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Machine, Platform, Crowd: Harnessing Our Digital Future
“A clear and crisply written account of machine intelligence, big data and the sharing economy. But McAfee and Brynjolfsson also wisely acknowledge the limitations of their futurology and avoid over-simplification.” ― Financial Times In The Second Machine Age , Andrew McAfee and Erik Brynjolfsson predicted some of the far-reaching effects of digital technologies on our lives and businesses. Now they’ve written a guide to help readers make the most of our collective future. Machine | Platform | Crowd outlines the opportunities and challenges inherent in the science fiction technologies that have come to life in recent years, like self-driving cars and 3D printers, online platforms for renting outfits and scheduling workouts, or crowd-sourced medical research and financial instruments.
416 pages, Paperback
First published June 27, 2017
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July 30, 2017
Warning! Red Alert! At the end of each chapter this book has summaries of the main points and questions, and in particular questions about how the content of the chapter may relate to the goings on at “your employer.” It is clearly meant to be packaged into “continued education” courses offered by the authors’ employer (the Sloane School of Business at MIT) to middle aged (hence the enormous print) middle managers on a two-week jolly / off-site / executive MBA. This, sadly, I discovered only after the book had come through the mail.
I decided to read it anyway, because the authors of “Machine Platform Crowd” are who I thank for waking me up to the fact that we are living through a proper, bona-fide depression. Just like the depression that the discovery of the tractor and phosphates caused in the 1930’s, by dint of putting out of work, permanently, the 25% of the US workforce who used to work in agriculture, McAfee and Brynjolfsson argued six year ago in their 76 page monograph “Race Against the Machine” that we are living a new depression brought about by a “Second Machine Age.” (which is the title of their second, less sombre, book, incidentally) The victims this time round are educated people who do repetitive work that once upon a time (but not any more!) could only be performed by an educated human. Oh, and we’re only getting started.
Sure, blame the deficits, blame the banks, blame the ninja loans, blame the Fed, blame who you like, but only for trying to solve this intractable problem in silly ways that won’t work and thereby for making things even worse. The deeper cause of the depression, however, is that the educated class has educated itself to do repetitive tasks that are increasingly done by machines. Oh, and the 1% of guys who can “run with the machines,” yeah, they are going to be the bad-guy 1 percenters. Ooops.
This was a good way for the authors to become famous (and earn my respect forever) but not a terribly good way to get rich themselves! “Dismal” does not sell. Ask that Malthus fellow.
Boy, have they changed tack since 2011.
“Machine Platform Crowd” is to the machine age what Candide and Ingenu were to the Enlightenment, but with no trace of irony, sarcasm or, indeed, doubt about what promises to be the best of possible worlds.
Let’s start with us humans. We suck at judgement, it turns out. Our Kahneman “System 1” is trash and an algorithm will always beat it. But wait. Not all is lost! That info is solid gold for those of us who are smart enough to understand that we have been doing things backwards. All we need to do is let our “System 1” free to come up with whatever garbage a billion of years of evolution have taught it to do, and then feed it all as input to the algorithm. Job done. Conversely, don’t dare take the results of the algorithm and judge them with your experience. You’ll mess it all up.
Don’t meet the client. Trust that FICO score. Call up the guys at FICO and ask politely if their computer will talk to your loan officer. It may well be able to process his otherwise useless experience into an even better FICO score. (You’ve guessed right, it does not say this in the book, that’s me extrapolating, sorry)
Next let’s look at the machines themselves. In the words of ZZ Top, they come in two classes: First, the kind that we program with some sensible ideas we have (example “adjectives in English absolutely have to be in this order: opinion-size-age-shape-color-origin-material-purpose-Noun” p.70) and then have the machine implement much faster than we ever could. Second, the kind that don’t need us at all and look at reams of data and come back with some answer and we just tell them how well they guessed. (That’s called “supervised learning” for those in the back who are not paying attention)
The first kind has been beating idiots like me at chess since I can remember. The second kind (steered, but not quite, by a fellow Greek, let’s hear it for Demis!) did something much more awesome the other day, it beat the world champion in Go, which is apparently much harder because there are fewer atoms in the known universe (and any undiscovered parallel universes) than there are ways to lay your pieces on a Go board. Maybe. Approximately. Where’s Val Kilmer when I need him?
The second kind of machine does not know what it knows or how it learned it, it embodies the Polanyi paradox. What’s new and amazing, basically, is a machine that, like me, could not tell you why it played the move, but very much unlike me, plays the correct move! All from having played many many many more times than I ever have, mostly with itself. (no, honestly, that’s what it does) And it’s finally possible today thanks to (i) Moore’s Law (ii) Amazon Web Services and (iii) the availability of “big data” to train itself on.
The future is in machines that don’t know what they know, just like us, basically. Instead of asking for the “Highest Paid Person’s Opinion,” also known as the HiPPO, ask this machine. It may not know what a liver transplant is, but if it thinks you need one, stop reading and call Alvin Roth now. (Kidney, liver, it’s all the same, don’t heckle! Instead, pray that it’s as well trained in recommending rare medical procedures as Demis’ Deep Mind is at playing Go with itself. I’m sure it will be fine. Better than the highest paid doctor’s opinion, you can be sure of that.)
The final frontier is that machines are starting to do creative work. Exactly how they play Go without knowing why they played the move, merely that it will probably work, they can design a radiator that looks like no radiator you’ve seen before, rig up a very effective chassis for your racing car, or compose a piece of music that you are likely to enjoy. Amazingly, after all the mumbo jumbo of the first 100 pages in the book, I actually found this (fifth!) chapter to be totally fascinating and convincing.
From “Machine” the book moves on to “Platform,” which actually is a tremendous section. (There are two authors at work here, basically, and this is the one I prefer)
The authors start by explaining that Apple makes 110% of all money made in phones today because 1. it controls the “platform” for all the apps and 2. nobody is counting the money Google is making off of Android. Jokes aside, they make the very strong point that making devices comes down to competing on costs, whereas establishing a platform allows you to reap the positive externalities generated by every single new participant in your platform. The virtuous circle works like this:
• every app that runs on an iPhone creates demand for the iPhone itself
• if many people own an iPhone, this creates a bigger supply of good apps
So 700 dollars is a lot of money for a telephone, but not if it can run 700 apps you’d pay a dollar each for, and things work out such that it will. And Apple no longer has to find its competitive edge in squeezing down the costs of making its beautiful devices.
Next come up the “two-sided” platforms, which are all the craze. I do not remember my days of starting book2eat.com that fondly (a good 40 VC’s were aghast at the fact that I was trying to sign up both restaurants and punters at the same time, and another 200 never answered my calls or emails) but the point is that if you manage to fill more seats the word gets out and you sign up more restaurants and if you’ve signed up more restaurants punters are likelier to make a booking on your platform and this creates a dynamic that becomes irresistible. So much so, that for example a company called ClassPass (that filled exercise studios with punters who were happy to be told at the last minute where to take their yoga mat to) had to revise its pricing policy (p. 178) due to the unmitigated success of the business model in filling exercise classes!
Next up is an analysis of Uber. Here I finally understood something that had always been a mystery to me: Uber’s obsession with low price is so huge because that’s where the demand curve is most elastic: All the way to the right, the demand curve is almost horizontal. People switch over from the train to Uber at some point, basically, and then all your cabs are full all of the time. The chart is on p. 213 and I totally buy it. Congestion in that city would be awful, but that’s down to the choice of the taxi example, of course. The point about why double-sided platforms love a low price is very well made.
The way ratings have solved the asymmetric information problem is discussed here too, with the inevitable name-dropping of the authors’ colleague down the hall who got the Nobel Prize for first posing it. Oh, and don’t worry, Airbnb will not kill the hotels industry, because hotels cater to business travelers. Don’t forget, it’s all good! The fate of the cabbies and the longshoremen is left to the reader to ponder, but they can all go work for Travis, no?
The third, final, section of the book is about “the crowd”
It starts by explaining that crowdsourced software rocks, basically, and that the ingredients you need are:
1. Openness: who knows what motivates them, but people do contribute
2. Noncredentialism: good software can be written by absolutely anyone
3. Verifiable and reversible contributions: unlike a novel, you can test software quickly and undo any poor contributions
4. Clear outcomes: via a good license you can assure coders that their work will remain public
5. Self-organization: people do best the work that they WANT to do and if that leads to a fork in the code, so be it
6. Geeky leadership: it’s the kind coders will write code for
Hayek and Polanyi make another guest appeareance in the chapter, but it works fine without them.
A further important point about the crowd is that very often the contribution to a project that makes the big difference does not come from an expert in the field. Indeed, the knowledge that will cut the Gordian knot may come from somebody with knowledge that is “far away” from the subject, i.e. somebody who will be surplus to requirements 99% of the time and thus a team of experts could never afford to have on board: “The expert you know is not the expert you need,” basically. He’s somewhere in the crowd and that’s where you must reach for him.
From there we jump to a painfully banal chapter on Bitcoin that addresses the points about cryptocurrency I could not care less about (like the mechanics of how it works, described just inaccurately enough for you not to be able to actually work it out, or the effete generalization that blockchain may be more important than Bitcoin,) barely gets into the aspects that matter (is it money? How does it provide store of value if there can be a million different otherwise scarce and deflationary varieties of Bitcoin? How will it compete if nobody will accept to be paid tax in it?) and complains that the Chinese are now dominating it.
By that point, we find ourselves in a final chapter that’s nothing to do with Machine, Platform or Crowd, but is there to make the customers feel good who are attending the seminar and assures them that companies will still carry on being necessary in the future, because they are who possesses “the residual rights to control: the right to make decisions not specified in contracts.”
Given that, presumably for the benefit of the same attendees, there is a need to sketch (very well, I must say, see pp 154-156) how the demand curve and the supply curve work and what happens when they intersect, one can safely say that this short paean to the firm is guaranteed to go over their head. But it must make for a warm conclusion. And now, back to work!
I decided to read it anyway, because the authors of “Machine Platform Crowd” are who I thank for waking me up to the fact that we are living through a proper, bona-fide depression. Just like the depression that the discovery of the tractor and phosphates caused in the 1930’s, by dint of putting out of work, permanently, the 25% of the US workforce who used to work in agriculture, McAfee and Brynjolfsson argued six year ago in their 76 page monograph “Race Against the Machine” that we are living a new depression brought about by a “Second Machine Age.” (which is the title of their second, less sombre, book, incidentally) The victims this time round are educated people who do repetitive work that once upon a time (but not any more!) could only be performed by an educated human. Oh, and we’re only getting started.
Sure, blame the deficits, blame the banks, blame the ninja loans, blame the Fed, blame who you like, but only for trying to solve this intractable problem in silly ways that won’t work and thereby for making things even worse. The deeper cause of the depression, however, is that the educated class has educated itself to do repetitive tasks that are increasingly done by machines. Oh, and the 1% of guys who can “run with the machines,” yeah, they are going to be the bad-guy 1 percenters. Ooops.
This was a good way for the authors to become famous (and earn my respect forever) but not a terribly good way to get rich themselves! “Dismal” does not sell. Ask that Malthus fellow.
Boy, have they changed tack since 2011.
