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Networks and the Next Economy
Tim O’Reilly
@timoreilly
oreilly.com
wtfeconomy.com
Tech Week Kansas City
October 11, 2018
How is the economy changing?
What are the implications for business?
What does technology now make
possible that was previously impossible?
What work needs doing?
Why aren’t we doing it?
wtfeconomy.com
We have to let go of the maps that are steering us wrong
In 1625, we thought
California was an island
In 1977, we still thought robots might look like this
Here’s what we got instead
In 2005, we thought
the connected
taxicab looked like
this
Here’s what we got instead
“Framing blindness”
“Make it new!”
Ezra Pound
“Gradually, then suddenly”
Ernest Hemingway
Gradually, then suddenly
Large segments of the economy
are governed not by free markets
but by centrally managed platform
monopolies
Gradually, then suddenly
Artificial Intelligence and algorithmic
systems are everywhere, in new kinds
of partnerships with humans
In 2018, we still believe in the “invisible hand”
of free markets
Internet-scale networked platforms managed by algorithm
are fundamentally changing the economic equation
and the very nature of markets
The invisible hand at work
What happens when there’s only one queue?
Networks and the Next Economy
Networks and the Next Economy
Networks and the Next Economy
And what happens when there’s
only one price for everything?
Networks and the Next Economy
The algorithms decide “who gets what – and why”
Markets are outcomes. A better designed
marketplace can have better outcomes.
But it can be enormously disruptive for
existing participants.
Algorithms become a battleground
Security: “That word does not
mean what you think it means.”
We are all living and working inside a machine
“The Uber app is the drivers’ workplace,
as much as the city where they’re driving
is. Each decision about its interface
structures drivers’ interactions with Uber
the company as well as Uber the
transportation marketplace.”
Alexis Madrigal, The Atlantic,
“Uber Drivers are About to Get a New Boss”
An Amazon warehouse is a human-machine hybrid
If we want to understand the future of business and the
economy, we have to understand these platforms
Networks and the Nature of the Firm
“The existence of high transaction costs outside
firms led to the emergence of the firm as we
know it, and management as we know it….The
reverse side of Coase’s argument is as
important: If the (transaction) costs of exchanging
value in the society at large go down drastically
as is happening today [because of networks], the
form and logic of economic and organizational
entities necessarily need to change! The
mainstream firm, as we have known it, becomes
the more expensive alternative.”Esko Kilpi
A language for networked marketplaces
Network effect: the value of a network is
proportional to the square of the number of
possible connections
Scale effect: bigger is better (but not always)
Feedback effect: the more data you collect from
the marketplace, the more you can learn, and the
better the services you can provide
Two-sided market: different classes of users
being matched up: searchers and advertisers,
drivers and passengers, homes and renters.
Asymptotic Networks
“The reason Lyft is able to compete with
Uber is that even if they have fewer drivers
in many cities, both platforms are still able
to guarantee a ride with an average wait
time of 4 minutes. Neither can improve by
adding more drivers to a city.”
James Currier
Networks and the Next Economy
Networks and the Next Economy
Networks and the Next Economy
“A business model is the way that
all of the parts of a business work
together to create competitive
advantage and customer value.”
- Dan and Meredith Beam
Who Do You Want Your Customers to Become?
Henry Ford didn’t just rethink
the automobile and the
factory, he rethought the
work week, and the reasons
why people might want to
drive.
A Business Model Map of Uber
 A magical app that lets drivers
and passengers find each other
in real time
 A networked marketplace of
drivers and passengers
 Customers who trust that they
don’t have to drive their own car
 Augmented workers able to join
the market as and when they
wish
 A matching market managed by
algorithm
What makes an app “magical”?
1. It seems unbelievable at first.
2. It changes the way the world works, so that the
unbelievable comes to seem inevitable and normal.
3. It results in an ecosystem of new services, jobs, business
models, and industries.
Why simply adding an app doesn’t change the game for taxis
Think platform, think ecosystem
It’s very hard to beat an entrenched platform
at its own game
Technology has a fitness landscape
In my career, I’ve watched a number of migrations to new peaks, and I’d like to share with
you some observations about what happened, and why. And then we’ll talk about some
lessons for companies like Google, but also for the overall economy.
