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Invisible Women: Data Bias in a World Designed for Men

Name: Invisible Women: Data Bias in a World Designed for Men
Author: Caroline Criado Perez

by Caroline Criado Perez

2019

416 pages

Abrams Press

Non-fiction

Social Science / Gender Studies

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Overview

Invisible Women exposes the pervasive gender data gap that systematically disadvantages women in a world designed primarily for men. Through extensive research, the book reveals how the absence of female data in various fields leads to biased policies, products, and services.

The book highlights real-world examples, from healthcare to urban planning, illustrating how this data bias impacts women's lives negatively. It calls for a more inclusive approach to data collection and analysis to create a fairer society.

Caroline Criado Perez argues that addressing this data gap is crucial for achieving gender equality. The book serves as both a wake-up call and a roadmap for policymakers, designers, and researchers to consider women's needs and experiences in their work.

1
The gender data gap leads to systemic disadvantages for women in many areas.
2
Medical research often excludes women, resulting in misdiagnoses and ineffective treatments.
3
Workplaces and urban environments are designed without considering women's needs.
4
Technology and AI can perpetuate gender bias if not developed inclusively.
5
Economic policies frequently overlook the unpaid labor predominantly done by women.
6
Public transport and safety measures often fail to address women's specific concerns.
7
Closing the data gap is essential for creating equitable policies and products.

Chapter 1: Introduction: The Default Male

Introduces the concept of the male as the default in data and design, setting the stage for the book’s exploration of gender bias.

Chapter 2: Part 1: Daily Life

Examines how everyday products and environments, from smartphones to office temperatures, are designed with men in mind.

Chapter 3: Part 2: The Workplace

Explores gender bias in workplaces, including wage gaps, unpaid labor, and occupational health risks.

Chapter 4: Part 3: Design and Technology

Discusses how technology and AI can perpetuate gender biases if female data is excluded.

Chapter 5: Part 4: Medicine and Healthcare

Highlights the exclusion of women in medical research and its consequences on diagnosis and treatment.

Chapter 6: Part 5: Public Life

Analyzes how public infrastructure, transport, and safety measures often neglect women’s needs.

Chapter 7: Conclusion: Closing the Data Gap

Calls for systemic change in data collection and policy-making to create a more equitable world.

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Key Takeaways

Incorporate gender-disaggregated data in all research and policy-making.

Design products and services with diverse user needs, including women’s perspectives.

Ensure medical studies include female participants to improve healthcare outcomes.

Recognize and value unpaid labor in economic analyses and policy decisions.

Develop AI and technology with awareness of potential gender biases.

Advocate for urban planning and public transport that prioritize women’s safety and convenience.

Promote transparency and accountability in data collection to address gender disparities.

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