“Machine Platform Crowd” is to the machine age what Candide and Ingenu were to the Enlightenment, but with no trace of irony, sarcasm or, indeed, doubt about what promises to be the best of possible worlds.
Let’s start with us humans. We suck at judgement, it turns out. Our Kahneman “System 1” is trash and an algorithm will always beat it. But wait. Not all is lost! That info is solid gold for those of us who are smart enough to understand that we have been doing things backwards. All we need to do is let our “System 1” free to come up with whatever garbage a billion of years of evolution have taught it to do, and then feed it all as input to the algorithm. Job done. Conversely, don’t dare take the results of the algorithm and judge them with your experience. You’ll mess it all up.
Don’t meet the client. Trust that FICO score. Call up the guys at FICO and ask politely if their computer will talk to your loan officer. It may well be able to process his otherwise useless experience into an even better FICO score. (You’ve guessed right, it does not say this in the book, that’s me extrapolating, sorry)
Next let’s look at the machines themselves. In the words of ZZ Top, they come in two classes: First, the kind that we program with some sensible ideas we have (example “adjectives in English absolutely have to be in this order: opinion-size-age-shape-color-origin-material-purpose-Noun” p.70) and then have the machine implement much faster than we ever could. Second, the kind that don’t need us at all and look at reams of data and come back with some answer and we just tell them how well they guessed. (That’s called “supervised learning” for those in the back who are not paying attention)
The first kind has been beating idiots like me at chess since I can remember. The second kind (steered, but not quite, by a fellow Greek, let’s hear it for Demis!) did something much more awesome the other day, it beat the world champion in Go, which is apparently much harder because there are fewer atoms in the known universe (and any undiscovered parallel universes) than there are ways to lay your pieces on a Go board. Maybe. Approximately. Where’s Val Kilmer when I need him?
The second kind of machine does not know what it knows or how it learned it, it embodies the Polanyi paradox. What’s new and amazing, basically, is a machine that, like me, could not tell you why it played the move, but very much unlike me, plays the correct move! All from having played many many many more times than I ever have, mostly with itself. (no, honestly, that’s what it does) And it’s finally possible today thanks to (i) Moore’s Law (ii) Amazon Web Services and (iii) the availability of “big data” to train itself on.
The future is in machines that don’t know what they know, just like us, basically. Instead of asking for the “Highest Paid Person’s Opinion,” also known as the HiPPO, ask this machine. It may not know what a liver transplant is, but if it thinks you need one, stop reading and call Alvin Roth now. (Kidney, liver, it’s all the same, don’t heckle! Instead, pray that it’s as well trained in recommending rare medical procedures as Demis’ Deep Mind is at playing Go with itself. I’m sure it will be fine. Better than the highest paid doctor’s opinion, you can be sure of that.)
The final frontier is that machines are starting to do creative work. Exactly how they play Go without knowing why they played the move, merely that it will probably work, they can design a radiator that looks like no radiator you’ve seen before, rig up a very effective chassis for your racing car, or compose a piece of music that you are likely to enjoy. Amazingly, after all the mumbo jumbo of the first 100 pages in the book, I actually found this (fifth!) chapter to be totally fascinating and convincing.
From “Machine” the book moves on to “Platform,” which actually is a tremendous section. (There are two authors at work here, basically, and this is the one I prefer)
The authors start by explaining that Apple makes 110% of all money made in phones today because 1. it controls the “platform” for all the apps and 2. nobody is counting the money Google is making off of Android. Jokes aside, they make the very strong point that making devices comes down to competing on costs, whereas establishing a platform allows you to reap the positive externalities generated by every single new participant in your platform. The virtuous circle works like this:
• every app that runs on an iPhone creates demand for the iPhone itself
• if many people own an iPhone, this creates a bigger supply of good apps
So 700 dollars is a lot of money for a telephone, but not if it can run 700 apps you’d pay a dollar each for, and things work out such that it will. And Apple no longer has to find its competitive edge in squeezing down the costs of making its beautiful devices.
Next come up the “two-sided” platforms, which are all the craze. I do not remember my days of starting book2eat.com that fondly (a good 40 VC’s were aghast at the fact that I was trying to sign up both restaurants and punters at the same time, and another 200 never answered my calls or emails) but the point is that if you manage to fill more seats the word gets out and you sign up more restaurants and if you’ve signed up more restaurants punters are likelier to make a booking on your platform and this creates a dynamic that becomes irresistible. So much so, that for example a company called ClassPass (that filled exercise studios with punters who were happy to be told at the last minute where to take their yoga mat to) had to revise its pricing policy (p. 178) due to the unmitigated success of the business model in filling exercise classes!
Next up is an analysis of Uber. Here I finally understood something that had always been a mystery to me: Uber’s obsession with low price is so huge because that’s where the demand curve is most elastic: All the way to the right, the demand curve is almost horizontal. People switch over from the train to Uber at some point, basically, and then all your cabs are full all of the time. The chart is on p. 213 and I totally buy it. Congestion in that city would be awful, but that’s down to the choice of the taxi example, of course. The point about why double-sided platforms love a low price is very well made.
The way ratings have solved the asymmetric information problem is discussed here too, with the inevitable name-dropping of the authors’ colleague down the hall who got the Nobel Prize for first posing it. Oh, and don’t worry, Airbnb will not kill the hotels industry, because hotels cater to business travelers. Don’t forget, it’s all good! The fate of the cabbies and the longshoremen is left to the reader to ponder, but they can all go work for Travis, no?
The third, final, section of the book is about “the crowd”
It starts by explaining that crowdsourced software rocks, basically, and that the ingredients you need are:
1. Openness: who knows what motivates them, but people do contribute
2. Noncredentialism: good software can be written by absolutely anyone
3. Verifiable and reversible contributions: unlike a novel, you can test software quickly and undo any poor contributions
4. Clear outcomes: via a good license you can assure coders that their work will remain public
5. Self-organization: people do best the work that they WANT to do and if that leads to a fork in the code, so be it
6. Geeky leadership: it’s the kind coders will write code for
Hayek and Polanyi make another guest appeareance in the chapter, but it works fine without them.
A further important point about the crowd is that very often the contribution to a project that makes the big difference does not come from an expert in the field. Indeed, the knowledge that will cut the Gordian knot may come from somebody with knowledge that is “far away” from the subject, i.e. somebody who will be surplus to requirements 99% of the time and thus a team of experts could never afford to have on board: “The expert you know is not the expert you need,” basically. He’s somewhere in the crowd and that’s where you must reach for him.
From there we jump to a painfully banal chapter on Bitcoin that addresses the points about cryptocurrency I could not care less about (like the mechanics of how it works, described just inaccurately enough for you not to be able to actually work it out, or the effete generalization that blockchain may be more important than Bitcoin,) barely gets into the aspects that matter (is it money? How does it provide store of value if there can be a million different otherwise scarce and deflationary varieties of Bitcoin? How will it compete if nobody will accept to be paid tax in it?) and complains that the Chinese are now dominating it.
By that point, we find ourselves in a final chapter that’s nothing to do with Machine, Platform or Crowd, but is there to make the customers feel good who are attending the seminar and assures them that companies will still carry on being necessary in the future, because they are who possesses “the residual rights to control: the right to make decisions not specified in contracts.”
Given that, presumably for the benefit of the same attendees, there is a need to sketch (very well, I must say, see pp 154-156) how the demand curve and the supply curve work and what happens when they intersect, one can safely say that this short paean to the firm is guaranteed to go over their head. But it must make for a warm conclusion. And now, back to work!
September 18, 2017
Uma continuação do The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, com desdobramentos sociais do mundo tecnológico moderno. Não me acrescentou tanto quanto o primeiro – que foi de longe um dos livros mais influentes que li – mas trouxe boas ideias. Ele é na verdade um bom apanhado de ideias que circulam em outros livros, mas resume todas elas bem, de forma que conta por uns 10 livros do gênero.
Tem um pouco sobre internet e plataformas dominando a mediação de transações, o que é discutido mais a fundo nos livros do Tim Wu. Tem um pouco sobre bitcoins e novas plataformas, como Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World e The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order explicam. Fala sobre algoritmos e como predições automáticas podem ser melhores que o julgamento humano, como Rise of the Robots: Technology and the Threat of a Jobless Future explica, ao mesmo tempo que levanta os pontos negativos de Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. E por aí vai.
Enfim, se quiser ler uma intro sobre novas tecnologias e como o mundo deve mudar pelos próximos 10 anos, é um livro bem legal.
Tem um pouco sobre internet e plataformas dominando a mediação de transações, o que é discutido mais a fundo nos livros do Tim Wu. Tem um pouco sobre bitcoins e novas plataformas, como Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World e The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order explicam. Fala sobre algoritmos e como predições automáticas podem ser melhores que o julgamento humano, como Rise of the Robots: Technology and the Threat of a Jobless Future explica, ao mesmo tempo que levanta os pontos negativos de Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. E por aí vai.
Enfim, se quiser ler uma intro sobre novas tecnologias e como o mundo deve mudar pelos próximos 10 anos, é um livro bem legal.
August 3, 2017
Неплохая книга, но много воды. Три основные мысли размазаны на 300+ страниц. Хорошая глава очень просто объясняющая, что такое блокчейн и умные контракты. И две последние ито��овые главы стоит прочитать.
Если выбирать, что читать про будущее, то лучше прочитайте The Inevitable.
Если выбирать, что читать про будущее, то лучше прочитайте The Inevitable.
September 6, 2017
I was disappointed with this.
The authors are well known professors/consultants who write a lot about current developments in technology and the workplace. They place current developments in the context of our prior understandings of industry, work, and technology and thus help their readers orient themselves to a fast changing technical environment. I also suspect that these sorts of works are helpful as reading materials for executive education classes and consulting assignments. This is clear from the summaries and discussion questions at the end of each chapter. I have no problem with any of this and this sort of intellectual gate keeping on really technical matters is very helpful.
This book is organized around three related streams of technical development - the proliferation of cheap and powerful computing, the development and prospering of network platform approaches to organizing technical firms, and the increasing importance of crowd-based approaches for obtaining tacit knowledge that is resident is some collective group or audience. So far, so good -- these are critical streams of development and lots of books and papers are written about each. For each of these three, McAfee and Brynjolfsson create a pairing with more traditional business arrangements. For smart computers, the pairing is with traditional views of simpler and more routinized machines and non-data driven tasks. Networked platforms are compared with traditional manufacturing and service strategies. Crowds are sources of critical information are compared with the traditional hierarchical expert-based structures of traditional firms. For each of these pairs, the authors then review current developments of interest and highlight the important issues that have arisen, especially over the last decade. The discussions are generally informative and well written. The materials that are referenced are current and on target. The discussions also highlight important case examples, especially if they have made the news. For example, Uber and AirBnb are featured as cases to show the growth of network platform businesses.
Why only three stars? To start with, I had seen many of the examples before and there was not much new in the presentations. Far too often, I wondered what the authors were bringing to the table in terms of new information or principles. There were some fairly informative discussions that I liked, especially in discussion of network strategies and how they worked for Uber. I also enjoyed the discussion of bitcoin and block chain issues. Several of the discussions fell flat.
