100 Books Like Power in Numbers

This book completely reframed how I see the world. Perez dives into the pervasive gender data gaps that impact everything from workplace policies to public health. Her meticulous research and compelling examples made me realize how much of our world is designed without women in mind. It’s equal parts infuriating and enlightening, and it left me determined to question systems that perpetuate inequality.

This book is a must-read for anyone who wants to understand the hidden ways gender bias shapes our lives.

This one is pure fun. It’s hard to believe no one thought to make a female chemist the star of a cooking show before! The story is witty and original, artfully combining the hard truths of being a scientist and a TV personality in male-dominated fields, with femininity and motherhood.

Sexism is rampant (obviously, it’s the 1950s), and the challenges the protagonist faces often seem insurmountable. Garmus takes these difficult themes seriously, while delivering them with humor and a lightheartedness that makes for a refreshing read.

This is a beautiful science memoir, that tells the story of fellow Stanford professor Fei-Fei’s Li’s life.

It gives deep insights into the challenges of life in the United States, growing up as an immigrant from a loving but low-income home, and her rise to becoming one of the most important and influential AI leaders of our time. The interweaving of the story of the genesis of AI as a field and Fei-Fei as a scientist is fascinating and educative. 

Fei-Fei’s excitement for science and knowledge, combined with her commitment to family and relationships, makes for a delightful and inspirational read.

I love all of Eugenia’s books, she is a cool mathematician working to educate the public about real mathematics – a subject of deep explorations and connected ideas.

Eugenia shares the creativity in mathematics, and the importance of pushing against boundaries, including the gender boundaries that often stop girls and women going forward in STEM. Her playful use of mathematical ideas to disrupt the myths of narrow and inequitable mathematics and the dominance of men in the field, is so fascinating, especially for those of us perturbed by the inequities in STEM.

This is a great book for those who would like to love mathematics a little more than they do now.

Too Much Happiness, the title story in a 2009 collection by Alice Munro, is a fictionalised account of the last days in the life of mathematician Sofya Kovalevskaya.

What really grabbed me was the way Munro managed to express, with wonderful economy, the way that Kovalevskaya’s acceptance as a woman mathematician in the 19th century felt conditional – she won prizes but had to fight to get a job; if she travelled for work people would allude to the daughter at home who might need her: “a jab there, a suggestion familiar to her, of faulty motherhood”.

It’s a beautiful and poignant portrayal of a complicated, brilliant woman. 

This book has haunted me for years. For what is it, exactly, that gives it such enduring popularity? After all, it was first published in 1936, yet is still in print today. In his autobiography, Hogben remarks on the importance of eye-catching illustrations but speculates that its success may instead be because the book contains – most unusually for a 'popular' work – exercises and answers, making it more suitable for self-teaching. Whatever the real answer, his book must surely have something to teach anyone – like myself – who aspires to bring mainstream mathematics to life for the general public.

An enthralling, fictional description of a young scientist (Einstein) and his dreams/thoughts about space, time, relativity, and the nature of reality. The book fictionalizes Einstein’s dreams in 1905, his “Annus Mirabilis” (“Miracle Year”), in which he wrote four fundamental papers, including one on his theory of Special Relativity. While this is a work of fiction, the physics concepts are beautifully explained.

This book is not about computing, but it is relevant in an indirect way. I love this book, since it is written in such an engaging style and illustrates with many examples that math is not a dry subject to be practiced only by mathematicians but helps everyone to solve real-world problems. The book shows how important it is to be precise in describing problems and that applying a little mathematical rigor goes a long way in solving them. Ellenberg describes mathematics as the “extension of common sense by other means.” In a similar way, I view computer science as the extension of problem-solving methods (aka “algorithms”) by other means. 

Polya was a great mathematician who knew what counted (after all, he made major contributions to combinatorics, the mathematics of counting). He thought hard about what he was doing when working on problems in mathematics, developing a mental process that lead to creative breakthroughs and solutions. Polya’s problem-solving method is broadly applicable to domains other than mathematics, and this book features many nice puzzles to improve your thinking.

Algorithm design is challenging because it often requires flashes of sudden insight which seem to come out of the blue. But there is a way of thinking about problems that make such flashes more likely to happen. I try to teach this thought process in my books, but Polya got there first.

This may seem an odd choice, but as a maths popularizer I need to know all that I can about why some people find the main elements of the subject so difficult. I found Doug French's book exceptionally helpful in this respect, even though it is aimed principally at high school teachers. This is partly because he focuses throughout on the most important mathematical ideas and difficulties. Moreover, the scope is wider than the title suggests, for he also ventures imaginatively into both geometry and calculus.