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Algorithms to Live By: What Computers Can Teach Us About Solving Human Problems by Tom Griffiths
mrahim's review against another edition
3.0
The book does a good attempt at introducing computer science algorithms and helping the layman apply them to the real world. Found myself applying a few of these whilst making major life decisions too (e.g. the 37% rule). It goes into great details on the history of the field such as key figures like Alan Turing and age-defining technology such as internet and TCP. Unfortunately, at certain times, it becomes far too technical for the average person to follow -- but it is tricky to avoid this.
The writers tie this book together at the end by highlighting the importance of the human aspect when trying to resolve things optimally, such as reducing cognitive load. An example of this is where the US uses quarters etc when the way to reduce change the most amount would be 18 cents, thus making it far easier for cashiers to calculate change.
I think this final part ties the book together well as it serves as a reminder that, although algorithms can be helpful for easier situations, they should not be haphazardly applied without considering the human aspect. Since the release of this book, several issues with deep learning have also been reported to the mainstream news such as ingrained racism in the training data. This highlights a degree of foresight and understanding in the computer scientists who wrote this book which, unfortunately, is not as common as you’d expect.
The writers tie this book together at the end by highlighting the importance of the human aspect when trying to resolve things optimally, such as reducing cognitive load. An example of this is where the US uses quarters etc when the way to reduce change the most amount would be 18 cents, thus making it far easier for cashiers to calculate change.
I think this final part ties the book together well as it serves as a reminder that, although algorithms can be helpful for easier situations, they should not be haphazardly applied without considering the human aspect. Since the release of this book, several issues with deep learning have also been reported to the mainstream news such as ingrained racism in the training data. This highlights a degree of foresight and understanding in the computer scientists who wrote this book which, unfortunately, is not as common as you’d expect.
alir777's review against another edition
informative
medium-paced
2.5
The premises of this book were very promising, but I sadly found it dry and prolix. Although there were some chapters I appreciated, I believe that overall the authors fail in their aim to provide a useful account toward everyday life decisions/situations.
vikingvisuals's review against another edition
informative
slow-paced
3.0
Although the book is informative, extremely well researched, and at times witty, it was way to slow for my taste and missed, in my opinion, the mark of its very title.
Given the title I was expecting much more insight into leveraging various algorithms for daily life, but instead each chapter seems to delve more into how certain algorithms came to be and what technical or other challenges they were formulated around, then a competitively abrupt note on more practical applications. The insight is more inferred in the texts than actually highlighting meaningful and actionable insights.
I feel the book caters to a general audience with the title, but then goes overly in depth into aspects of the algorithms that may put the general audience off while also being likely too general for people with a more technical/philosophical/statistical background.
I would recommend to someone interested in the subject that may be somewhat more new to it, but otherwise feel a lot of the main points that could be pertainant to daily life could be either summed up or expanded with less emphasis on the historical background.
Given the title I was expecting much more insight into leveraging various algorithms for daily life, but instead each chapter seems to delve more into how certain algorithms came to be and what technical or other challenges they were formulated around, then a competitively abrupt note on more practical applications. The insight is more inferred in the texts than actually highlighting meaningful and actionable insights.
I feel the book caters to a general audience with the title, but then goes overly in depth into aspects of the algorithms that may put the general audience off while also being likely too general for people with a more technical/philosophical/statistical background.
I would recommend to someone interested in the subject that may be somewhat more new to it, but otherwise feel a lot of the main points that could be pertainant to daily life could be either summed up or expanded with less emphasis on the historical background.
catherzh's review against another edition
5.0
Never thought I’d truly enjoy reading a book about algorithms, but this was a super fun and compelling read bringing theory from mathematics and computer science to life with history, context, and real life applications or parallels. The textbook I wish I had while I was pursuing my undergraduate CS degree!
szeckirjr's review against another edition
5.0
damn!! first of all, what a well written book! felt like my pal yuval’s writing at parts, really enjoyed it
second, what a cool topic!! I’m super biased being in software eng but the authors did such a good job of compiling all the main topics in computing, and then comparing and contrasting them to real world examples
very very cool and well thought out book
p.s.: my friends joke that I talk like a computer already, this book has multiplied that by tenfold
second, what a cool topic!! I’m super biased being in software eng but the authors did such a good job of compiling all the main topics in computing, and then comparing and contrasting them to real world examples
very very cool and well thought out book
p.s.: my friends joke that I talk like a computer already, this book has multiplied that by tenfold
t_shaffner's review against another edition
3.0
I enjoyed this book. In the midst of classes on machine learning and programming algorithms there were, fortuitously, several places in which the algorithms it discussed were ones I'd learned recently and it both helped give me a broader theoretical perspective on some of them and link them to every day life. And more generally, it felt like the perspective this brought was useful in a number of places and might be interesting and helpful to apply to life. This was particularly true in the comments about the perspective on turning away a relative or friend who repeatedly asks for and abuses trust as a relation to internet connection behavior; i.e. double the time you wait before accepting again, allowing one to both be careful and protect oneself and yet never turn someone away.
On the flipside though, a number of the instances in this book seemed a bit of a stretch to apply to daily life. The mathematical cases used were often too clean to be truly comparable, or the "insights" gained were not likely to be particularly helpful. In the few cases where they might be they seemed also just as likely to be quickly forgettable while simultaneously not being good enough to merit the work required to memorize them and build them into daily life. The one above was the one exception to that, and the others, while fun, didn't feel necessarily likely to actually be useful much in life.
The end result though was still a fun read with some interesting perspective and insights and a useful complement to my studies. The net result being I'm glad I read it.
On the flipside though, a number of the instances in this book seemed a bit of a stretch to apply to daily life. The mathematical cases used were often too clean to be truly comparable, or the "insights" gained were not likely to be particularly helpful. In the few cases where they might be they seemed also just as likely to be quickly forgettable while simultaneously not being good enough to merit the work required to memorize them and build them into daily life. The one above was the one exception to that, and the others, while fun, didn't feel necessarily likely to actually be useful much in life.
The end result though was still a fun read with some interesting perspective and insights and a useful complement to my studies. The net result being I'm glad I read it.