For one example of this, early on the question is raised of expert systems outperforming expert human judges, raising the issue of whether AI systems will eventually take over in making decisions. The problem with the discussion is that these issues have been common for decades and yet the computer has not made much progress in taking over, except in well known specific situations. The discussion turns out to be rehash rather than a new look at the importance of high powered computers. Surprise! We still need human judgment. Big Data is not the total solution. The facts do not speak for themselves.
For another example, there is a discussion towards the end of whether organizations and firms have a future and whether new networked technology and crowd sourcing approaches will lead to a radical decentralization that obviates the need for organizations. Well, it turns out that there are more organizations than ever and more managers than ever. Evidently it is hard to do away with the incomplete contracting problem raised by transaction cost economists. ...but who ever suggested that firms and organizations would go away under the onslaught of technology? Nobody. Organizations have changed, big firms are more decentralized, and outsourcing is more common than it was 50 years ago - for reasons well considered by transaction cost researchers. Why the big discussion on this when the dynamics have been well known for a long time?
My biggest issue is that the book spends too much time disabusing readers about some troubling future trends that seem to be the result of overzealous hyping of technological changes - perhaps by the consultant and guru classes. Changes are happening and the resulting business environment is complex. Readers have to come to grips with this and think hard about it. It does not help to take the highly touted putative success of some start-ups (that have yet to show profits) and see the future as the realization of the hype. Real life is hard enough to analyze for these developments. Some of the marketing advocacy and promise of new worlds would have been better left in the box.
This book will be most valuable for people who need to get up to speed on these issues in a hurry. For more nuanced views, read the articles that are cited and dive a bit deeper into the details. It will be well worth it.
The authors are well known professors/consultants who write a lot about current developments in technology and the workplace. They place current developments in the context of our prior understandings of industry, work, and technology and thus help their readers orient themselves to a fast changing technical environment. I also suspect that these sorts of works are helpful as reading materials for executive education classes and consulting assignments. This is clear from the summaries and discussion questions at the end of each chapter. I have no problem with any of this and this sort of intellectual gate keeping on really technical matters is very helpful.
This book is organized around three related streams of technical development - the proliferation of cheap and powerful computing, the development and prospering of network platform approaches to organizing technical firms, and the increasing importance of crowd-based approaches for obtaining tacit knowledge that is resident is some collective group or audience. So far, so good -- these are critical streams of development and lots of books and papers are written about each. For each of these three, McAfee and Brynjolfsson create a pairing with more traditional business arrangements. For smart computers, the pairing is with traditional views of simpler and more routinized machines and non-data driven tasks. Networked platforms are compared with traditional manufacturing and service strategies. Crowds are sources of critical information are compared with the traditional hierarchical expert-based structures of traditional firms. For each of these pairs, the authors then review current developments of interest and highlight the important issues that have arisen, especially over the last decade. The discussions are generally informative and well written. The materials that are referenced are current and on target. The discussions also highlight important case examples, especially if they have made the news. For example, Uber and AirBnb are featured as cases to show the growth of network platform businesses.
Why only three stars? To start with, I had seen many of the examples before and there was not much new in the presentations. Far too often, I wondered what the authors were bringing to the table in terms of new information or principles. There were some fairly informative discussions that I liked, especially in discussion of network strategies and how they worked for Uber. I also enjoyed the discussion of bitcoin and block chain issues. Several of the discussions fell flat.
For one example of this, early on the question is raised of expert systems outperforming expert human judges, raising the issue of whether AI systems will eventually take over in making decisions. The problem with the discussion is that these issues have been common for decades and yet the computer has not made much progress in taking over, except in well known specific situations. The discussion turns out to be rehash rather than a new look at the importance of high powered computers. Surprise! We still need human judgment. Big Data is not the total solution. The facts do not speak for themselves.
For another example, there is a discussion towards the end of whether organizations and firms have a future and whether new networked technology and crowd sourcing approaches will lead to a radical decentralization that obviates the need for organizations. Well, it turns out that there are more organizations than ever and more managers than ever. Evidently it is hard to do away with the incomplete contracting problem raised by transaction cost economists. ...but who ever suggested that firms and organizations would go away under the onslaught of technology? Nobody. Organizations have changed, big firms are more decentralized, and outsourcing is more common than it was 50 years ago - for reasons well considered by transaction cost researchers. Why the big discussion on this when the dynamics have been well known for a long time?
My biggest issue is that the book spends too much time disabusing readers about some troubling future trends that seem to be the result of overzealous hyping of technological changes - perhaps by the consultant and guru classes. Changes are happening and the resulting business environment is complex. Readers have to come to grips with this and think hard about it. It does not help to take the highly touted putative success of some start-ups (that have yet to show profits) and see the future as the realization of the hype. Real life is hard enough to analyze for these developments. Some of the marketing advocacy and promise of new worlds would have been better left in the box.
This book will be most valuable for people who need to get up to speed on these issues in a hurry. For more nuanced views, read the articles that are cited and dive a bit deeper into the details. It will be well worth it.
September 19, 2017
I enjoyed it. I do not watch TV and do not read news so i only found out about this couture clothing and accessories renting platforms from this book. Clever. And some items are exposed to particular markets after they served their time in more advanced ones. And too bad the system of purchasing unlimited access to unused capacities of exercise facilities did not survive but I am sure eventually most optimal solution will be found. My own need is for a platform where i can order for a reasonable price a reasonable quality narration of a book not available on audio CD or audible... Other memorabilia from this book: order a car cleaning service exactly where the car is parked (service arrives to it); Uber asks drivers to take and submit selfies once in a while to make sure the car is still driven by the one who received the ratings (dealing with information asymmetries); make the problem generic enough (free of domain knowledge) and ask the crowd to try to optimize the algorithm (reducing the time to complete a task); possibilities that block chain technology (an un-alterable ledger) can bring... https://blockgeeks.com/guides/what-is..... Will follow the authors for sure.
October 1, 2017
This is an excellent book about our evolving reality thanks to technology. It's divided into 3 parts: Men vs Machine, Product vs Platform, and Core vs Crowd.
1. Men or machine? AI is already making better decisions in investment, medical diagnosis and a host of other scenarios. However, it suffers from Polanyi's Paradox, meaning that there is so much tacit knowledge, AI can't possibly consider them all because it does not know what to know. That's why predictive AI for presidential election can miss the mark. Also if John goes to football games every week, but broke his leg, a human will immediately know that he won't be going this week, but AI would not. Also AI is good at doing what it's supposed to do. It is inflexible. That's why Uber's surge pricing during terrorist attacks, though economically correct, caused so much public uproar. In the end surge pricing AI was shut down for that period.
2. Product or Platform? The power is clearly shifting to the Platforms like Google, Amazon, Facebook, Uber and Airbnb. However they cannot completely eradicate the traditional business. The authors give the example of Airbnb which is not suitable for the business traveller, who needs meeting room, easy meals etc. I must add that there is backlash against these. Google was fined by the EU, and London has just shut down Uber.
3. Core or Crowd? The crowd is getting smarter than core, with examples given as solving some genetic problems. Some platforms are now available to let anyone anywhere to bid for jobs. Bitcoin was developed to bypass central banks and government control of money. However the problem for Bitcoin is that China is now running the largest proportion of nodes and they will eventually have control over it. Decentralised work is unlikely to annihilate the firm, because of the problem of incomplete contract. That essentially says that all contracts (or algorithms) are imperfect and thus we still need the firm to solve unexpected problems.
I enjoyed this well researched book. The only thing is that I ended up skipping the repetitive chapter summary and 'study questions'.
1. Men or machine? AI is already making better decisions in investment, medical diagnosis and a host of other scenarios. However, it suffers from Polanyi's Paradox, meaning that there is so much tacit knowledge, AI can't possibly consider them all because it does not know what to know. That's why predictive AI for presidential election can miss the mark. Also if John goes to football games every week, but broke his leg, a human will immediately know that he won't be going this week, but AI would not. Also AI is good at doing what it's supposed to do. It is inflexible. That's why Uber's surge pricing during terrorist attacks, though economically correct, caused so much public uproar. In the end surge pricing AI was shut down for that period.
2. Product or Platform? The power is clearly shifting to the Platforms like Google, Amazon, Facebook, Uber and Airbnb. However they cannot completely eradicate the traditional business. The authors give the example of Airbnb which is not suitable for the business traveller, who needs meeting room, easy meals etc. I must add that there is backlash against these. Google was fined by the EU, and London has just shut down Uber.
3. Core or Crowd? The crowd is getting smarter than core, with examples given as solving some genetic problems. Some platforms are now available to let anyone anywhere to bid for jobs. Bitcoin was developed to bypass central banks and government control of money. However the problem for Bitcoin is that China is now running the largest proportion of nodes and they will eventually have control over it. Decentralised work is unlikely to annihilate the firm, because of the problem of incomplete contract. That essentially says that all contracts (or algorithms) are imperfect and thus we still need the firm to solve unexpected problems.
I enjoyed this well researched book. The only thing is that I ended up skipping the repetitive chapter summary and 'study questions'.
October 7, 2019
This book is a good run down of commercially disruptive technologies, at least those disruptive as of 2017. Things move so fast that one wonders how long this text will be useful but at the time of reading two years later it still acted as a decent primer.
McAfee and Brynjolfsson are not men to doubt the capitalist paradigm or free markets so they are well into the idea that creative destruction is one of those things we have to live with and that dinosaurs will die and adaptable creatures will thrive. Managers, of course, are set up to be heroes.
The book is divided into three parts matching the three starting nouns - machine, platform and crowd. Each part moves steadily and clearly into the more radical end of each model, with (for those who like that sort of thing) end chapter executive summaries and questions for troubled executives.
The 'Machine' covers the rise of machine learning and artificial intelligence and has some tough things to say about the value of human reason. In the end, humans are relegated to being the creatures who command the machines to meet their wants and needs according to their values.
Much of the administrative and professional class is going to be consigned to history, it would seem, leaving a management elite of those who make the value judgments and a working community of personal service providers and those who 'monkey around' (literally) the machines.
Even 'creativity' (so they suggest) will be devolved to machines. While humans are not to be made useless by any means (after all, this is for our benefit), work is going to mean something very different for us within a very few decades.
Needless to say, being market ideologues speaking unto managers and capitalists (or would-be capitalists), the authors have nothing to say on the wider social and cultural consequences of a world of machine-human interaction. One suspects they don't enormously care in this book.
The 'Platform' section is exceptionally useful in explaining, in clear terms and from the perspective of economics, one of the mysteries of the new economy to ordinary folk - precisely how it creates wealth or, rather, how it makes money (which may or may not be the same thing).
The consumer sees a lot of things provided for free - I pay for one newspaper subscription (reluctantly), use ad blockers and restrict streaming to Netflix, Amazon Prime and Spotify so how do I get so much information and entertainment elsewhere for nothing?
I found this valuable enough to know that I will hold on to the book (business books otherwise tend to get recycled out of my library faster than most categories) for quick reference when ever I have to deal with a start up in technology in order to double-check the viability of their business model.
It has to be said that, two years on, with the financial markets beginning to get cold feet about pouring money into platforms like WeWork, one gets the sense that what works on paper may not quite work as the authors expect as projects come up against real world difficulties.
