Myth of the Average and Perceived Neutrality
In the world of data analysis, design, and decision-making, the concept of "average" often provides a comforting, albeit misleading, reference point. This reliance on averages can obscure the true diversity and richness of human experience, leading to flawed assumptions and inequitable outcomes. At QuakeLab, challenging the myth of the average is paramount.
The Myth of the Average
The "myth of the average" is a term popularized by Todd Rose, an expert in the science of individual achievement. He argues that designing systems, policies, or products based on the "average" person often leads to solutions that fit no one perfectly. When we design for the average, we overlook the needs and realities of individuals who fall outside this narrow band.
Consider an example from healthcare: designing a standard treatment protocol based on the average patient. This protocol might be ineffective or even harmful for patients with atypical responses to medication or unique medical histories. Similarly, in education, teaching methods designed for the average student can leave both advanced and struggling students behind.
Perceived Neutrality and Its Pitfalls
Perceived neutrality refers to the belief that certain processes, practices, or policies are inherently unbiased. This assumption can be particularly dangerous, as it often masks underlying inequities. For example, a hiring process designed to be "neutral" might still reflect biases present in the recruitment criteria, perpetuating disparities in employment opportunities.
Perceived neutrality often stems from a lack of awareness about how data is collected, processed, and interpreted. Data is not collected in a vacuum; it is influenced by the context, the people collecting it, and the societal structures within which it is embedded. Ignoring these factors can lead to the false belief that data-driven decisions are inherently fair and objective.
How These Concepts Contribute to Flawed, Inequitable Design
The combined impact of the myth of the average and perceived neutrality leads to designs that are fundamentally flawed and inequitable. Design flaws at their best mean bad products and services, and their worst can mean the risk of safety and security. We see this in crash test dummies, seat belts, and even pee-in-place systems for military pilots that are only made for one kind of pilot (take a wild guess). But at a high level, here’s how these design flaws affect everything we build:
Exclusion of Diverse Needs: Designing for the average excludes the needs of individuals who do not fit this narrow category. This exclusion disproportionately affects marginalized and underserved communities, exacerbating existing inequities.
Masking of Biases: Perceived neutrality masks the biases embedded in data, processes, and systems. This leads to decisions that perpetuate existing inequities, as the underlying biases remain unaddressed.
Lack of Responsiveness: Solutions based on the average are less responsive to the actual needs of diverse populations. This lack of responsiveness can result in lower effectiveness and satisfaction among users or beneficiaries.
Perpetuation of Inequities: When biases are masked by perceived neutrality, they are allowed to persist and even amplify over time. This perpetuation of inequities can have long-term negative impacts on marginalized communities.
By challenging these flawed concepts, QuakeLab aims to promote more equitable and effective designs across all industries. We work with our clients to systematically embed equity into their processes and outcomes for an approach that recognizes the diversity of human experiences and actively seeks to address and mitigate biases. This commitment to equity is not just a moral imperative but a practical necessity for creating systems, products, and policies that truly serve everyone.
Equity as a Technical and Universal Skill
At QuakeLab, we believe that achieving equity is not just a matter of good intentions but requires the marrying of existing technical skills and deliberate embedding of equity across all disciplines and industries. Here’s how we approach this:
Inclusive Data Collection: Ensure that data collection methods capture a diverse range of experiences and perspectives and can be disaggregated. This involves using mixed methods, such as qualitative interviews and surveys, to supplement quantitative data.
Barriers to Access and Participation: Employing techniques to detect and mitigate barriers in processes and policies. This includes conducting regular audits and using decision-making tools.
User-Centered Design: Prioritize the needs of marginalized and underserved communities. By engaging these groups early and often, you create solutions that are more effective and less likely to replicate historical harms.
Implementing these principles has tangible benefits across various industries. In healthcare, for instance, involving patients from racially and gender diverse backgrounds in the design of treatment plans has led to more effective and personalized care. In education, tailoring teaching methods to accommodate different learning styles has improved outcomes for all students. By analyzing the outputs of these practices and adjusting for inequitable patterns, organizations can build and maintain more equitable products, workforces and offerings.
Challenging the myth of the average and recognizing the limitations of perceived neutrality are essential steps toward creating more equitable systems and practices. At QuakeLab, we view equity not as an add-on but as a core function and lens that enhances the quality and impact of our work. By embedding these principles into our processes, we can create solutions that truly serve all, not just the hypothetical average.
