Books to read: Algorithms to Live By

This book is a solid read with ideas that apply to decision making across a broad spectrum of areas. The authors are able to make the math and conversation around algorithms map to life in well thought and articulated examples that should open your thinking to new ways to approach problems and opportunities.

A few sections that jumped out to me are referenced here or in the reviews, but I encourage you to take the book for a spin yourself.

The most prevalent critique of modern communications is that we are always connected; we’re not. The problem is that we are always buffered. The difference is enormous.

Algorithms to live by pp226

We are now consuming so much information, we cannot possibly process it all. We now queue information to consume, inhibiting real time engagement and leaving an inescapable feeling of “missing out” or need to “catch up”.

From Amazon:

An exploration of how computer algorithms can be applied to our everyday lives to solve common decision-making problems and illuminate the workings of the human mind.

What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of the new and familiar is the most fulfilling? These may seem like uniquely human quandaries, but they are not. Computers, like us, confront limited space and time, so computer scientists have been grappling with similar problems for decades. And the solutions they’ve found have much to teach us.

In a dazzlingly interdisciplinary work, Brian Christian and Tom Griffiths show how algorithms developed for computers also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one’s inbox to peering into the future, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Why I recommend this book:

I lead teams in the Pharma / BioPharma industries and we grapple with large challenges on a regular basis – the ideas presented in the book resonate with me as I think about both the scientific / math applications, but as importantly, the human implications. As leaders it is often required that we know enough about everything in our area of responsibility to help guide the decision making for the organization(s). How we go about prioritizing what to focus on, what to allow in the queue vs what we allow to drop off is a critical bit of surviving and thriving. The best bets are made by those who can sperate the noise from the actionable data. To get there, we need to filter and extrapolate from what we have to what we need to do. This book helps shape a number of interesting and workable ideas to explore in this space.


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