Understanding Decision Hygiene: Reducing Noise and Bias with RM Compare (2/2)

By Mark House

This is the second of a 2-part blog series investigating how noise and bias influence human judgement, how each is affected by the judgement process, and what we might do about it.

In the realm of decision-making, two significant challenges often undermine the accuracy and fairness of our judgments: noise and bias. These concepts, extensively explored in Daniel Kahneman's book Noise: A Flaw in Human Judgment, highlight the inherent flaws in human judgment and offer insights into how we can mitigate these errors. This blog post aims to elucidate the differences between noise and bias, explain their impact on decision-making, and demonstrate how RM Compare can enhance decision hygiene to reduce these errors.

What Are Noise and Bias?

Noise refers to the unwanted variability in judgments that should be identical. For instance, if two doctors provide different diagnoses for the same patient or two examiners hand out different marks for the same submission, this inconsistency is termed noise. Noise can arise from various sources, including individual differences, situational factors, and random fluctuations in judgment. It is a statistical phenomenon that indicates variability without a clear causal explanation.

Bias, on the other hand, is a systematic deviation from the ideal judgment. Bias pushes decisions consistently in one direction, such as overestimating performance forecasts or showing favoritism towards certain groups. Unlike noise, bias has a causal force and can be identified in individual decisions

Why Are Noise and Bias Problematic?

Both noise and bias lead to errors in decision-making, but they do so in different ways:

  • Noise creates inconsistency and unpredictability. For example, in teacher marking, noise can result in vastly different grades for similar work, undermining the fairness and reliability of the assessment system.
  • Bias leads to systematic errors that skew decisions in a particular direction. This can result in persistent over- or underestimation in various contexts, such as grade forecasting or performance evaluations.

The presence of noise and bias in decision-making processes can have significant consequences, including unfair outcomes, reduced credibility, and increased costs for organisations.

How Do Noise and Bias Occur in Traditional Decision-Making?

Traditional decision-making processes often rely heavily on human judgment, which is susceptible to both noise and bias. Several factors contribute to these errors:

  • Individual Differences: Different people may interpret the same information differently, leading to variability in judgments (noise).
  • Situational Factors: External conditions, such as time of day or mood, can influence decisions, adding to the noise.
  • Cognitive Biases: Pre-existing beliefs and preferences can skew judgments, resulting in bias.
  • Group Dynamics: In group settings, the opinions of dominant individuals can disproportionately influence the final decision, introducing both noise and bias

Improving Decision Hygiene with RM Compare

RM Compare offers a powerful solution to enhance decision hygiene by reducing both noise and bias in assessments. Here’s how:

  1. Structured Comparisons: RM Compare uses Adaptive Comparative Judgement (ACJ) to allow assessors to compare two pieces of work side-by-side. This method leverages our natural ability to make relative judgments, which are less noisy than absolute judgments.
  2. Multiple Assessors: By involving multiple judges in the assessment process, RM Compare aggregates diverse opinions, which helps to average out individual biases and reduce noise.
  3. Consistency and Transparency: The platform provides a simple holistic statement to participants, reducing the variability in judgments.
  4. Feedback Mechanisms: RM Compare allows judges to leave feedback on their decisions, which can be reviewed and used to further refine the assessment process, ensuring continuous improvement in decision hygiene.

Conclusion

Noise and bias are pervasive issues in traditional decision-making processes, leading to inconsistent and unfair outcomes. By understanding these concepts and implementing strategies to mitigate their impact, we can improve the accuracy and fairness of our judgments.

RM Compare offers a robust solution to enhance decision hygiene, providing a structured, transparent, and reliable assessment process that reduces both noise and bias. Embracing such tools can lead to better decision-making and ultimately drive better outcomes in various fields, from education to business.

For more information on how RM Compare can help you achieve better decision hygiene, visit our Help Centre.

Photo by Elyas Pasban on Unsplash