Apple
Personal
Computer
Big Data
and
AI
Smartphones
The Rules for Success Change
 IBM: Maximize competitive advantage by control over hardware
 Microsoft: Maximize competitive advantage by control over software
 Google: Maximize competitive advantage by control over data and marketplaces
 Apple: Maximize competitive advantage by integrated control of hardware, software, and
marketplace.
 In each case, companies playing by the old rules lost. Or did they?
Generosity takes us to the next peak
Tim Berners-Lee, 1990
The World Wide Web
Linus Torvalds, 1991
Linux
Big Data
and
AI
Tim Berners-Lee, 1990
The World Wide Web
Linus Torvalds, 1991
Linux
Generous or “Long-term greedy”?
Smart platforms enable their “hackers” and their ecosystem –
unfortunately, most eventually forget this lesson
Google’s share of ad revenue over time
O’Reilly Research
Where does it stop?
Networks and the Next Economy
Why must it be winner takes all?
?? ?
The great opportunity of the 21st century is to use our
newfound cognitive tools to build
sustainable networks and ecosystems
Growth goes on forever?
The runaway objective function
“Even robots with a seemingly
benign task could indifferently harm
us. ‘Let’s say you create a self-
improving A.I. to pick strawberries,’
Musk said, ‘and it gets better and
better at picking strawberries and
picks more and more and it is self-
improving, so all it really wants to do
is pick strawberries. So then it would
have all the world be strawberry
fields. Strawberry fields forever.’ No
room for human beings.”
Elon Musk, quoted in Vanity Fair
https://www.vanityfair.com/news/2017/03/elon-musk-
billion-dollar-crusade-to-stop-ai-space-x
“Doughnut Economics”
Kate Raworth
O’Reilly Media
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2.0, Maker Movement, Big Data
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companies
Change the world
by spreading the knowledge of innovators
Networks and the Next Economy
Networks and the Next Economy
Networks and the Next Economy
Networks and the Next Economy
Networks and the Next Economy
O’Reilly’s Platform-Centered Learning Ecosystem
Safari
(learning
platform)
Conferences/
Foo Camps
Live Training
Books
Video
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Notebooks
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Network
Materials for reference
and learning
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Cutting edge idea forums
Digital platform for
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across modalities.
Books, video,
synchronous and
asynchronous
online learning
Our ecosystem matches
thousands of learning providers
with millions of customers
How might network enablement play out
For Uber and Lyft?
For Airbnb?
For Facebook or Google?
For Amazon?
Market Networks
In a market network, you’re not
connecting a simple marketplace of
buyers and sellers, but also
connecting them with intermediaries
and service providers. A Market
Network combines elements of a
professional network, an online
marketplace, and SaaS tools.
Networks and the Next Economy
“We wouldn’t be able to build defensibility from our supply-
side relationships purely on the basis of a Marketplace
Network Effect, because it was in the interests of the real
estate agents to syndicate their listings through every
possible channel…. So we created an XML feed standard …
This prevented brokers from having to go through the hassle
of posting them manually to every channel, and soon our
competitors had adopted the same XML standards for their
sites as well.”
And, after 2009, when the real estate market collapsed, ”to
scale [a] new monetization strategy targeting smaller
customers, we set to work creating cost-effective marketing
and lead generation products for the individual real estate
agents.”
Pete Flint
“Once they get some traction, platforms survive
either because:
 They achieve critical mass in a market with
network effects. They are the default place to
go—this is why Craigslist, Airbnb, ebay, Etsy,
and other places with most of the inventory
thrive.
 They provide a tool set ecosystem. The
product or service has certain functions that
buyer and seller need (escrow, analytics, a
CRM, etc.) that the marketplace can provide with
an economy of scale that beats everyone doing
it themselves.”
Alistair Croll
In 2018, we believe that technology replaces people
“…47 percent of jobs are “at
risk” of being automated in the
next 20 years.”
Carl Frey and Michael Osborne, Oxford University
“The Future of Employment: How Susceptible
Are Jobs to Computerisation?”
