Bad Choices: How Algorithms Can Help You Think Smarter And Live Happier by Ali Almossawi

The Blurb On The Back:

The secret recipe for modern success. 

Ali Almossawi’s first book Bad Arguments (“A flawless collection of flaws” Alice Roberts) was a cult hit all round the world.  In Bad Choices, he takes on algorithms, those perennially misunderstood principles that underlie so many of our everyday activities.  Taking us through twelve very funny, highly illustrated situations – from how we listen to music to finding every item on a shopping list as quickly as possible – Bad Choices explains how algorithms work and how to use them for yourself.

We all have an intuitive knack for solving problems, but can we use this ability to find items in logarithmic time?  Can we create cognitive stacks to cut down on errands?  Can we figure out which book we want to read next with link analysis?  Almossawai shows us how and once we recognise what makes a method faster and more efficient, we’ll all become more nimble, creative thinkers, ready to face new challenges.

Covering everything from maze-solving in Ancient Greece to the Two Ronnies, and from rapping in supermarkets to how Facebook predicts our likes, in opening algorithmic thinking to all readers Bad Choices shows us how to choose better – and live happier.

The Review (Cut For Spoilers):

Ali Almossawi’s introduction to algorithmic thinking (illustrated by Alejandro Giraldo) is easy to follow if you’re completely new to the subject and takes you through basic algorithmic methods and fundamental concepts but some of the examples are a little patronising and the humour too strained in parts so it’s really only useful to complete novices.

The book’s structured so that 12 different methods of algorithmic organisation are set out with Almossawi basing each chapter around a specific problem or scenario where an algorithm can provide a solution.  I found this very easy to follow and each chapter builds on what was set out in the preceding chapter so that the reader can build upon their understanding with Almossawi deliberately choosing physical scenarios to demonstrate that algorithms aren’t just connected with computers and big data (although he does bring in occasional allusions to how computer and social media companies use the principles).  Giraldo’s wry illustrations offer a visual guide to the methodologies discussed, including through the use of graphs, which I found a little difficult to follow at first (although when I re-examined them on finishing a chapter I found that I understood them a lot better).  Almossawi also provides a useless additional reading section, which gives those interested in the subject matter suggestions of what to check out next.

My main issue though is that I think Almossawi pitches his examples at a slightly too basic level and his desire to be quirky and humorous sometimes seemed a little patronising to me (although I think this is a matter of personal taste and no doubt some people will enjoy it).  I’d have also liked more real-world examples to help flesh out the concepts and make it directly relevant and the title’s suggestion that algorithms can help you “live happily” was not proved in my experience.

Ultimately I thought this was an interesting introduction to the subject but it is pitched at a very basic level so if you have any familiarity with algorithms I suspect this is not the book for you.

Thanks to the Amazon Vine Programme for the review copy of this book.

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