Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech

Sara Wachter-Boettcher

Reviewed By: Morgan Lopez (September 4, 2020)

Bits and bytes aside, computer science has another side to which we all engage with daily: design. Whether it’s tactful marketing, pleasing aesthetic, or familiar color combinations, we have not only witnessed technological inclusion in daily life but have also been unknowing drivers for this technical revolution.

Technically Wrong demands its readers to think critically about the tech we use everyday. Wachter-Boettcher uses provocative case studies to reveal the ways in which biased design and imperfect algorithms underpin the tech world. Her book explores the meaning behind default settings, why we have “funny” virtual assistants, and the harm of claiming to be an all-knowing, unbiased machine. She examines everything from data privacy to “algorithmic inequality” to examples of when well-intentioned-though-poorly-thought-out procedures overstep boundaries. In a quick-though-thorough exploration, Wachter-Boettcher encourages her readers to become critical thinkers when it comes to technology.

After finishing Technically Wrong readers will be able to make informed decisions about the tech they use and support. I will never be able to look at tech the same way and now feel compelled to demand the tech industry become a safer, more inclusive space as well as empowered to actively participate in bringing about this change. Anyone interested in learning to acknowledge and dismantle the bias that designs our tech will deeply benefit from reading Technically Wrong.

It’s up to us to demand that those choices be made differently—not because we want to see technology fail, but rather because we want it to succeed, on terms that work for all of us. After all, most of us don’t hate tech. We love it. It’s time we demand that it love us back.

Sara Wachter-Boettcher

Algorithms to Live By: The Computer Science of Human Decisions

Brian Christian and Tom Griffiths

Reviewed By: Morgan Lopez (September 25, 2020)

“Algorithm” seemed like a mysterious and complex word that would always be just beyond the scope of my comprehension. After reading this book by Brian Christian and Tom Griffiths—and with some help from COSC-051and 052!—I was able to recognize how computing algorithms are applied to our everyday lives. Being able to relate what is discussed in the classroom to human decision making is an incredibly helpful way to not only better understand algorithms but also to better understand your own thought process.

Christian and Griffiths explore how a multitude of computing algorithms apply to our everyday lives. Their book takes an algorithmic—though never robotic nor mechanical—approach towards assessing “human questions.” They pose strategies that can help with everything from finding a parking spot to optimizing a busy schedule. Algorithms to Live By examines optimal stopping, networking, randomness and more by striking a unique balance between the world of computer science and the world in which we live. 

With thought-provoking narration and the minimum level of technical jargon necessary, readers are not only able to understand the logic behind these algorithms but are also able to relate to what these algorithms accomplish. This book is great for readers who are interested in the intersection of computer science and decision-making and want to be introduced to the logic behind algorithms. Algorithms to Live By reveals how similar our problems are to the problems of computers and I am certain that every reader will put down this book with an enhanced ability to recognize the patterns that quietly rule our lives

The next pages begin our journey through some of the biggest challenges faced by computers and human minds alike: how to manage finite space, finite time, limited attention, unknown unknowns, incomplete information, and an unforeseeable future; how to do so with grace and confidence; and how to do so in a community with others who are all simultaneously trying to do the same.

Algorithms to Live By: The Computer Science of Human Decisions