Algorithms to Live By: The Computer Science of Human Decisions Book Summaries - You Exec

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By: Brian Christian and Tom Griffiths24-MINUTE AUDIO / 3046 WORDS (13 PAGES)
SYNOPSISCan computer science teach us the secrets of life? Perhaps not, but it can shed light on how certain everyday processes work and how to exploit them. Algorithms are everywhere, from following a recipe to the order in which you sort your email.
In Algorithms to Live By, programmer and researcher Brian Christian and psychology and cognitive science professor at UC Berkeley Tom Griffiths share the many ways that algorithms shape everything from the way we remember things to how we make big and small decisions. 





























































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TOP 20 INSIGHTSThe "37% rule" refers to a series of steps, or algorithms, that someone must follow to make the best decision within a set amount of time. Someone allots 37% of their time to research before they make a decision, then commits to the very next "best choice" they find. 
The "explore/exploit" trade-off refers to the need to balance the tried and tested with the new and risky. The payoff of this algorithm depends entirely on how much time you have to make decisions. People are more likely to visit their favorite restaurant on their last night in town than risk something new.
Developed in 1952 by mathematician Herbert Robins, the "Win-Stay, Lose-Shift" algorithm uses slot machines as a metaphor. Choose a machine at random and play it until you lose. Then switch to another machine; this method was proven to be more reliable than chance.
A psychology study found that given choices, people often "over explore" rather than exploit a win. Given 15 opportunities to choose which slot machine would win, 47% used Win-Stay, Lose-Shift strategies, and 22% chose machines randomly instead of staying with a machine that paid out.
Hollywood is a prime example of the exploit tactic. The number of movie sequels has steadily increased over the last decade. In both 2013 and 2014, seven of the Top 10 films were either sequels or prequels. The trend is likely to change if new movie ideas draw more box office dollars.
The A/B test is similar to the two slot machine scenario in that you stick with the option that performs best. More than 90% of Google's $50 million in annual revenue is from paid advertisements, which means that explore/exploit algorithms power a large portion of the internet. 
The Gittins Index provides a framework of odds that assume you have an indefinite amount of time to achieve the best payoff, but the chances reduce the longer you wait. For example: choose a slot machine with a track record of one-to-one wins/losses (50%) over the machine that has won nine out of 18 times.
"Upper Confidence Bound" algorithms offer more room for discovery than the "Win-Stay, Lose-Shift" method. This algorithm assigns a value based on what "could be" based on the information available. A new restaurant has a 50/50 chance to provide a good experience because you have never been there.
The "Shortest Processing Time" algorithm requires that you complete the quickest tasks first. Divide the importance of the task by how long it will take. Onl

By: Brian Christian and Tom Griffiths24-MINUTE AUDIO / 3046 WORDS (13 PAGES)
SYNOPSISCan computer science teach us the secrets of life? Perhaps not, but it can shed light on how certain everyday processes work and how to exploit them. Algorithms are everywhere, from following a recipe to the order in which you sort your email.
In Algorithms to Live By, programmer and researcher Brian Christian and psychology and cognitive science professor at UC Berkeley Tom Griffiths share the many ways that algorithms shape everything from the way we remember things to how we make big and small decisions. 





























































DIAGRAMS

























View fullsize
























View fullsize



























TOP 20 INSIGHTSThe "37% rule" refers to a series of steps, or algorithms, that someone must follow to make the best decision within a set amount of time. Someone allots 37% of their time to research before they make a decision, then commits to the very next "best choice" they find. 
The "explore/exploit" trade-off refers to the need to balance the tried and tested with the new and risky. The payoff of this algorithm depends entirely on how much time you have to make decisions. People are more likely to visit their favorite restaurant on their last night in town than risk something new.
Developed in 1952 by mathematician Herbert Robins, the "Win-Stay, Lose-Shift" algorithm uses slot machines as a metaphor. Choose a machine at random and play it until you lose. Then switch to another machine; this method was proven to be more reliable than chance.
A psychology study found that given choices, people often "over explore" rather than exploit a win. Given 15 opportunities to choose which slot machine would win, 47% used Win-Stay, Lose-Shift strategies, and 22% chose machines randomly instead of staying with a machine that paid out.
Hollywood is a prime example of the exploit tactic. The number of movie sequels has steadily increased over the last decade. In both 2013 and 2014, seven of the Top 10 films were either sequels or prequels. The trend is likely to change if new movie ideas draw more box office dollars.
The A/B test is similar to the two slot machine scenario in that you stick with the option that performs best. More than 90% of Google's $50 million in annual revenue is from paid advertisements, which means that explore/exploit algorithms power a large portion of the internet. 
The Gittins Index provides a framework of odds that assume you have an indefinite amount of time to achieve the best payoff, but the chances reduce the longer you wait. For example: choose a slot machine with a track record of one-to-one wins/losses (50%) over the machine that has won nine out of 18 times.
"Upper Confidence Bound" algorithms offer more room for discovery than the "Win-Stay, Lose-Shift" method. This algorithm assigns a value based on what "could be" based on the information available. A new restaurant has a 50/50 chance to provide a good experience because you have never been there.
The "Shortest Processing Time" algorithm requires that you complete the quickest tasks first. Divide the importance of the task by how long it will take. Onl