Invisible Women: Exposing Data Bias in a World Designed for Men

Caroline Criado-Perez

Data is fundamental to the modern world. From economic development to health care to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this insidious bias, in time, in money, and often with their lives. Celebrated feminist advocate Caroline Criado Perez investigates this shocking root cause of gender inequality in the award-winning, #1 international bestseller Invisible Women. Examining the home, the workplace, the public square, the doctor’s office, and more, Criado Perez unearths a dangerous pattern in data and its consequences on women’s lives. Product designers use a “one-size-fits-all” approach to everything from pianos to cell phones to voice recognition software, when in fact this approach is designed to fit men. Cities prioritize men’s needs when designing public transportation, roads, and even snow removal, neglecting to consider women’s safety or unique responsibilities and travel patterns. And in medical research, women have largely been excluded from studies and textbooks, leaving them chronically misunderstood, mistreated, and misdiagnosed.

Gender & SexualityGender & Sexuality · medium confidenceGender & Sexuality81 signalsLlm Classifier: Gender & Sexuality -> Gender & SexualityOpen Library: Gender mainstreaming -> Gender & SexualityOpen Library: Gender Studies -> Gender & SexualityTechnology, Computing & AIScience & Discovery
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies

This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.

  1. 01 Central figures

    None extracted with sufficient confidence.

  2. 02 Central places

    None extracted with sufficient confidence.

  3. 03 Suggested argument

    Because data often treats men as the default and women as atypical, gender bias is built into systems, causing discrimination that costs women time, money, and sometimes their lives.

    Model confidence 72%

  4. 04 Reading orientation

    35 / 100 academic

    Serious trade

    An estimate of intended readership and scholarly apparatus—not quality or importance.

Confidence percentages are the model's own estimates. Profile confidence: 78%.