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The Mathematical Corporation: Where Human Ingenuity and Thinking Machines Design the Future
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The Mathematical Corporation: Where Human Ingenuity and Thinking Machines Design the Future

3.39  ·  Rating details ·  127 ratings  ·  10 reviews
The Mathematical Corporation breaks new and important ground by restoring the importance of people, especially those in leadership roles, in harnessing the synergistic combination of fast computing, algorithms, and big data to attain organizational and competitive advantage. The technology is powerful but it is still a toolone used by people to apply human ingenuity, ...more
ebook, 304 pages
Published June 6th 2017 by PublicAffairs
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Nick Ertz
Jul 15, 2017 rated it liked it
First the authors clearly have drank the kool-aide. However, the book is a strong guide for the leader of a enterprise that depends on data. Part of the point is that nearly every corporation should be looking at the data that is available to them and how it can move the firm forward. Most valuable in the book is an excellent review and discussion of the ethics lurking behind big data. This is not a how-to book, but rather a why not.
Olivier Cruchant
Jul 06, 2017 rated it did not like it
Shelves: business
I read only the first 35%
the book contains a lot of qualitative terms and is extremely fuzzy when it comes to technical concepts, be they about the math or CS aspect of data-driven management. It looks more like a marketing prospectus
Charles Franklin
Apr 07, 2017 rated it it was amazing  ·  review of another edition
Shelves: future-of-work
This book dramatically changed how I viewed the future of business forever. Instead of pitting humans vs robots in the future, it argues that business should embrace the capabilities of both.

This is both a good thing and a bad thing for the future of our workforce.

On the one hand, it offers a way to participate in the next industrial revolution. There will be new jobs doing all kinds that humans can't even imagine. On the other hand, the dramatic shift towards automation, artificial
...more
Matt Heavner
This is a very buzzword, business-speak look at "machine intelligence." There are many anecdotes, but I felt it was lacking in specifics/details. This is a peak inside the buzz-cycle. If you are already over the big data, data science, machine learning, then you need this book. Big data is now the data lake. APIs are a new miracle (not... they are definitely a great thing, but new??). It was a worthwhile read, but I wondered if this was machine generated? The target is the "thought leaders" (or ...more
Devin
Jul 04, 2018 rated it did not like it
Skip this book. I recently started working for an AI company as a business person and read every high-rated book in the space. This one has virtually no meaningful content and is full of vague consultant-speak like "future power" and "big mind". I'm pretty sure the authors have never worked on any meaningful AI projects, otherwise they would have had more valuable expertise to share.
KT
Nov 27, 2017 rated it liked it  ·  review of another edition
Shelves: i-know-stuff
I got this book as a freebie at work. It was the first (and only) book I've read on this topic so some parts may be totally obvious and cliched to people who actually follow the subject closely. However, it was an adequate introduction. The chapter on data ownership and ethics was surprisingly quite good and compelling - nice little bonus amidst otherwise dry subject matter.
Nilesh
Nov 14, 2017 rated it liked it
Shelves: new-sciences
With AI, Big Data, Machine Learning and other technologies, the way we decide has changed. And, this is definitely true at the organization level, as the book forcefully and rightly points out.

Historically, decision making was deductive. Without much data and analysis, perceptive were leaders who could apply a priori logic to arrive at the decisions that are proven right later. Even if some of these decisions were based on nothing but the gut, the good leaders were those that were confident and
...more
Theodore Kinni
Good intro to how machine learning will change how we do business. I introduced a curated excerpt here: http://sloanreview.mit.edu/article/et...
Matt S
Aug 10, 2018 rated it liked it  ·  review of another edition
The book is a mixed bag. The authors cover some interesting ground with great detail - the chapters on data ethics and what types of knowledge are at risk vs. safe from automation were great - but then they'll switch into vague topics with incredibly fluffy writing. (Here's an excerpt from p.156: "But when the answer is over the horizon, no amount of analysis of the landscape up front will reveal it. You need to go on a learning journey - sailing to the far shores to find the best answer.") Then ...more
Cliff Chew
Jul 28, 2018 rated it really liked it  ·  review of another edition
This book doesn't cover any algorithms or models, but I think it's a good book for management people to read. Also a good book for someone wants to be more strategic about data, rather than one who is trying to improve the accuracy of their models.

See this book as one which tries to help you get business value from your analytics models. Definitely has some interesting thinking points that I am trying to work on from here on.
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