The Data Gals

As we step into September, it’s the perfect time to curl up with a great book that not only inspires but also broadens our horizons in the world of data and technology. Whether you’re an experienced data scientist or just starting your journey, this month’s picks will challenge your perspective, ignite curiosity, and empower you to make a greater impact.

Here are our top 3 book recommendations for September, perfect for all the data-driven minds out there:

Invisible Women by Caroline Criado Perez

In Invisible Women, Caroline Criado Perez brings to light the hidden biases baked into systems we rarely question—from medicine to product design, and even algorithms. While the gender gap is often discussed in terms of leadership roles and workplace dynamics, Perez highlights how it extends to areas we take for granted in daily life. For example, medical research is often conducted primarily on male subjects, leading to drugs and treatments that may be less effective or even dangerous for women.

Perez also explores how gender bias in algorithms, particularly in recruitment processes, reinforces inequality by favouring men over women. This book is essential for anyone who wants to understand how deeply ingrained gender disparities shape our world—and how addressing these gaps is key to creating a more equitable future.

Women and Leadership by Julia Gillard & Ngozi Okonjo-Iweala

This powerful book explores the global struggle for gender equality in leadership. Less than 10% of national leadership positions are held by women, reflecting the widespread barriers to power that many women face. Through candid conversations with influential female leaders, Julia Gillard and Ngozi Okonjo-Iweala tackle the root causes of this disparity.

From body-shaming in the media to having their ideas disregarded, these women share their personal experiences with gender bias, sexism, and the additional hurdles they’ve faced on their leadership journeys. Their insights are not only inspiring but also provide actionable solutions for increasing female representation and breaking the cycle of bias.

Weapons of Math Destruction by Cathy O’Neil

In Weapons of Math Destruction, Cathy O’Neil takes a hard look at the unintended consequences of mathematical models and algorithms used in everyday processes like hiring, health insurance, and even security systems. While algorithms are often seen as neutral tools, O’Neil reveals how they can actually exacerbate social inequality. She argues that many algorithms are built on flawed data that reinforces discrimination, particularly against marginalized groups.

From the recruitment algorithms that screen out qualified candidates to risk models used by insurers that unfairly punish the most vulnerable, O’Neil’s book shows how these tools can be weaponized against society. More than a critique, this book is a call to hold data scientists and tech companies accountable for the algorithms they build and the real-world impacts they have.

Join the Conversation!

These books bring important issues to the forefront—gender bias, inequality in leadership, and the ethical dilemmas posed by data and algorithms. Have you read any of these titles? What did you think? Let us know in the comments!

Together, we can broaden our understanding of these challenges and work towards a more inclusive, equitable future for all.