The book is, however, wise to see platforms as disruptive but not exclusive and that 'traditional' businesses (such as hotels in relation to, say, Airbnb) still have many opportunities for adaptation whether into niches or into global segmentation for particular markets.
In the final section ['Crowd'], the authors draw a distinction between the crowd (enabled by the internet) and the core (the traditional hierarchical management centre). This section is largely about corporate organisation and decentralisation.
This reminds me of the last book we reviewed - Niall Ferguson's 'The Square and the Tower' - which explored how networks and hierarchies had played off each other to transform society and culture in history. The crowd/core story is a variant of that tale.
There is an element of 'wisdom of crowds' in this although we are personally suspicious of the long term value of this concept. Lemmings are a crowd and human confabulation and cognitive biases (which make machines more useful than us) can create herd absurdities.
To be fair, the authors are thoroughly sensible on the limits of decentralisation. This makes them very cautious about some of the more outre libertarian economic models. Recent history is tending to prove them right. There is a necessity for some core functions.
Which brings us neatly into the world of bitcoin and blockchain where the authors are still cautious boosters although the last two years has tended to show that these technologies have a long way to go yet before they are truly transformative instead of magic money pits.
The book closes with a question about whether the new technologies will eventually kill off the corporate sector to replace the firm with, say, the collective or the peer-to-peer network or some other form of decentralised organisation and it will be no surprise to hear that they do not think so.
This final and shortest section is worth reading because it is very well argued and plausible within a classic (American) capitalist framework, based on a very articulate exposition of the theory of 'transaction cost economics' and the problem of 'incomplete contracting'.
'Incomplete contracting' (the inability of contracts to cover every eventuality) acts as a check on the 'smart contract' being a total solution for global commerce as opposed to a (possible) solution to particular categories of repeatable contract.
The authors may contradict themselves here insofar as their 'Machine' section implies that AI will be able to make such managerial judgements but we'll let that pass on the basis that they also say there are natural limits to AI comprehension of real world human interactions.
Of course all this depends on a particular concept of property rights but the authors' complacency is certainly justified so long as the American Constitution remains honoured. Even the Corbynista socialists will have trouble unravelling the British bedrock of protective common and statute law.
At the very end, the book is a booster for 'good' managers who are (as all such books tend to do) 'heroised' as the new breed of socially skilled (aka manipulative, let us dare not say sociopathic) directors of persons in a common cause (making more money for people with money).
Taken as a whole, this is an excellent and fair (and not over-enthusiastic) guidebook to the new commercial reality. If it does not deal with social or cultural consequences and is managerialist to the core, it strikes me as well grounded in its economics.
If I have doubts, it is not about the book (which I recommend) but about where the ideology behind the book is leading us - or rather where it thinks it is leading us only to find that humans are remarkably stubborn about not being led except by their own desire, greed and fear.
It is not the 'little things', like the energy consumption of blockchain in an age of middle class neurosis about climate change, that suggest black swans ahead but the slow collapse of people's willingness to take expert or managerial guidance for granted.
I detect a much more volatile humanity, quite capable of switching out of a product or platform and into a new one at surprising speed, machines discredited quickly by single failures (as in the Ethiopian Airlines crash) and social and political resistance to unmanaged effects.
There are signs of techno-hubris. Too many energetic 'geniuses' chasing too many advanced projects. Too little interest in those awkward social and cultural effects and in the psychology of nervous politicians. Too much creative destruction for the market to bear.
Corporate managers manage the delivery of things but not the effects of things so the management of the latter is left to States with increasing problems of administrative capacity and volatile democratic politics. What could go wrong?
The simple business of lobbying for advantage is no longer simple and done behind closed doors. The old 'socialism for corporations' is being exposed to public gaze in the West and managers may well look to 'Chinese' guided democracy as preferable to chaos but not be able to wangle it.
I detect that the manipulations involved in marketing, PR and human resources have created a race of managers who believe their own lies - that they are needed and loved far more than they are - like aristocrats in 1788 who would swear that their peasants adored them.
Just when managers most need the skills outlined so well by McAfee and Brynjolfsson at the end of the book, the crowd communications on platforms may be educating - 'raising the awareness of' - workers and public that those skills may be manipulative and manufactured and so to be resisted.
It may even be that, if we think of the original of socialism as being an ideology of freedom that was actually about bread, shelter and medicine, we are moving towards a variant ideology of needs and wants that is actually about freedom and that freedom is, in fact, resistance to managerialism.
I would be fascinated to see a dissident reverse engineer this text and take it out of the zone of managers meeting needs and wants through the corporate organisation of markets and into a new zone of demands that use the technologies to contain and control managers and administrators.
In fact, as always, my guess is that the coming decades will see an uneasy compromise of networks and hierarchies. The technologies will raise social and other problems. Managers will be run ragged by the complexity of it all. Populations will never quite be clear about what they want.
It is probable that even the mighty FANGS could be brought down to earth and new forms of enterprise emerge and at ever faster speeds. The regulators will be fighting wars on two fronts. Voters will alternate between rage and apathy and it will never be clear which is uppermost.
Above all, survival requires something more than understanding how to manage human beings in an age of machines. It also requires an understanding of actual rather than believed power relations - a recognition of powerlessness or manipulation or exploitation is the very trigger for revolt.
Still, if you are a manager struggling with this new and unstable world, then this book is not a bad basic primer so long as you remember that the theory may not always accord with the brute reality as it unfolds in the future.
July 14, 2017
I see this book more as a revision to "The Second Machine Age" by the same authors. Though the main difference is that in that book, the authors differentiate the societal impacts of the Industrial Revolution from the Second Machine Age. However, in this book, they dive deep into the current Information and Communication Technologies (ICT) revolution and categorize the various rapid, seemingly random innovations under three buckets or re-balancings -- Man and Machine, Products and Platforms and finally Core and Crowd. The authors have excelled in convincing the readers (at least me) about the categorization and they also provide some advice on how individuals and organizations can balance between the three pairs.
A timely book. The best time to read this is now :)
A timely book. The best time to read this is now :)
August 26, 2017
Machine, Platform, Crowd is more like a "vision" from a "Guru" - heavy with fancy terms, apparently innovative and "true" new perspectives or frameworks, full of examples from the life around and with the messages created for effect. There was an era when such schemas created runaway bestsellers, led to hit management or executive courses and provided another tool to the busy business consultants. The utility is far less, and for a far shorter period, now except perhaps for the technologically-archaic people that are unable to understand new forces being unleashed by AI, cloud, mobile, big data, social networking, etc.
The three big forces that the book claims to have found are neither new nor really unified, real forces. Let's think about what the author tries to mean with each one of them. The first section builds on the indisputable claim that "machines" are becoming more intelligent and will do more and more with the passage of time. Isn't this going on for centuries? The pace will massively intensify with AI, but the broad "machine" term conjured up by the author for this section serves only one useful purpose in the context of the book: it helps drive home the point that humans will be better at doing extremely small list of things from here on. The author resolutely steers away from possibly the only important implications from this "force": the impact on jobs and other social/societal/political forces.
"Platform" is far vaguer than "machine". It is supposed to stand for something that contrasts "processes" - the author's contrasts have to start from the same alphabets! Last decade, and coming few years, are the pinnacle of technology exploits from new levels of connectivity. However, the use of the word "platform" to signify this completely misses the bigger picture. The world of innovation does not end with Uber and the likes. The decades ahead will have bigger changes affected by solar power, genetics, nano technology, big data etc. "Platforms" as used here, are a phase, an important phase. It is actually neither anti-process nor anti-capital or anti-material. For us to do better, sciences needed to make more out of not only material and processes but also connectivity and information processing. Is this really a force called "platform"?
"Crowd" is the weakest of all. With connectivity, we have more innovative ways of coming together for specific activities like funding, writing a program, creating Wikipeadia or even sparking political agitations. This is not only old but frankly not as rapidly evolving as the first two despite the recent progresses of concepts like crowd funding and social networking.
The author uses numerous interesting examples and concepts to make his points. However, the main framework is theoretically unsound and practically without much utility.
The three big forces that the book claims to have found are neither new nor really unified, real forces. Let's think about what the author tries to mean with each one of them. The first section builds on the indisputable claim that "machines" are becoming more intelligent and will do more and more with the passage of time. Isn't this going on for centuries? The pace will massively intensify with AI, but the broad "machine" term conjured up by the author for this section serves only one useful purpose in the context of the book: it helps drive home the point that humans will be better at doing extremely small list of things from here on. The author resolutely steers away from possibly the only important implications from this "force": the impact on jobs and other social/societal/political forces.
"Platform" is far vaguer than "machine". It is supposed to stand for something that contrasts "processes" - the author's contrasts have to start from the same alphabets! Last decade, and coming few years, are the pinnacle of technology exploits from new levels of connectivity. However, the use of the word "platform" to signify this completely misses the bigger picture. The world of innovation does not end with Uber and the likes. The decades ahead will have bigger changes affected by solar power, genetics, nano technology, big data etc. "Platforms" as used here, are a phase, an important phase. It is actually neither anti-process nor anti-capital or anti-material. For us to do better, sciences needed to make more out of not only material and processes but also connectivity and information processing. Is this really a force called "platform"?
"Crowd" is the weakest of all. With connectivity, we have more innovative ways of coming together for specific activities like funding, writing a program, creating Wikipeadia or even sparking political agitations. This is not only old but frankly not as rapidly evolving as the first two despite the recent progresses of concepts like crowd funding and social networking.
The author uses numerous interesting examples and concepts to make his points. However, the main framework is theoretically unsound and practically without much utility.
January 12, 2019
A Platform of Platforms: The Internet
Machine, Platform, Crowd is an application level guide to implementing available technology into the business place. It seems geared towards workplace staff development for companies, with questions at the end of each chapter that could be discussed in a team read of the book. It is the type of book employees often read to further their own personal development, as well. It is not a work of great vision for the future, or cutting edge tech info, or business theory to any degree. All of the ideas contained within are dated 5-15 years from before the publication date. But, to be clear, this is intended to spark ideas for existing programs. And, it is intended to be a guide to thinking and practice in the work world.
To give some comparison, Michio Kaku writes about future tech and new ideas in the world of business tech. His ideas are often theory level and show great genius and vision. They are ideas the average person would not come up with just by surveying the available literature. Vision is like creativity. The authors here point out an idea from ai pioneer Marvin Minsky. He says that some words that describe processes in our mind our suitcase-like jungles of different ideas. Creativity is such a word. Creativity is specifically thought of as the use of imagination or original ideas especially in the production of new works. But, the actual denotation is simply the ability to make new things or think of new ideas. The average employee and manager pair in the work world are like the stage coach owners and drivers. They are not adept at thinking of how to invent railroads. They are finding a decent amount of success at their current business plan. This is why many business models fall to the wayside when some new tech comes to the foreground. Where Michio Kaku type writers are looking for alternative ideas outside the box that could in possibility be developed; books like this one provide ideas from inside the box to augment your current tools of the trade.
