Distorted View of Diverse Group Due to Unconscious Bias

Unconscious Bias in the Workplace: Are Your Gut Feelings Costing You?

Avery Sinclair in Mind & Education June 2025 • 4 min read.

"New research reveals how hidden biases in familiar sources can distort decision-making and impact diversity, media perceptions, and even project finance."

In today's interconnected world, making informed decisions relies on gathering information from a multitude of sources. We all use a combination of traditional data, advice from trusted colleagues, and insights from algorithms. However, a new study highlights a troubling reality: our reliance on familiar sources can be a major source of skewed decision-making.

Researchers Junnan He, Lin Hu, Matthew Kovach, and Anqi Li demonstrate that pre-existing biases within our go-to information channels can act as 'yardsticks' that distort how we perceive new and unfamiliar information. This distortion can have far-reaching implications, affecting everything from labor market discrimination and media bias to financial project oversight.

The team's findings suggest that even with access to diverse information, our unconscious biases can lead to systematic errors in judgment. Understanding how these biases operate is the first step in mitigating their impact and fostering fairer, more accurate decision-making processes.

The Hidden Yardsticks: How Familiar Biases Distort New Information

Distorted View of Diverse Group Due to Unconscious Bias

Imagine you're a manager evaluating employee performance. You consult various sources: your personal observations, input from senior colleagues, and standardized HR data. But what if you unconsciously hold a bias against certain groups? The research shows that this implicit bias can skew your interpretation of information from newer sources, such as innovative employee data analytics tools or insights from newly formed committees.

The study models a decision-maker (DM) who relies on both familiar and unfamiliar information sources to predict a random state. While unfamiliar sources hold potentially unbiased insights, the DM's pre-existing beliefs about familiar sources act as a filter, coloring their perception of the new data. This is especially problematic when those pre-existing beliefs are inaccurate or 'misspecified'.

The DOOM Property: The distortion in prediction depends only on misspecified sources, not on sources with initially unfamiliar biases or the opportunity to learn about their biases over time.
The Long-Run Impact: The DM underestimates the bias of any unfamiliar source that is adversarial toward minorities while overestimating the bias of any unfamiliar source that is favorable to them.
Real-World Examples: This has implications for labor market discrimination, media bias, and project finance and oversight.

The researchers found that this distortion effect, termed 'DOOM' (Dependence Only On Misspecified sources), occurs because the DM uses familiar sources as benchmarks. This can lead to persistent misinterpretations of unfamiliar sources, ultimately impacting long-run predictions. For example, a manager with an implicit bias might consistently undervalue contributions from minority employees, even when presented with data that suggests otherwise.

Combating Bias: Practical Steps for Fairer Decisions

While the findings might seem disheartening, awareness is the first step toward change. By recognizing the potential for familiar sources to distort our perceptions, we can take proactive steps to mitigate bias and create more equitable outcomes. The following offers a few strategies to consider:

About this Article -

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This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2309.0874,

Title: Learning Source Biases: Multisource Misspecifications And Their Impact On Predictions

Subject: econ.th

Authors: Junnan He, Lin Hu, Matthew Kovach, Anqi Li

Published: 15-09-2023

Everything You Need To Know

What are 'unconscious biases' and how do they impact workplace decisions?

Unconscious biases are hidden prejudices or stereotypes that individuals hold without being aware of them. These biases, particularly those embedded in 'familiar sources', can skew workplace decisions, leading to unfair evaluations, missed opportunities, and a lack of diversity. The research by He, Hu, Kovach, and Li highlights that these biases distort how we interpret new information, causing systematic errors in judgment. This distortion can then impact things like labor market discrimination, media bias, and project finance and oversight.

What is the 'DOOM Property' and how does it affect our interpretation of new information?

The 'DOOM Property' (Dependence Only On Misspecified sources) refers to a distortion in prediction that stems solely from 'misspecified sources,' meaning sources with inaccurate pre-existing biases. It suggests that the distortion doesn't arise from biases in unfamiliar sources or from the ability to learn about biases over time. Because decision-makers often use familiar sources as benchmarks, these misspecified sources can persistently skew the interpretation of new or 'unfamiliar sources', leading to inaccurate long-run predictions and flawed decision-making.

How can reliance on 'familiar sources' negatively influence labor market discrimination, according to the research?

The research indicates that pre-existing biases in 'familiar sources' can lead to systematic errors in judgment, impacting labor market discrimination. For instance, if a manager's assessment of employee performance relies heavily on input from senior colleagues who hold implicit biases, this can skew the manager's interpretation of information from newer sources, such as employee data analytics or insights from newly formed committees. Even if new data suggests otherwise, a manager may consistently undervalue contributions from minority employees, perpetuating unfairness.

In project finance, how might 'unconscious biases' in 'familiar sources' affect oversight?

In project finance, unconscious biases within familiar sources can compromise effective oversight. If key decision-makers rely on a network of advisors who share similar backgrounds or perspectives, they might unconsciously dismiss alternative viewpoints or fail to recognize potential risks associated with certain projects. This can lead to skewed evaluations, misallocation of resources, and ultimately, poor project outcomes. Overestimating the reliability of biased sources can result in overlooking critical information that could lead to better-informed decisions and prevent financial losses.

What does the study suggest about mitigating the impact of 'unconscious biases' and fostering fairer decision-making?

The study suggests that awareness is the first step toward mitigating the impact of 'unconscious biases'. By recognizing the potential for familiar sources to distort perceptions, individuals and organizations can take proactive steps to create more equitable outcomes. Strategies might include seeking diverse perspectives, critically evaluating information sources, implementing blind review processes, and using data analytics to identify and address potential biases. Regular training and self-reflection can also help individuals become more aware of their own biases and actively work to counteract them.