

• It reduces the transaction costs involved with traditional mentoring programs
• It is designed to make it easier to track the progress of the mentoring program and gain insight into improvements
• It facilitates deeper engagement and more efficient mentoring
• It delivers a discussion-based environment that facilitates document sharing, video conferencing, and collaboration with other mentors

MentorcliQ’s mentor matching tool was built to respond to the consistent frustrations reported by talent development leaders trying to run successful mentoring programs. Matching has historically been one of the most significant burdens to launching mentoring programs.

Because of this, manually-run programs that rely on hand matching are usually limited in the number of participants that can be matched, and the number of programs administrators can run at any one time, at least, not without an army of program administrators on hand. Ultimately, manually run programs don’t produce the type of ROI that makes them a practical training, development, and engagement strategy. And they’re far more likely to produce biased matches, which in itself will ruin the program from the start.

There’s a reason why 98% of Fortune 500 companies have mentoring programs. They see the value and are more likely to invest in the technology that makes mentoring easier to establish at scale across their organizations.

Nevertheless, not all Fortune 500 companies are using effective matching software. This is why your complaints about unconscious bias and favoritism in the workplace are on the rise. Mentoring is designed to help create human connection and develop people and culture, but it can’t do that when the matches are built on a foundation of unconscious biases that limit development and growth.

The following are some of the benefits you can enjoy when you utilize a software approach for your mentoring programs that start with a mentor matching engine.

For mentors

Mentor matching engines can expand the number of mentors you have available for mentoring programs. By eliminating the amount of lift needed to enroll in a program, mentors can join a program and, after completing a quick survey, be matched with mentees almost immediately. However, program administrators can also examine best-fit matches determined by the system and pair based on suggested matches.

Additionally, mentoring software allows mentors to keep a better track of mentoring goals and milestones, communications, and learning goals.

For mentees

Mentees are the biggest beneficiaries of mentoring software and mentor matching engines (as they should be!). As with mentors, mentees can enroll quickly and get matched quickly. They also have access to tools that help them track progress toward milestones and goals, integrated communications with their mentors, and a platform that even allows on-demand mentoring with open mentoring programs.

For organizations

Organizations have an understandable need to see results from mentoring program software. If you’re going to invest in a mentor matching engine and mentoring software, it should help you achieve critical objectives.

Thankfully, mentoring software can produce incredible results when utilized correctly. In fact, with MentorcliQ’s mentoring software, companies see an average 50% reduction in turnover. That’s thanks in no small part to its ability to create better mentor-mentee connections.

That’s just one area where mentoring software produces significant cost savings and ROI, but for most companies, it’s enough to get the conversation going on applying mentoring strategies for other business objectives, such as succession planning, leadership development, and DEI.

Remember: Unbiased mentoring doesn’t end at the match

The use of mentor-matching software is a reliable way to achieve more accuracy and mitigate bias within your mentoring program. However, as important as matching is, effective relationships must have meaning, and participants must still be self-aware. Make sure your mentoring programs are effectively structured and well-planned so that once mentors and mentees are matched, they’re working toward goals that lead to successful program and relationship outcomes. Commonly, one of the biggest hurdles to that kind of success is how well mentors themselves are prepared to step into that role.