At the core of this book is the question, "Is your business a 'Second Machine Age Company?'" This idea is an expansion on their earlier book of that title. I have not read that book, so I have no idea whether it is practice or theory. But, judging from the dates of publication, and the dates of ideas used in this book, it sounds like this is just a more down-to-earth application of the same principles from that book. I would expect that it is more of a synthesis of the available ideas, while this involves a lower application level of thinking. It gives suggestions for encouraging the acquisition of new ideas in your work. But, everything contained here can be gained from reading, watching the news, or even playing video games, which deals quite a bit with robotics and technology.
What's more, all of these ideas are already being used to great success all over the business world. I know Honda uses robotics throughout the manufacturing process, and has for years, for one example. Asimo, their robot, was first created in 2000 I believe. So, this is not cutting edge stuff here. Not only could your 15 year old research and compile this info, but your 9 year old would not even need to do the research. And, that draws me to the crux of everything in this book. If you are not using young people, or as the authors term tech savvy people, "geeky workers" as leaders and decision makers; then your organization, business, or group will still be making stage coaches while the customers are on the train platform. It is great to have leaders with mature judgment, and good leadership qualities, as well as great communicators. But, don't leave out the younger and/or tech savvy generation in your leadership.
The book is set up on the plan of: Mind+Machine, Products+Platform, Core+Crowd. In the past, business as usual meant having a product, and using your mind to develop that product with the backing of a core of important leaders. In this second machine age of today there is often no visible product. Instead, the product is a digitized or mechanized bit of data... the machine. And, instead of just relying on a core of people, many companies are reaching out to the crowd for backers and input. A good example of this from the book is that of David Bowie and his 'Bowie Bonds.' He sold bonds to raise money for an album. This idea came and went very fast, but he was using creative funding techniques. Another example is that of game developers who now often use crowd funding to kickstart their games. During the development process, they reach out to the crowd funders for ideas on what they want to see in that game. It places much of the locus of control outside the core, but it makes a much more marketable product.
There are times when the crowd may not be the best source of inspiration. Take the unique situation of churches for example. The leadership of a church is often guided by ideas that are limited to a certain framework of their interpretation of Scripture. Reaching out to the crowd would result in di-vision instead of vision... or multiple plans, many counterintuitive to the overarching goal. Businesses have to keep this in mind as well. Ultimately, the game designer in my earlier example will lose some of his own ideas in that finished product by virtue of having accepted crowd input. Does this matter? That is a highly personal question, and has caused the split up of many companies. Sometimes, a company is intending heading in a certain direction, while one element wants to move in a different direction. When this happens, people often split and form individual companies. So, I am saying that in all this thinking outside the box, you ultimately have to ask yourself why you were inside the box in the first place. Is the box a guide, or is it keeping you from moving forward?
Throughout the book, many ideas and specific examples of technology are described: from Chess and Go playing Artificial Intelligences, to War Games style 'taking humans out of the loop,' to self-driving cars, to crypto-currencies. The authors point out the preferability of favoring the crowd over the core for many internet users of Bit Coins. They describe how the intention was for the currency to be uncontrollable by any one society, but with over half of the currency being owned within China, it loses some of that freedom of crowd ownership. They point to what Science Fiction writer Bruce Sterling said in 2012. He said that it makes no sense to talk about: Internet, PC business, telephones, silicone valley, or the media. It makes more sense to study Google, Apple, Facebook, Amazon, and Microsoft. He was talking about what happens when we favor the core over the crowd. He called them 'stacks' because there is a great concentration of power there in these companies. We used to refer to 'Trust Busters' and monopolies. But today, monopoly is becoming an irrelevant term.
When you put it all together, the internet itself is the ultimate model of this idea of machine, platform, crowd. The internet is the machine, the platform, and the crowd all three in one. And, many businesses today have succeeded by going O2O, or Online to Offline and bringing 'bits to the world of atoms.' Uber is a prime example of this. I enjoyed reading the book, and think it is a good look at what is happening around us, or rather what has happened in an already being fulfilled kind of way. The only thing new I learned here was of the existence of Airbnb. That is definitely an interesting service that utilizes several concepts that have been in practice for decades. The developer of Airbnb is certainly using the machine, platform, crowd design idea of the internet to make money. I enjoyed this in the Audible format, which was narrated well by Jeff Cummings.
Machine, Platform, Crowd is an application level guide to implementing available technology into the business place. It seems geared towards workplace staff development for companies, with questions at the end of each chapter that could be discussed in a team read of the book. It is the type of book employees often read to further their own personal development, as well. It is not a work of great vision for the future, or cutting edge tech info, or business theory to any degree. All of the ideas contained within are dated 5-15 years from before the publication date. But, to be clear, this is intended to spark ideas for existing programs. And, it is intended to be a guide to thinking and practice in the work world.
"In general it is not the owner of stage coaches who invent railways."
To give some comparison, Michio Kaku writes about future tech and new ideas in the world of business tech. His ideas are often theory level and show great genius and vision. They are ideas the average person would not come up with just by surveying the available literature. Vision is like creativity. The authors here point out an idea from ai pioneer Marvin Minsky. He says that some words that describe processes in our mind our suitcase-like jungles of different ideas. Creativity is such a word. Creativity is specifically thought of as the use of imagination or original ideas especially in the production of new works. But, the actual denotation is simply the ability to make new things or think of new ideas. The average employee and manager pair in the work world are like the stage coach owners and drivers. They are not adept at thinking of how to invent railroads. They are finding a decent amount of success at their current business plan. This is why many business models fall to the wayside when some new tech comes to the foreground. Where Michio Kaku type writers are looking for alternative ideas outside the box that could in possibility be developed; books like this one provide ideas from inside the box to augment your current tools of the trade.
"Machines can do better"- Human minds: brilliant but buggy."
At the core of this book is the question, "Is your business a 'Second Machine Age Company?'" This idea is an expansion on their earlier book of that title. I have not read that book, so I have no idea whether it is practice or theory. But, judging from the dates of publication, and the dates of ideas used in this book, it sounds like this is just a more down-to-earth application of the same principles from that book. I would expect that it is more of a synthesis of the available ideas, while this involves a lower application level of thinking. It gives suggestions for encouraging the acquisition of new ideas in your work. But, everything contained here can be gained from reading, watching the news, or even playing video games, which deals quite a bit with robotics and technology.
What's more, all of these ideas are already being used to great success all over the business world. I know Honda uses robotics throughout the manufacturing process, and has for years, for one example. Asimo, their robot, was first created in 2000 I believe. So, this is not cutting edge stuff here. Not only could your 15 year old research and compile this info, but your 9 year old would not even need to do the research. And, that draws me to the crux of everything in this book. If you are not using young people, or as the authors term tech savvy people, "geeky workers" as leaders and decision makers; then your organization, business, or group will still be making stage coaches while the customers are on the train platform. It is great to have leaders with mature judgment, and good leadership qualities, as well as great communicators. But, don't leave out the younger and/or tech savvy generation in your leadership.
"The company of the future will have just two employees: A human and a dog. The human's job will be to feed the dog. And, the dog's job will be to keep the human from touching any of the machines." -joke anecdote from the book
The book is set up on the plan of: Mind+Machine, Products+Platform, Core+Crowd. In the past, business as usual meant having a product, and using your mind to develop that product with the backing of a core of important leaders. In this second machine age of today there is often no visible product. Instead, the product is a digitized or mechanized bit of data... the machine. And, instead of just relying on a core of people, many companies are reaching out to the crowd for backers and input. A good example of this from the book is that of David Bowie and his 'Bowie Bonds.' He sold bonds to raise money for an album. This idea came and went very fast, but he was using creative funding techniques. Another example is that of game developers who now often use crowd funding to kickstart their games. During the development process, they reach out to the crowd funders for ideas on what they want to see in that game. It places much of the locus of control outside the core, but it makes a much more marketable product.
"The best way to predict the future is to invent it."
There are times when the crowd may not be the best source of inspiration. Take the unique situation of churches for example. The leadership of a church is often guided by ideas that are limited to a certain framework of their interpretation of Scripture. Reaching out to the crowd would result in di-vision instead of vision... or multiple plans, many counterintuitive to the overarching goal. Businesses have to keep this in mind as well. Ultimately, the game designer in my earlier example will lose some of his own ideas in that finished product by virtue of having accepted crowd input. Does this matter? That is a highly personal question, and has caused the split up of many companies. Sometimes, a company is intending heading in a certain direction, while one element wants to move in a different direction. When this happens, people often split and form individual companies. So, I am saying that in all this thinking outside the box, you ultimately have to ask yourself why you were inside the box in the first place. Is the box a guide, or is it keeping you from moving forward?
“Uber, the world’s largest taxi company, owns no vehicles,” he wrote. “Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. And Airbnb, the world’s largest accommodation provider, owns no real estate. Similarly, many of the largest hotel companies don’t actually own all the properties that bear their names, opting instead to sign licensing or management agreements with real estate holders. Similarly, many of the largest hotel companies don’t actually own all the properties that bear their names, opting instead to sign licensing or management agreements with real estate holders."
Throughout the book, many ideas and specific examples of technology are described: from Chess and Go playing Artificial Intelligences, to War Games style 'taking humans out of the loop,' to self-driving cars, to crypto-currencies. The authors point out the preferability of favoring the crowd over the core for many internet users of Bit Coins. They describe how the intention was for the currency to be uncontrollable by any one society, but with over half of the currency being owned within China, it loses some of that freedom of crowd ownership. They point to what Science Fiction writer Bruce Sterling said in 2012. He said that it makes no sense to talk about: Internet, PC business, telephones, silicone valley, or the media. It makes more sense to study Google, Apple, Facebook, Amazon, and Microsoft. He was talking about what happens when we favor the core over the crowd. He called them 'stacks' because there is a great concentration of power there in these companies. We used to refer to 'Trust Busters' and monopolies. But today, monopoly is becoming an irrelevant term.
"Alibaba, founded in 1999 by former schoolteacher Jack Ma and seventeen colleagues, acted as an online middleman connecting buyers and sellers. Its most popular sites were the Taobao Marketplace, where individuals and small businesses sold goods to consumers, and Tmall, where larger companies did the same. By the end of 2016, the number of Chinese people using Alibaba’s apps every month was greater than the entire US population."
When you put it all together, the internet itself is the ultimate model of this idea of machine, platform, crowd. The internet is the machine, the platform, and the crowd all three in one. And, many businesses today have succeeded by going O2O, or Online to Offline and bringing 'bits to the world of atoms.' Uber is a prime example of this. I enjoyed reading the book, and think it is a good look at what is happening around us, or rather what has happened in an already being fulfilled kind of way. The only thing new I learned here was of the existence of Airbnb. That is definitely an interesting service that utilizes several concepts that have been in practice for decades. The developer of Airbnb is certainly using the machine, platform, crowd design idea of the internet to make money. I enjoyed this in the Audible format, which was narrated well by Jeff Cummings.
