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Make Work Fair summary
Iris Bohnet
Data-Driven Design for Real Results
- 4.5 (22 ratings)
- 20 mins
- 5 Key ideas
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Make Work Fair examines systemic workplace inequalities and gender biases. Authors Iris Bohnet and Siri Chilazi propose actionable steps to foster fairness, inclusivity, and equity across organizations by implementing evidence-based changes in policies and practices.
Make Work Fair
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Key ideas in Make Work Fair
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Invisible unfairness
For decades starting in the mid 1960s, car safety engineers used crash test dummies to improve automotive safety. They set the standard height of the dummies at five feet nine inches, and the weight at around 170 pounds. Every seatbelt, airbag, and safety feature was optimized for this one body type.
The result was both predictable and tragic. Women and children suffered significantly higher rates of injury and death in car accidents. Not because they were inherently more fragile, but because the safety systems were never designed with their smaller, lighter bodies in mind.
This isn’t just a story about automobiles. It’s the story of how most systems in the world work. Someone, at some point, decided what “normal” looks like. They chose a standard – often without realizing they were making a choice at all. And that standard became embedded in everything from office temperatures to medical research to workplace policies.
Think about the traditional corporate career path. It assumes you can work long hours without interruption. It rewards people who can travel frequently and relocate at a moment’s notice. It values in-person work in the office, and availability around the clock. This model suits some people. But for anyone with caregiving responsibilities, health conditions, or just a different way of working, the system creates barriers at every turn.
Museums offer another surprising example of how far the system can be stacked against anyone not looking like the imagined “norm.” Women represent about half of all professional artists, and are the majority of art school graduates. Yet they make up less than ten percent of the artists in major museum collections. The problem isn’t a shortage of talented women artists. It’s that collection practices, exhibition choices, and acquisition decisions were built around certain assumptions about whose work matters most.
The pattern repeats across all industries and contexts. Safety standards, workplace policies, recruitment processes, and organizational cultures all reflect choices that someone made about what normal means. Every design choice advantages some people while creating obstacles for others – the playing field seems level until you realize it was built on a slope.
To see how this might impact your own workplace, take a look at one process you control, whether that’s running meetings, hiring decisions, or performance evaluations. Ask yourself who this process was designed for, who it serves, and whose needs might be invisible in the current setup.
Only then can you identify potential roadblocks you could remove. Maybe meeting times always conflict with school pickup, or job descriptions require credentials that aren’t actually needed on the job. As we’ll see in the upcoming sections, small changes to systems create large changes in the outcomes.
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What is Make Work Fair about?
Make Work Fair (2025) offers a data-driven alternative to ineffective diversity training by showing how to redesign workplace systems themselves. It demonstrates how measuring patterns, removing structural barriers, and building accountability into daily work creates organizations that are both fairer and more effective.
Who should read Make Work Fair?
- People who run meetings, mentor colleagues, or influence workplace processes
- Those curious about why traditional diversity efforts frequently fail
- Anyone who wants to understand how systems create invisible advantages and disadvantages
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