Will there really be nothing left for people to do?
Is there really
nothing left for
humans to do?
Networks and the Next Economy
Dealing with climate change
Rebuilding our infrastructure
Feeding the world
Ending disease
Resettling refugees
Caring for each other
Educating the next generation
Enjoying the fruits of shared prosperity
This is what technology wants
“Prosperity in human societies is best
understood as the accumulation of
solutions to human problems. We won’t
run out of work until we run out of
problems.”
Nick Hanauer
What happened when Amazon added 45,000 robots
Jeff Bezos calls this “the flywheel”
“I’ve just invested in an AI startup that will put 30% of call
center workers out of a job.”
(A VC who shall remain nameless)
This is the master design pattern
for applying technology: Do more.
Do things that were previously
impossible.
The Augmented Worker
Neo: “Can you fly that thing?”
Trinity: “Not yet.”
Uber’s app isn’t quite what Trinity’s got, but…
“In order to fully reap the benefits of a
changing economy—and sustain growth
over the long-term—businesses will need
to increase the earnings potential of the
workers who drive returns, helping the
employee who once operated a machine
learn to program it. They must improve
their capacity for internal training and
education to compete for talent in today’s
economy and fulfill their responsibilities to
their employees.”
Just-in-time learning is a 21st century competency
Larry Fink,
CEO, Blackrock
WeWork Acquires The Flatiron School
Like Kiva (Amazon
Robotics), this is a
network-enabling
acquisition!
Supercharge the skills
of your employees, your customers, and your partners
Create more value than you capture
Work on stuff that matters
Tim O’Reilly
@timoreilly
• O’Reilly AI Conference
• Strata: The Business of Data
• JupyterCon
• O’Reilly Open Source Summit
• Maker Faire
• Foo Camp
• …
• 40,000+ ebooks
• Tens of thousands of hours
of video training
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• Millions of customers
• A platform for knowledge
exchange
• Commercial internet
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• Web 2.0
• Maker movement
• Government as a platform
• AI and The Next Economy
Founder & CEO, O’Reilly Media
Partner, O’Reilly AlphaTech Ventures
Board member, Code for America
Co-founder, Maker Media

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Networks and the Next Economy

  • 1. Networks and the Next Economy Tim O’Reilly @timoreilly oreilly.com wtfeconomy.com Tech Week Kansas City October 11, 2018
  • 2. How is the economy changing? What are the implications for business? What does technology now make possible that was previously impossible? What work needs doing? Why aren’t we doing it? wtfeconomy.com
  • 3. We have to let go of the maps that are steering us wrong In 1625, we thought California was an island
  • 4. In 1977, we still thought robots might look like this
  • 5. Here’s what we got instead
  • 6. In 2005, we thought the connected taxicab looked like this
  • 7. Here’s what we got instead
  • 11. Gradually, then suddenly Large segments of the economy are governed not by free markets but by centrally managed platform monopolies
  • 12. Gradually, then suddenly Artificial Intelligence and algorithmic systems are everywhere, in new kinds of partnerships with humans
  • 13. In 2018, we still believe in the “invisible hand” of free markets
  • 14. Internet-scale networked platforms managed by algorithm are fundamentally changing the economic equation and the very nature of markets
  • 16. What happens when there’s only one queue?
  • 20. And what happens when there’s only one price for everything?
  • 22. The algorithms decide “who gets what – and why” Markets are outcomes. A better designed marketplace can have better outcomes. But it can be enormously disruptive for existing participants.
  • 23. Algorithms become a battleground Security: “That word does not mean what you think it means.”