February 15, 2018
Terminei esse livro na sequência do The Second Machine Age. Que é um livro excelente, já comentei aqui no GoodReads. Este livro, publicado em 2017, torna disponível uma visão de tecnologia dificilima de alcançar por conta própria, leva um tempão de leituras e conversas e escritos, para chegar a essa visão. Mostra as relações entre o ser humano e a máquina, entre a sociedade e a tecnologia, e dá o caminho do que está vindo por ai. Mas em bases sólidas, com dados consistentes e bem fundamentados como é o The Second Machine Age. Lança caminhos para a investigação e para o lançamento de negócios inovadores. A complementação entre o ser humano e a máquina deve ser o padrão da relação homem-máquina atual e no futuro, vendo as máquinas (virtuais ou não) como próteses do ser humano, ajudando nas decisões e solução de problemas complexos que hoje não temos competência nem capacidade para resolver, com o nosso limitado hardware humano para alguns tipos de problemas. Engana-se quem tem a visão simplista de que esse livro é continuação do The Second Machine Age, não é. O foco é outro, embora também seja voltado para tecnologia e desenvolvimento tecnológico. Digo mais, a leitura é desafiante e não é fácil entender tudo o que está no livro, exige conhecimento vasto, notadamente em computação e economia. Imperdível.
September 12, 2019
I have the good Fortune of thinking about the future and the implications of technology professionally. Frankly, at this stage of my life, these thoughts are woven into my DNA and all consuming. My only escape is a good (non-tech) book.
So, if you're a curious nerd this (and everything written by the authors) is a must read, ponder, and apply.
So, if you're a curious nerd this (and everything written by the authors) is a must read, ponder, and apply.
January 17, 2018
This is a business book and I will examine it as such. There are three parts:
1) Machine (developments in artificial intelligence and its impacts to companies in the past and present with comparisons to the start of electric era and adoption of computers and internet in 90s)
2) Platform (how the so-called platform economics of Facebook, Uber, Airbnb came to be and who and how have benefited and who have not)
3) Crowd (Examples of Linux, Wikipedia and other decentralized networks that have been successful and some that have bee not. The most prominent example would be DAO - an Etherum blockchain based "decentralized autonomous organization" which turned out to fail. Blockchain is still a mixed blessing in general but it seems to be the same kind of transitional problem that was with previous technological changes. To answer "So, what do we do with this new thing?" usually takes a little time both by companies (managers and employees) and costumers. Diversion at the end to Transaction Cost Economics and why companies still exist and will probably continue to exist was also very interesting (another variation of "we can't know the future").
Disclaimer: I am neither an economist or in business so certain things that I found interesting and valuable may not be so for others. I see this book in the larger realization by economists and pundits that automation and the ever-increasing capabilities of different forms of AI are not the only thing happening in the economy due to technological changes. The other trends are also fascinating and they are worth pondering about.
There will be an acronym from the book that I will probably keep using for some time DANCE: Data, Algorithms, Networks, Cloud, Exponentially improving hardware. Its a nice mnemonic to keep in mind although the word "Exponential" has pitfalls (usually actual trends are S-shaped and stall at some point or when looked closely have some other mathematical term behind them).
In general I found the content in general unevenly interesting and had to force myself to read at times. On the other hand there was a certain kind of humility "we are not entirely sure what the future will bring" and to make the reader ponder as well on such questions there are actual questions at the end of each chapter which are usually a variant of "how do you implement/have you considered the impact of technology X in your organisation?" Before the questions is a short bulletpointed summary of the main ideas of each chapter so the content can be gleamed from there as well.
1) Machine (developments in artificial intelligence and its impacts to companies in the past and present with comparisons to the start of electric era and adoption of computers and internet in 90s)
2) Platform (how the so-called platform economics of Facebook, Uber, Airbnb came to be and who and how have benefited and who have not)
3) Crowd (Examples of Linux, Wikipedia and other decentralized networks that have been successful and some that have bee not. The most prominent example would be DAO - an Etherum blockchain based "decentralized autonomous organization" which turned out to fail. Blockchain is still a mixed blessing in general but it seems to be the same kind of transitional problem that was with previous technological changes. To answer "So, what do we do with this new thing?" usually takes a little time both by companies (managers and employees) and costumers. Diversion at the end to Transaction Cost Economics and why companies still exist and will probably continue to exist was also very interesting (another variation of "we can't know the future").
Disclaimer: I am neither an economist or in business so certain things that I found interesting and valuable may not be so for others. I see this book in the larger realization by economists and pundits that automation and the ever-increasing capabilities of different forms of AI are not the only thing happening in the economy due to technological changes. The other trends are also fascinating and they are worth pondering about.
There will be an acronym from the book that I will probably keep using for some time DANCE: Data, Algorithms, Networks, Cloud, Exponentially improving hardware. Its a nice mnemonic to keep in mind although the word "Exponential" has pitfalls (usually actual trends are S-shaped and stall at some point or when looked closely have some other mathematical term behind them).
In general I found the content in general unevenly interesting and had to force myself to read at times. On the other hand there was a certain kind of humility "we are not entirely sure what the future will bring" and to make the reader ponder as well on such questions there are actual questions at the end of each chapter which are usually a variant of "how do you implement/have you considered the impact of technology X in your organisation?" Before the questions is a short bulletpointed summary of the main ideas of each chapter so the content can be gleamed from there as well.
March 13, 2018
Very well written summary of research and expert opinion on the changing nature of economics and business. Highly recommended to both researchers and the layperson.
The book is divided into three sections based on the themes in the title. The most interesting are the sections on robots and platforms. The section on crowds seems comparitively less important, and is much more thin on material.
In the machine section, three big insights stick with me.
1) Robot decision makers often outperform humans. Use more of it when the task has clear inputs, outputs, and decision criteria. Human intuition can be used as an input to decision making, or override it as a 'sanity checker', but shouldn't be elevated above it in routine situations.
2) Many jobs have some component which is automatable. The challenge moving forward will not be what jobs will be automated, but how to change jobs so that the automatable part can be sliced off.
3) New advances in machine vision have the potential to launch a Cambrian Explosion in the variety of tasks robots can do.
When I spoke to Erik recently, he said of Marshall Van Alstyne: "He's a great researcher, but he thinks platforms are everything." To this I responded, "Yep, that's incorrect, according to your book, they're 1/3 of things."
The novel touches lots of familiar ground in the platform section. The parts I found most novel were in thinking about how digital platforms differ from digital-to-physical platforms in dealing with the newspaper vendor problem. There was also some very sketched remarks about when, as an established brand, to join on with a platform (vs. insisting on working independently). Both of these lines of reasoning seem like productive research directions.
The final section, on crowdsourcing, seems much less important. To me at least, Kickstarter (and its brethren) seems like it will continue to be a niche method of financing projects. Meanwhile, the rest of the section, is mainly a list of types of tasks that can be crowdourced. None of this seemed particularly revolutionary. In a Coasian sense, its just some additional activities being outsourced, because negotiation/communication costs have been lowered for outside temp workers.
As far as I can understand, the main objection to this book is that it recycles a lot of material that had been used in previous works by the authors. Although I have read some of that, I have not read Second Machine Age. So I do not know how much of this is a repeat of that.
The book is divided into three sections based on the themes in the title. The most interesting are the sections on robots and platforms. The section on crowds seems comparitively less important, and is much more thin on material.
In the machine section, three big insights stick with me.
1) Robot decision makers often outperform humans. Use more of it when the task has clear inputs, outputs, and decision criteria. Human intuition can be used as an input to decision making, or override it as a 'sanity checker', but shouldn't be elevated above it in routine situations.
2) Many jobs have some component which is automatable. The challenge moving forward will not be what jobs will be automated, but how to change jobs so that the automatable part can be sliced off.
3) New advances in machine vision have the potential to launch a Cambrian Explosion in the variety of tasks robots can do.
When I spoke to Erik recently, he said of Marshall Van Alstyne: "He's a great researcher, but he thinks platforms are everything." To this I responded, "Yep, that's incorrect, according to your book, they're 1/3 of things."
The novel touches lots of familiar ground in the platform section. The parts I found most novel were in thinking about how digital platforms differ from digital-to-physical platforms in dealing with the newspaper vendor problem. There was also some very sketched remarks about when, as an established brand, to join on with a platform (vs. insisting on working independently). Both of these lines of reasoning seem like productive research directions.
The final section, on crowdsourcing, seems much less important. To me at least, Kickstarter (and its brethren) seems like it will continue to be a niche method of financing projects. Meanwhile, the rest of the section, is mainly a list of types of tasks that can be crowdourced. None of this seemed particularly revolutionary. In a Coasian sense, its just some additional activities being outsourced, because negotiation/communication costs have been lowered for outside temp workers.
As far as I can understand, the main objection to this book is that it recycles a lot of material that had been used in previous works by the authors. Although I have read some of that, I have not read Second Machine Age. So I do not know how much of this is a repeat of that.
February 16, 2020
I was expecting more from this book, it felt basically a reference summary of The Platform Revolution, Thinking Fast and Slow (which are both amazing books) and numerous books written on the topic of AI. The authors also tried to bring in basic economic theory to this book (supply and demand relations, consumer surplus, demand curve, supply curve) which was indeed quite basic and did not lead to any new innovative angles. In the end I would not say that it was a complete waste of time due to the numerous examples analyzed through the above mentioned elements.
“In 2006, Avinash Kaushik and Ronny Kohavi, two data analysis professionals who were then working at Intuit and Microsoft, respectively, came up with the acronym HiPPO to summarize the dominant decision-making style at most companies. It stands for “highest-paid person’s opinion.” We love this shorthand and use it a lot, because it vividly illustrates the standard partnership. Even when the decisions are not made by the highest-paid people, they’re often—too often—based on opinions, judgments, intuition, gut, and System 1. The evidence is clear that this approach frequently doesn’t work well, and that HiPPOs too often destroy value.”
“Owners of premium brands can charge more for their offerings, but the owners of two-sided networks want to pay to sellers as little as possible of the money they take in from buyers. The result is an obvious tension. Many platforms, especially when they’re new and trying to build volume and network effects, want to have on board at least one prestigious brand. But as platforms grow, they want to keep more of the consumer’s share of both mind and wallet.”
“Pricing strategies for two-sided networks can be aggressive and seemingly nonsensical if you don’t understand their peculiar economics. In particular, changes in the quantity demanded on one side of the network can affect demand on the other side of the network...Lowering the price on one side of the network increases demand on both sides of the network, creating an extra benefit for each price cut.”
“In 2006, Avinash Kaushik and Ronny Kohavi, two data analysis professionals who were then working at Intuit and Microsoft, respectively, came up with the acronym HiPPO to summarize the dominant decision-making style at most companies. It stands for “highest-paid person’s opinion.” We love this shorthand and use it a lot, because it vividly illustrates the standard partnership. Even when the decisions are not made by the highest-paid people, they’re often—too often—based on opinions, judgments, intuition, gut, and System 1. The evidence is clear that this approach frequently doesn’t work well, and that HiPPOs too often destroy value.”
“Owners of premium brands can charge more for their offerings, but the owners of two-sided networks want to pay to sellers as little as possible of the money they take in from buyers. The result is an obvious tension. Many platforms, especially when they’re new and trying to build volume and network effects, want to have on board at least one prestigious brand. But as platforms grow, they want to keep more of the consumer’s share of both mind and wallet.”
“Pricing strategies for two-sided networks can be aggressive and seemingly nonsensical if you don’t understand their peculiar economics. In particular, changes in the quantity demanded on one side of the network can affect demand on the other side of the network...Lowering the price on one side of the network increases demand on both sides of the network, creating an extra benefit for each price cut.”
