Simple Heuristics that Make Us Smart (Evolution and Cognition) 1st Edition, Kindle Edition

by Gerd Gigerenzer (Author), Peter M. Todd (Author), ABC Research Group (Author)

13 customer reviews

ISBN-13: 978-0195143812

ISBN-10: 0195143817

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Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality.
But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market.
As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions.

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Product details

File Size: 5764 KB
Print Length: 416 pages
Publisher: Oxford University Press; 1 edition (August 31, 2000)
Publication Date: September 30, 1999
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B000U8R31Q
Text-to-Speech: Enabled

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Word Wise: Enabled
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Enhanced Typesetting: Not Enabled

Amazon Best Sellers Rank: #780,020 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
- #331 in Kindle Store > Kindle eBooks > Nonfiction > Politics & Social Sciences > Philosophy > Logic & Language
- #381 in Kindle Store > Kindle eBooks > Computers & Technology > Computer Science > Artificial Intelligence > AI & Semantics
- #1018 in Kindle Store > Kindle eBooks > Nonfiction > Science > Behavioral Sciences > Cognitive Psychology

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Michael Valenzuela

Our computerized approaches to decision making are wrong! This book can help.

March 21, 2016

Format: PaperbackVerified Purchase

This book contains a collection of essays discussing how intelligent creatures actually make decisions. The book presents a dichotomy of formal/standard approaches (e.g., multiple linear regression) and fast & frugal heuristics. The following comparison is a little unfair, but it should be useful for the less technical readers: traditional AI approaches are like being "book smart" and the heuristics discussed and defended in this book are like being "street smart."

Let me elaborate. Many standard approaches are radically different from how we, as intelligent beings, think. Many (most) formal decision making algorithms are based on machine learning approaches, which simply process the data, ignoring the data collection task. They are data hungry. Give them the perfect data set and they can break records (or beat players at the game called Go).

Alternatively, the fast and frugal heuristics take into account that information might be hard to come by in the first place. Moreover, these heuristics are much easier to follow in real life. They are based on three simple principles:
(1) Simple search rules,
(2) Simple stopping rules, and
(3) Simple decision rules.
The primary reasons one should care about fast and frugal heuristics is that they:
(A) Are ecologically rational, meaning they can be implemented with limited time, mental effort, and other resources,
(B) In many cases perform as well as more sophisticated algorithms, and
(C) Provide insight into real life intelligences.

The heuristics presented here are not necessarily going to win in top Artificial Intelligence (AI) competitions, but are still surprisingly useful. These heuristics are more biological-like AI.

5 people found this helpful

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baylor

Well, i liked it anyway

December 29, 2003

Format: PaperbackVerified Purchase

Whether you like a book depends on what information you're looking for. i make computer models of human behavior so this book, which is easy to read but filled with concrete solutions and lots of supporting dat, was near-perfect for me
As a note, i'm picky when it comes both to writing and thinking. And i hate most books written by academics. Even the ones with good information (eg, Fodor's Modularity) are hard to read and filled with confusing, field-specific words. Not this book. It's really well written. Written in plain English, very few assumptions, very thorough analysis, lots of self-criticism, lots and lots of data (OK, that part is boring and can be skipped, but it's comforting to know it's there)
What's it about? Common AI, psych and economic decision and learning algorithms (decision trees, neural nets, Bayes, multiple linear regression, etc.) are compared to several absurdly simple algorithms the authors believe real humans use. The various approaches are compared and evaluated on the basis of performance, accuracy on training data, accuracy on test data (generalization) and amount of input data required. Tests are on the standard UC Irvine data learning test sets. Comparisions, outcome explanations and relevance to the human mind and the real world are provided. Explanations and analysises are easy to understand and pretty convincing
i've decided to use a lot of what was in this book in my software, things that have made my agents more natural and easier to implement. i absolutely love this book

71 people found this helpful

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Ramiro R.

Five Stars

July 30, 2017

Format: PaperbackVerified Purchase

Excellent!

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Muir

Why are so many books about 'biases''wrong? (Oh, and in the process, can I lead a happier life?)

December 28, 2012

Format: HardcoverVerified Purchase

-

Are we really that flawed that in order to figure out which pizza to order you need to do multiple regression analysis?

Or do we survive (and have for millennia) because we are part of the order of things, and as such, have innately within us, the correct mechanisms to figure out things.

Or, are these mechanisms outdated in Modern society?

Gigerenzer makes a very compelling argument for, not against, Heuristics.

We are not flawed beyond repair in our thinking process.

But maybe some that espouse 'biases' are.

We do not have (or need) a computer-like brain, or worse, have a moral dictate to be an efficient being (even when such an attempt actually makes us less efficient!)

Highly recommended.

-

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William Blanton Sr.

Three Stars

January 14, 2018

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Bookeater

Too technical for me.

July 15, 2010

Format: PaperbackVerified Purchase

This book reads like a PhD thesis re-written for mass consumption. All the statistics are coma-inducing and I felt like I had to hunt for useful information. I don't recommend it for the Kindle because some of the most useful information was presented in tiny charts which render poorly on my Gen II.

I give it two stars because it presents a truly innovative approach to the science of decision making and, though almost impossible to finish, it taught me something new.

10 people found this helpful

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Peter McCluskey

Some good ideas, less widely applicable than they suggest

April 30, 2010

Format: Paperback

This book presents serious arguments in favor of using simple rules to make most decisions. They present many examples where getting a quick answer by evaluating a minimal amount of data produces almost as accurate a result as highly sophisticated models. They point out that ignoring information can minimize some biases: "people seldom consider more than one or two factors at any one time, although they feel that they can take a host of factors into account". (Tetlock makes similar suggestions in Expert Political Judgment).

They appear to overstate the extent to which their evidence generalizes. They test their stock market heuristic on a mere six months worth of data. If they knew much about stock markets, they'd realize that there are a lot more bad heuristics which work for a few years at a time than there are good heuristics. I'll bet that theirs will do worse than random in most decades.

The book's conclusions can be understood by skimming small parts of the book. Most of the book is devoted to detailed discussions of the evidence. I suggest following the book's advice when reading it - don't try to evaluate all the evidence, just pick out a few pieces.

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