  • 24. We are all living and working inside a machine
  • 25. “The Uber app is the drivers’ workplace, as much as the city where they’re driving is. Each decision about its interface structures drivers’ interactions with Uber the company as well as Uber the transportation marketplace.” Alexis Madrigal, The Atlantic, “Uber Drivers are About to Get a New Boss”
  • 26. An Amazon warehouse is a human-machine hybrid
  • 27. If we want to understand the future of business and the economy, we have to understand these platforms
  • 28. Networks and the Nature of the Firm “The existence of high transaction costs outside firms led to the emergence of the firm as we know it, and management as we know it….The reverse side of Coase’s argument is as important: If the (transaction) costs of exchanging value in the society at large go down drastically as is happening today [because of networks], the form and logic of economic and organizational entities necessarily need to change! The mainstream firm, as we have known it, becomes the more expensive alternative.”Esko Kilpi
  • 29. A language for networked marketplaces Network effect: the value of a network is proportional to the square of the number of possible connections Scale effect: bigger is better (but not always) Feedback effect: the more data you collect from the marketplace, the more you can learn, and the better the services you can provide Two-sided market: different classes of users being matched up: searchers and advertisers, drivers and passengers, homes and renters.
  • 30. Asymptotic Networks “The reason Lyft is able to compete with Uber is that even if they have fewer drivers in many cities, both platforms are still able to guarantee a ride with an average wait time of 4 minutes. Neither can improve by adding more drivers to a city.” James Currier
  • 34. “A business model is the way that all of the parts of a business work together to create competitive advantage and customer value.” - Dan and Meredith Beam
  • 35. Who Do You Want Your Customers to Become? Henry Ford didn’t just rethink the automobile and the factory, he rethought the work week, and the reasons why people might want to drive.
  • 36. A Business Model Map of Uber  A magical app that lets drivers and passengers find each other in real time  A networked marketplace of drivers and passengers  Customers who trust that they don’t have to drive their own car  Augmented workers able to join the market as and when they wish  A matching market managed by algorithm
  • 37. What makes an app “magical”? 1. It seems unbelievable at first. 2. It changes the way the world works, so that the unbelievable comes to seem inevitable and normal. 3. It results in an ecosystem of new services, jobs, business models, and industries.
  • 38. Why simply adding an app doesn’t change the game for taxis
  • 40. It’s very hard to beat an entrenched platform at its own game
  • 41. Technology has a fitness landscape In my career, I’ve watched a number of migrations to new peaks, and I’d like to share with you some observations about what happened, and why. And then we’ll talk about some lessons for companies like Google, but also for the overall economy. Apple Personal Computer Big Data and AI Smartphones
  • 42. The Rules for Success Change  IBM: Maximize competitive advantage by control over hardware  Microsoft: Maximize competitive advantage by control over software  Google: Maximize competitive advantage by control over data and marketplaces  Apple: Maximize competitive advantage by integrated control of hardware, software, and marketplace.  In each case, companies playing by the old rules lost. Or did they?
  • 43. Generosity takes us to the next peak Tim Berners-Lee, 1990 The World Wide Web Linus Torvalds, 1991 Linux Big Data and AI Tim Berners-Lee, 1990 The World Wide Web Linus Torvalds, 1991 Linux
  • 45. Smart platforms enable their “hackers” and their ecosystem – unfortunately, most eventually forget this lesson
  • 46. Google’s share of ad revenue over time O’Reilly Research
  • 47. Where does it stop?
  • 49. Why must it be winner takes all? ?? ?
  • 50. The great opportunity of the 21st century is to use our newfound cognitive tools to build sustainable networks and ecosystems
  • 51. Growth goes on forever?
  • 52. The runaway objective function “Even robots with a seemingly benign task could indifferently harm us. ‘Let’s say you create a self- improving A.I. to pick strawberries,’ Musk said, ‘and it gets better and better at picking strawberries and picks more and more and it is self- improving, so all it really wants to do is pick strawberries. So then it would have all the world be strawberry fields. Strawberry fields forever.’ No room for human beings.” Elon Musk, quoted in Vanity Fair https://www.vanityfair.com/news/2017/03/elon-musk- billion-dollar-crusade-to-stop-ai-space-x
  • 54. O’Reilly Media ● Providing learning for almost 40 years ● Trends called – Open Source, Web 2.0, Maker Movement, Big Data ● 500 employees, thousands of contributors ● 5,000+ enterprise clients, 2.3m platform users globally ● 17 global technology events serving 20k individuals and 1,000 sponsor companies
  • 55. Change the world by spreading the knowledge of innovators
  • 61. O’Reilly’s Platform-Centered Learning Ecosystem Safari (learning platform) Conferences/ Foo Camps Live Training Books Video Jupyter Notebooks Expert Network Materials for reference and learning Immersive learning experiences with industry experts Cutting edge idea forums Digital platform for on-demand learning across modalities. Books, video, synchronous and asynchronous online learning Our ecosystem matches thousands of learning providers with millions of customers
  • 62. How might network enablement play out For Uber and Lyft? For Airbnb? For Facebook or Google? For Amazon?