December 17, 2017
When I read Brynjolfsson and McAfee's "Race Against the Machine" a few years ago, it was a real eye opener on the transformative potential of new technologies, especially artificial intelligence. Back then, self driving cars hadn't reached the centre of the public debate yet, and only hypergeeks had an idea what neural networks were. One of the reasons why reading the book was such a disquieting experience was that serious economists were suggesting that there were good reasons to believe that this time was indeed different, and technological change could be a net destroyer of jobs for human beings, just as the private car destroyed most jobs for horses. These ideas were further elaborated in "The second machine age". Both books remain essential reading for anyone who wants to participate in an intelligent and informed discussion about the impact of technology on our societies, and what policy makers need to do to prepare the labour force for this new era.
In "Machine, platform, crowd", the focus shifts away from policy implications to recommendations for business strategy. For a variety of professional reasons, I have closely watched the evolving discussion on artificial intelligence, web based platforms and crowdsourced information (especially with respect to the implications for transport and mobility) in recent years. Therefore, this book felt less radically novel than its predecessors.
I would however still very strongly recommend it. Brynjolfsson and McAfee do not shy away from tackling topics that are highly controversial, and where the world is increasingly divided between believers and non-believers. If we really want to understand how technology is changing business models and interactions between humans (and is in turn influenced by both), we need more than evangelists. We need people who offer a cool headed analysis of these trends, and who do not get carried away by whatever is the latest fad. Brynjolfsson and McAfee offer precisely what we need.
In "Machine, platform, crowd", the focus shifts away from policy implications to recommendations for business strategy. For a variety of professional reasons, I have closely watched the evolving discussion on artificial intelligence, web based platforms and crowdsourced information (especially with respect to the implications for transport and mobility) in recent years. Therefore, this book felt less radically novel than its predecessors.
I would however still very strongly recommend it. Brynjolfsson and McAfee do not shy away from tackling topics that are highly controversial, and where the world is increasingly divided between believers and non-believers. If we really want to understand how technology is changing business models and interactions between humans (and is in turn influenced by both), we need more than evangelists. We need people who offer a cool headed analysis of these trends, and who do not get carried away by whatever is the latest fad. Brynjolfsson and McAfee offer precisely what we need.
December 31, 2017
新思惟高雄校友會的時候，可能因為小弟讀的書稍微多些，想事情也比較積極，我被問到最多的問題，就是「人工智慧來了，我們該怎麼辦？」總共四次，而且前一桌問完，下一桌馬上又問。
除了根據提問者的行業與憂慮，精確地回答之外，之前我會建議朋友去看《人類大歷史》，先瞭解我們自己是怎樣的生物後，再讀《人類大命運》，瞭解我們即將創造出的未來是什麼樣子的。不過這兩本「人類大○○」的作者哈拉瑞，畢竟是歷史學家出身，即使他的跨領域知識已經非常強悍，但畢竟不是真正的資訊科技從業者，看大趨勢沒問題，但當下的今年、明年，我們該注意哪些時事與其意義，就稍微少了些。
同樣是天下文化出的《機器、平台、群眾》，就解決了這個問題。
首先，這本書告訴你，你該擔心的不只是書名中「機器」所指的人工智慧（驚）！世界級的網路平台（書名「平台」所指），以及分散式的群眾智慧（書名「群眾」所指），更是靜悄悄的讓很多人失業，而且被取代的人們，非常弱勢，幾乎無法反擊。
AlphaGO 讓職業圍棋選手毫無勝算，Uber 讓計程車司機陷入苦戰，Wikipedia 讓大英百科全書幾乎完蛋。這三個領域，分別就是機器、平台、群眾的寧靜革命。
即使單說人工智慧領域，電腦所做的設計、創新，都開始超越人類。過去我們以為，數位工具是我們大腦的外接儲存系統，勉強就是個不錯的資料庫或硬碟而已，沒想到才過幾年，電腦已經能處理一部份我們大腦在做的分析、判斷、設計、建構，而且做得更好。
其次，這兩個作者 Andrew McAfee 與 Erik Brynjolfsson 資歷顯赫，專長是研究資訊科技對商業、經濟、企業的影響，而這正是最近十年改變人類生活樣貌最顯著的領域。
書本的寫作結構，就是一直先告訴你，目前世界上已經出現的各種實驗、研究、商業測試，反覆的提醒：「世界不是即將改變，而是已經改變」，只是火現在還沒燒到你身上而已。接著分析一般人常見的「妄念」，像是「我要怎麼跟人工智慧競爭」這種問題，作者會直接告訴你，人類沒有勝算，你要改變自己的心態，把機器能做的都交給機器去做。
就像汽車問世後，如果你問「我該怎麼��汽車比速度？」「我要怎麼跟汽車競爭？」這樣就搞錯問題了，你該問的，是「我要怎麼學會開車？」「我要怎麼才能弄到一台汽車？」
最後，再根據他們兩人的共識分析，告訴你哪些領域是我們還有機會的，給出很明確的指引，哪些領域短期內不太可能被 AlphaGO、Uber、Wikipedia 這樣的類似產物取代。
有趣的是，大概是怕讀者一下子聽到太多資訊消化不良，每章最後還幫你整理好「本章摘要」以及「延伸思考題」，確定你有看懂重點，也真的讓大腦動一動。
https://i-chentsai.innovarad.tw/2017/...
除了根據提問者的行業與憂慮，精確地回答之外，之前我會建議朋友去看《人類大歷史》，先瞭解我們自己是怎樣的生物後，再讀《人類大命運》，瞭解我們即將創造出的未來是什麼樣子的。不過這兩本「人類大○○」的作者哈拉瑞，畢竟是歷史學家出身，即使他的跨領域知識已經非常強悍，但畢竟不是真正的資訊科技從業者，看大趨勢沒問題，但當下的今年、明年，我們該注意哪些時事與其意義，就稍微少了些。
同樣是天下文化出的《機器、平台、群眾》，就解決了這個問題。
首先，這本書告訴你，你該擔心的不只是書名中「機器」所指的人工智慧（驚）！世界級的網路平台（書名「平台」所指），以及分散式的群眾智慧（書名「群眾」所指），更是靜悄悄的讓很多人失業，而且被取代的人們，非常弱勢，幾乎無法反擊。
AlphaGO 讓職業圍棋選手毫無勝算，Uber 讓計程車司機陷入苦戰，Wikipedia 讓大英百科全書幾乎完蛋。這三個領域，分別就是機器、平台、群眾的寧靜革命。
即使單說人工智慧領域，電腦所做的設計、創新，都開始超越人類。過去我們以為，數位工具是我們大腦的外接儲存系統，勉強就是個不錯的資料庫或硬碟而已，沒想到才過幾年，電腦已經能處理一部份我們大腦在做的分析、判斷、設計、建構，而且做得更好。
其次，這兩個作者 Andrew McAfee 與 Erik Brynjolfsson 資歷顯赫，專長是研究資訊科技對商業、經濟、企業的影響，而這正是最近十年改變人類生活樣貌最顯著的領域。
書本的寫作結構，就是一直先告訴你，目前世界上已經出現的各種實驗、研究、商業測試，反覆的提醒：「世界不是即將改變，而是已經改變」，只是火現在還沒燒到你身上而已。接著分析一般人常見的「妄念」，像是「我要怎麼跟人工智慧競爭」這種問題，作者會直接告訴你，人類沒有勝算，你要改變自己的心態，把機器能做的都交給機器去做。
就像汽車問世後，如果你問「我該怎麼��汽車比速度？」「我要怎麼跟汽車競爭？」這樣就搞錯問題了，你該問的，是「我要怎麼學會開車？」「我要怎麼才能弄到一台汽車？」
最後，再根據他們兩人的共識分析，告訴你哪些領域是我們還有機會的，給出很明確的指引，哪些領域短期內不太可能被 AlphaGO、Uber、Wikipedia 這樣的類似產物取代。
有趣的是，大概是怕讀者一下子聽到太多資訊消化不良，每章最後還幫你整理好「本章摘要」以及「延伸思考題」，確定你有看懂重點，也真的讓大腦動一動。
https://i-chentsai.innovarad.tw/2017/...
August 23, 2020
Extensively researched and thoughtful structured, the book explains why specific modern innovations have gained worldwide commercial successes by draiwng references back to classical microeconomic principles. Consider the number of books already in existence on the subject matters (machine, crowd, platforms, AI, etc.) - with the bulk of them focusing on the narratives rather than the analysis - this book stands out with its unique insights and academic rigour. Specific innovations vs economic principles discussed include:
Spotify - free, perfect and instant distribution
Facebook and Whatsapp - network effects
Apps - compliments (to smartphones)
Uber and AirBnB - price elasticises and economics of two-sided networks
Apple iOs - switch / sunk cost
Each chapter ends with an executive summary, and a list of questions that encourage introspection and application by the reader. This is a great book for anybody who wishes to gain clarity and focus in their career development. Also a highly current read for gaining a general understanding of development in computer science - both hard and soft - will be changing societies and the world of commerce.
Spotify - free, perfect and instant distribution
Facebook and Whatsapp - network effects
Apps - compliments (to smartphones)
Uber and AirBnB - price elasticises and economics of two-sided networks
Apple iOs - switch / sunk cost
Each chapter ends with an executive summary, and a list of questions that encourage introspection and application by the reader. This is a great book for anybody who wishes to gain clarity and focus in their career development. Also a highly current read for gaining a general understanding of development in computer science - both hard and soft - will be changing societies and the world of commerce.
January 29, 2021
Excellent. I think its a must read for all teenagers >16 or 17 and all the way up to where productive age finishes. The world is changing and fast. This read helps us understand how.
November 5, 2017
Book extracts I found particularly useful:
Technologies, platforms, digital communities:
- Page 75: Neural networks become more powerful as their size increases. And big data, i.e. the recent explosion of digital text, pictures, sounds, videos etc., has been almost as important to machine learning as Moore's law.
- Page 88: Many transactions and interactions, which used to take place between people in the physical world, are now completed via digital interfaces. An increasing number of tasks are being / can be done by machines. Examples: Transportation / driving, buying / paying for products and services.
- Page 101: 90% of all crop spraying in Japan is done by unmanned helicopters.
- Page 106: An important benefit of 3D printing is that it makes experimentation and customization inexpensive.
- Page 161: Examples of reasons for making apps available for free: 1. Freemium. Free products / services increase demand for paid products / services. 2. Ad revenue. 3. Public service. Example: FixMyStreet app helps everyone improve a city.
- Page 188: www.flexe.com connects partially or temporarily empty warehouses with companies that need short-term additional space.
- Page 190: Examples of platforms that conduct surveys: www.usertesting.com. www.survata.com. www.dscout.com. Google Consumer Surveys.
- Page 191: Other platform examples: www.go-jek.com connects riders and bikes. www.edaixi.com makes it easier for people to have a bag of laundry collected, cleaned, ironed and returned. www.guaguaxiche.com sends a professional to wash a car wherever it is parked in a city.
- Page 230: Libraries are among the oldest institutions of civilization. Libaries are founded and funded by monarchs, churches, democratically elected governments, and philantropists. Typically, libaries are staffed by trained professionals who select, arrange, and maintain their collections. The Internet is a crowd-generated and constantly growing and changing library.
