The Efficiency Paradox
What Big Data Can't Do
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Narrado por:
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Jason Culp
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De:
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Edward Tenner
Algorithms, multitasking, the sharing economy, life hacks: our culture can't get enough of efficiency. One of the great promises of the Internet and big data revolutions is the idea that we can improve the processes and routines of our work and personal lives to get more done in less time than we ever have before. There is no doubt that we're performing at higher levels and moving at unprecedented speed, but what if we're headed in the wrong direction?
Melding the long-term history of technology with the latest headlines and findings of computer science and social science, The Efficiency Paradox questions our ingrained assumptions about efficiency, persuasively showing how relying on the algorithms of digital platforms can in fact lead to wasted efforts, missed opportunities, and, above all, an inability to break out of established patterns. Edward Tenner reveals what we and our institutions, when equipped with an astute combination of artificial intelligence and trained intuition, can learn from the random and unexpected.
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Not a original thought, explained in an affected scientific tone, floating in a sea of contradictory citations.
Here and there, some insights.
Commonplace
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Good Listen
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I HIGHLY RECOMMEND this book to intellectuals, as well as people who are looking to improve their own lives without being preached at by a life coach or self-provlaimed know-it-all.
I SOMEWHAT RECOMMEND this book to corporate morning commuters who would like to think about what their roles are in the grabd scheme of things. I say somewhat, because it’s a little hard to pay attention to this book when tired. It’s packed with information and analysis, and it is thus not the easiest of listens.
I DO NOT RECOMMEND this book for those looking for a good story. As I said previously, this is a highly informational book (which I still think everyone should listen to), but don’t expect to feel overly entertained.
An extremely useful book, told slightly monotonically
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