  • 63. Market Networks In a market network, you’re not connecting a simple marketplace of buyers and sellers, but also connecting them with intermediaries and service providers. A Market Network combines elements of a professional network, an online marketplace, and SaaS tools.
  • 65. “We wouldn’t be able to build defensibility from our supply- side relationships purely on the basis of a Marketplace Network Effect, because it was in the interests of the real estate agents to syndicate their listings through every possible channel…. So we created an XML feed standard … This prevented brokers from having to go through the hassle of posting them manually to every channel, and soon our competitors had adopted the same XML standards for their sites as well.” And, after 2009, when the real estate market collapsed, ”to scale [a] new monetization strategy targeting smaller customers, we set to work creating cost-effective marketing and lead generation products for the individual real estate agents.” Pete Flint
  • 66. “Once they get some traction, platforms survive either because:  They achieve critical mass in a market with network effects. They are the default place to go—this is why Craigslist, Airbnb, ebay, Etsy, and other places with most of the inventory thrive.  They provide a tool set ecosystem. The product or service has certain functions that buyer and seller need (escrow, analytics, a CRM, etc.) that the marketplace can provide with an economy of scale that beats everyone doing it themselves.” Alistair Croll
  • 67. In 2018, we believe that technology replaces people
  • 68. “…47 percent of jobs are “at risk” of being automated in the next 20 years.” Carl Frey and Michael Osborne, Oxford University “The Future of Employment: How Susceptible Are Jobs to Computerisation?”
  • 69. Will there really be nothing left for people to do? Is there really nothing left for humans to do?
  • 71. Dealing with climate change Rebuilding our infrastructure Feeding the world Ending disease Resettling refugees Caring for each other Educating the next generation Enjoying the fruits of shared prosperity
  • 72. This is what technology wants “Prosperity in human societies is best understood as the accumulation of solutions to human problems. We won’t run out of work until we run out of problems.” Nick Hanauer
  • 73. What happened when Amazon added 45,000 robots
  • 74. Jeff Bezos calls this “the flywheel”
  • 75. “I’ve just invested in an AI startup that will put 30% of call center workers out of a job.” (A VC who shall remain nameless)
  • 76. This is the master design pattern for applying technology: Do more. Do things that were previously impossible.
  • 77. The Augmented Worker Neo: “Can you fly that thing?” Trinity: “Not yet.”
  • 78. Uber’s app isn’t quite what Trinity’s got, but…
  • 79. “In order to fully reap the benefits of a changing economy—and sustain growth over the long-term—businesses will need to increase the earnings potential of the workers who drive returns, helping the employee who once operated a machine learn to program it. They must improve their capacity for internal training and education to compete for talent in today’s economy and fulfill their responsibilities to their employees.” Just-in-time learning is a 21st century competency Larry Fink, CEO, Blackrock
  • 80. WeWork Acquires The Flatiron School Like Kiva (Amazon Robotics), this is a network-enabling acquisition!
  • 81. Supercharge the skills of your employees, your customers, and your partners
  • 82. Create more value than you capture
  • 83. Work on stuff that matters
  • 84. Tim O’Reilly @timoreilly • O’Reilly AI Conference • Strata: The Business of Data • JupyterCon • O’Reilly Open Source Summit • Maker Faire • Foo Camp • … • 40,000+ ebooks • Tens of thousands of hours of video training • Live training • Millions of customers • A platform for knowledge exchange • Commercial internet • Open source software • Web 2.0 • Maker movement • Government as a platform • AI and The Next Economy Founder & CEO, O’Reilly Media Partner, O’Reilly AlphaTech Ventures Board member, Code for America Co-founder, Maker Media