- Page 254 and 261: www.topcoder.com, www.innocentive.com and www.kaggle.com are platforms using which people can solve various challenges.
- Page 259: Studying 166 scientific challenges posted on www.innocentive.com, Lakhani and Lars Bo Jeppesen found out that the challenges most likely to be successfully solved were those that attracted people who were "far away" from the organization that posted the challenge. "Far away" can mean, for example, technically, socially, geographically and/or intellectually far away. Outsiders have become very valuable to help bring us all forward.
- Page 261: www.99designs.com, www.behance.net, www.care.com, www.upwork.com, www.care.com and www.taskrabbit.com are platforms using which people can help out solve tasks and/or involve people in solving tasks. To develop a logo, I tried using www.designs.com and was very satisfied with the work the designers, who participated in the design competition, I created, did.
- Page 313: Markets typically have lower production costs, i.e. costs that come with making goods and services. On the other hand, hierarchies typically have lower coordination costs, i.e. costs associated with setting up the production and running it smoothly. Search engines, communicating networks and digital platforms / communities drive down coordination costs. Logic dictates that as coordination costs go down, markets become more attractive. Thereby, "unbundling" firms have increased in recent years, as digital technologies have improved and diffused.
Values, competencies, culture:
- Page 21: Strong expertise can blind people in successful companies to hold on to status quo and not test possibilities / new technologies that depart from the status quo. Examples: Traditional schools and universities. Traditional banks. Traditional retail shops. Traditional museums. Traditional hospitals.
- Page 45: Avinash Kaushik and Ronny Kohavi came up with the acronym HiPPO [Highest Paid Person's Opinion] to summarize the dominant decision-making style at most companies. The evidence is clear: HiPPOs too often destroy value.
- Page 61: Among excellent companies, a fundamental shift is taking place: Away from long-range forecasts, long-term plans as well as big bets and towards taking small steps, testing / trying out ideas, getting feedback and making continuous adjustments.
- Page 123: The ability to work effectively with people's emotional states and social drives will remain a human skill for some time to come.
- Page 241: Key principles of www.linux.com: 1. Openness. Thousands of individual developers participated in developing the software. 2. Non-credentialism. Linus Torvalds required neither diplomas, good grades, years of experience or any other credentials. He just made the source code available on the Internet and asked for help to improve it. 3. Verifiable and reversible contributions. This means that if a piece of code degrades performance, it is easy to revert to the most recent version of the software. 4. Clear outcomes. 5. Self-organization. People decided themselves which parts of Linux they wanted to work on. 6. Geeky leadership. Torvalds sometimes posted very strongly worded views - leaving noone in doubt of what was not acceptable to do.
- Page 248: www.wikipedia.org was able to activate the crowd because it adopted the principles of openness, noncredentialism, and self-organization.
- Page 324: Vish Makhijani, www.udacity.com: There are talented people all over the place. We don't have to hire them. They (outsiders) can actually privide just as meaningful feedback, if not better.
- Page 333: One of the things our economy needs most are people, who can design and implement new combinations of technologies, human skills and other resources / assets to solve problems and meet the needs of potential customers. Machines are not very good at this sort of large-scale creativity and planning, but humans are.
Technologies, platforms, digital communities:
- Page 75: Neural networks become more powerful as their size increases. And big data, i.e. the recent explosion of digital text, pictures, sounds, videos etc., has been almost as important to machine learning as Moore's law.
- Page 88: Many transactions and interactions, which used to take place between people in the physical world, are now completed via digital interfaces. An increasing number of tasks are being / can be done by machines. Examples: Transportation / driving, buying / paying for products and services.
- Page 101: 90% of all crop spraying in Japan is done by unmanned helicopters.
- Page 106: An important benefit of 3D printing is that it makes experimentation and customization inexpensive.
- Page 161: Examples of reasons for making apps available for free: 1. Freemium. Free products / services increase demand for paid products / services. 2. Ad revenue. 3. Public service. Example: FixMyStreet app helps everyone improve a city.
- Page 188: www.flexe.com connects partially or temporarily empty warehouses with companies that need short-term additional space.
- Page 190: Examples of platforms that conduct surveys: www.usertesting.com. www.survata.com. www.dscout.com. Google Consumer Surveys.
- Page 191: Other platform examples: www.go-jek.com connects riders and bikes. www.edaixi.com makes it easier for people to have a bag of laundry collected, cleaned, ironed and returned. www.guaguaxiche.com sends a professional to wash a car wherever it is parked in a city.
- Page 230: Libraries are among the oldest institutions of civilization. Libaries are founded and funded by monarchs, churches, democratically elected governments, and philantropists. Typically, libaries are staffed by trained professionals who select, arrange, and maintain their collections. The Internet is a crowd-generated and constantly growing and changing library.
- Page 254 and 261: www.topcoder.com, www.innocentive.com and www.kaggle.com are platforms using which people can solve various challenges.
- Page 259: Studying 166 scientific challenges posted on www.innocentive.com, Lakhani and Lars Bo Jeppesen found out that the challenges most likely to be successfully solved were those that attracted people who were "far away" from the organization that posted the challenge. "Far away" can mean, for example, technically, socially, geographically and/or intellectually far away. Outsiders have become very valuable to help bring us all forward.
- Page 261: www.99designs.com, www.behance.net, www.care.com, www.upwork.com, www.care.com and www.taskrabbit.com are platforms using which people can help out solve tasks and/or involve people in solving tasks. To develop a logo, I tried using www.designs.com and was very satisfied with the work the designers, who participated in the design competition, I created, did.
- Page 313: Markets typically have lower production costs, i.e. costs that come with making goods and services. On the other hand, hierarchies typically have lower coordination costs, i.e. costs associated with setting up the production and running it smoothly. Search engines, communicating networks and digital platforms / communities drive down coordination costs. Logic dictates that as coordination costs go down, markets become more attractive. Thereby, "unbundling" firms have increased in recent years, as digital technologies have improved and diffused.
Values, competencies, culture:
- Page 21: Strong expertise can blind people in successful companies to hold on to status quo and not test possibilities / new technologies that depart from the status quo. Examples: Traditional schools and universities. Traditional banks. Traditional retail shops. Traditional museums. Traditional hospitals.
- Page 45: Avinash Kaushik and Ronny Kohavi came up with the acronym HiPPO [Highest Paid Person's Opinion] to summarize the dominant decision-making style at most companies. The evidence is clear: HiPPOs too often destroy value.
- Page 61: Among excellent companies, a fundamental shift is taking place: Away from long-range forecasts, long-term plans as well as big bets and towards taking small steps, testing / trying out ideas, getting feedback and making continuous adjustments.
- Page 123: The ability to work effectively with people's emotional states and social drives will remain a human skill for some time to come.
- Page 241: Key principles of www.linux.com: 1. Openness. Thousands of individual developers participated in developing the software. 2. Non-credentialism. Linus Torvalds required neither diplomas, good grades, years of experience or any other credentials. He just made the source code available on the Internet and asked for help to improve it. 3. Verifiable and reversible contributions. This means that if a piece of code degrades performance, it is easy to revert to the most recent version of the software. 4. Clear outcomes. 5. Self-organization. People decided themselves which parts of Linux they wanted to work on. 6. Geeky leadership. Torvalds sometimes posted very strongly worded views - leaving noone in doubt of what was not acceptable to do.
- Page 248: www.wikipedia.org was able to activate the crowd because it adopted the principles of openness, noncredentialism, and self-organization.
- Page 324: Vish Makhijani, www.udacity.com: There are talented people all over the place. We don't have to hire them. They (outsiders) can actually privide just as meaningful feedback, if not better.
- Page 333: One of the things our economy needs most are people, who can design and implement new combinations of technologies, human skills and other resources / assets to solve problems and meet the needs of potential customers. Machines are not very good at this sort of large-scale creativity and planning, but humans are.
February 9, 2018
One of the best books I've read on the current trends (circa 2010-2020) regarding upcoming technologies, its affect on work and how to begin adapting to the change.
- Machine: AI, Machine Learning, Creativity and combining forces of human thought and machine thought
- Platform: How the traditional products and services have been affected and altered by digital platforms, and how the integration of products and platforms is underway
- Crowd: How collaborative effort across the world is supplementing traditional organizations and R&D, and how to evolve to fit in the incming changeso
Really recommended reading!
- Machine: AI, Machine Learning, Creativity and combining forces of human thought and machine thought
- Platform: How the traditional products and services have been affected and altered by digital platforms, and how the integration of products and platforms is underway
- Crowd: How collaborative effort across the world is supplementing traditional organizations and R&D, and how to evolve to fit in the incming changeso
Really recommended reading!
November 11, 2018
Though intended for a business audience this book offers a lot to readers who want to better understand the revolutionary changes that technology is making in our work lives and in our everyday lives. Some examples are: 1) explaining why platforms (think apps on the iPhone, Uber, Amazon that connect people with sellers of goods & services without owning much) have taken over so much of our economy; 2) explaining how the technology behind BitCoin, the Blockchain, is being used to decentralize record-keeping to allow enforceable contracts in the form of computer programs without the need for lawyers. This is not an easy read but offers mind-blowing insights.
May 23, 2022
Very enjoyable business book that talks about how machines, platforms and crowds will rule business now and in the future. He has questions at the end of each chapter, to help you think about how the chapter content may affect your current business. Its educational, and very forward thinking. Great book.
March 17, 2024
Read this book for an MBA course - the course was actually structured entirely around the book, spending thirds diving into the machine, platform and crowd. This book is a must-read for business professionals and anyone interested in learning more about our digital future. Insightful and easy to digest. Highly recommend!
October 25, 2017
An excellent synthesis of three key trends
I had heard good things about the book but never got around to reading it until I found out that it was on the syllabus for a grad-level class at ASU. I decided to give it a look and I was instantly hooked. The authors write in a clear style that is anything but academic. What's more, they did quite a bit of research. McAfee and Brynjolfsson don't make broad pronouncements. Rather, they back up their assertions and with plenty of examples, some of which I hadn't heard of before.
This is an excellent synthesis of three key trends and I need to read their prior one.
I had heard good things about the book but never got around to reading it until I found out that it was on the syllabus for a grad-level class at ASU. I decided to give it a look and I was instantly hooked. The authors write in a clear style that is anything but academic. What's more, they did quite a bit of research. McAfee and Brynjolfsson don't make broad pronouncements. Rather, they back up their assertions and with plenty of examples, some of which I hadn't heard of before.
This is an excellent synthesis of three key trends and I need to read their prior one.
January 4, 2018
4.5 rounded up to 5 stars.
Buckle up, it's coming!
Buckle up, it's coming!
January 26, 2018
The four stars is mostly for the "Machine" section, which was what I was really interested in, but there was also some really interesting/thought provoking material in the rest too.
January 8, 2021
Must read for anyone interesting in the digital economy.
December 24, 2021
Another great book by McAffee and Brynjolfsson on digital markets. They have a talent to explain the mechanics of digital markets so well that it is easy to follow. I also finally understood how bitcoins work 😄
March 29, 2019
Very thought provoking and changed some of my views on digital. Loved the summary and questions at the end of each chapter...really brought it to life.
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