The Eye Test
A Case for Human Creativity in the Age of Analytics
Failed to add items
Add to Cart failed.
Add to Wish List failed.
Remove from wish list failed.
Follow podcast failed
Unfollow podcast failed
The Eye Test
Buy Now for $25.24
No default payment method selected.
We are sorry. We are not allowed to sell this product with the selected payment method
-
Narrated by:
-
Chris Jones
-
Written by:
-
Chris Jones
About this listen
In a world increasingly ruled by numbers and algorithms, award-winning journalist Chris Jones makes a compelling case for a more personal approach to analytical thinking.
The Eye Test is a necessary course correction, a call for a more balanced, personal approach to problem-solving. Award-winning journalist Chris Jones makes the case for the human element - for what smart, practiced, devoted people can bring to situations that have proved resistant to analytics. Jones shares what he’s learned from an army of extraordinary talents, including some of the best doctors, executives, athletes, meteorologists, magicians, designers, astrophysicists, and detectives in the world. There are lessons in their mastery.
Of course, there is a place for numbers in decision-making. No baseball player should be judged by his jawline. But the analytics revolution sparked by Michael Lewis’ Moneyball now threatens to replace one kind of absurdity with another. We have developed a blind faith in the machine, the way a driver overly reliant on his GPS might be led off the edge of a cliff. Not all statistical analysis is sound. Algorithms aren’t infallible, and spreadsheets aren’t testaments. Trust in them too much, and they risk becoming instruments of destruction rather than understanding.
Worse, data’s supremacy in our daily lives has led to a dangerous strain of anti-expertise: the belief that every problem is a math problem, and anyone given access to the right information will find the right answer. That taste doesn’t matter, experience doesn’t matter, creativity doesn’t matter. That we can’t believe our eyes, no matter how much they’ve seen.
The Eye Test serves as a reminder that if beauty is less of a virtue in the age of analytics, a good eye still is. This book is a celebration of our greatest beholders - and an absorbing, inspiring guide for how you might become one, too.
©2022 Chris Jones (P)2022 TwelveWhat the critics say
“If you’re worried that data are replacing human judgment instead of informing it, you’re going to love this book. If you’re confident that data from the past can always predict the future, you desperately need to read this book. With convincing arguments and delightful writing, Chris Jones makes the case for putting people back in the analytics equation.” (Adam Grant, number one New York Times best-selling author of Think Again and host of the TED podcast WorkLife)
"This is the rare book that will alter the way you perceive the world. It's a story, an argument, a manifesto even: a prayer for a more kind, more creative, more empathetic world. Chris Jones is writing about the human race paused at a fork in the road, and he puts us at that fork with our brothers and sisters. And so, finally, and perhaps most of all, THE EYE TEST serves as a map, out of this artificial mechanical wilderness and back to the flickering light of ourselves." (Wright Thompson, New York Times best-selling author of Pappyland and The Cost of These Dreams)
“Extremes are rarely a good thing - in politics, sports, or our culture. Chris Jones knows that, offering a nuanced argument that while analytics are all the rage, there isn’t any sort of mathematical equation to ensure success.” (Chris Cillizza, host of CNN's The Point)
What listeners say about The Eye Test
Average Customer RatingsReviews - Please select the tabs below to change the source of reviews.
-
Overall5 out of 5 stars
-
Performance5 out of 5 stars
-
Story4 out of 5 stars
- Amazon Customer
- 2023-01-18
A thought provoking book
I loved this book! So much food for thought about human creativity and data and analytics.
Something went wrong. Please try again in a few minutes.
You voted on this review!
You reported this review!
-
Overall5 out of 5 stars
-
Performance5 out of 5 stars
-
Story5 out of 5 stars
- Kindle Customer
- 2022-08-03
Insightful and entertaining!
It’s refreshing to hear that processing information as a mere human can be equally if not more advantageous *depending on the circumstances. Using technological tools to assist with analysis is fine and encouraged, but shouldn’t be the only or final factor. Well read and very entertaining.
Something went wrong. Please try again in a few minutes.
You voted on this review!
You reported this review!
-
Overall1 out of 5 stars
-
Performance1 out of 5 stars
-
Story1 out of 5 stars
- Anonymous User
- 2023-12-17
What if weapons of math destruction was worse?
It’s good that the author cited O’Neil’s “Weapons of math destruction” because this book is a much worse version of that book.
He brings up numerous examples of obvious statistic traps any good statistician, data scientist, data analyst etc. should already be aware of and working to prevent / avoid. Nobody working with data thinks these algorithms should be blindly trusted, and if they do, that person is an wrong, and the problem of people being wrong has nothing to do with statistic models, it’s just an inevitability of human life.
He also very much ignores obvious push backs. For example there is a chapter about racist policing algorithms. These do exist and are of course a large problem. But! In a book about why we should be using intuition instead, he fails to address an obvious pushback.
A- policing was notoriously racist before analytics were ever used.
B- at one point he mentions a racist algorithm has been problematic, but he mentions that police were using their OWN DISCRETION ABOUT WHEN TO LISTEN TO THE MODEL AND THEY USED THEIR OWN DISCRETION TO MAKE RACIST DECISIONS. He literally says that when people are allowed to use their own intuition they are racist in his argument about the value of intuition. It’s honestly remarkable.
So yeah, his book essentially just points out statistics can be used for bad in many cases. This is true, and this is a problem, but it is always people making the decisions and he ignores this. Even if an algorithm has been run, a person, using their own version of the eye test will be choosing what to do about it. And if the algorithm learned to be racist, it will have learned that from past human actions. The model doesn’t just become racist, it takes racist humans to make that happen. So like I guess then his argument would be racist people are bad? That is so obviously true it doesn’t need. A book.
So he just points out problems that algorithms can be bad in many obvious ways any good person working on such algorithms should already know. And completely ignores counter factuals, like how people were racist before the algorithm was in place. This means the root problem may be system racism which is a function of humans, not some algorithm.
Plus he offers no real solutions. In weapons of math destruction O’Neil offers a much better descriptions of the algorithms themselves , and detailed ideas to solve thee problems. For example how statistics which can be used to infer race should not be allowed in things like policing algorithms. That is useful! So just buy that book instead. It’s much better. He should have just retweeted her book on Twitter instead of wasting his time with this derivative book
Something went wrong. Please try again in a few minutes.
You voted on this review!
You reported this review!