SlideShare a Scribd company logo
1 of 77
Download to read offline
TIM O’REILLY
Founder + CEO
O’Reilly Media, Inc.
Twitter » @timoreilly
Rethinking Who Gets What and Why
How is work changing?
What does technology now make
possible that was previously
impossible?
What work needs doing?
How do we make the world
prosperous for all?
Why aren’t we doing it?
wtfeconomy.com
“My grandfather wouldn’t
recognize what I do as
work.”
Hal Varian,
Google Chief Economist
Rethinking Who Gets What and Why (NABE)
Many of today’s workers are programs.
Software developers are actually their managers.
Every day, they are inspecting the
performance of their workers and giving
them instruction (in the form of code)
about how to do a better job
Software has become a set of
ongoing business processes, not an artifact
New skillsets are needed
User Centered Design
Site Reliability Engineering
Data Science
Deep Learning
API Design
Economics
Market design
We have to let go of the maps that are steering us wrong
In 1625, we thought
California was an island
In 2018, it’s our maps of business
and the economy that are wrong
The invisible hand at work
What happens when there’s only one queue?
And it’s personalized for you?
Rethinking Who Gets What and Why (NABE)
Rethinking Who Gets What and Why (NABE)
Amazon.com
And what happens when there’s
only one price for everything?
Rethinking Who Gets What and Why (NABE)
Algorithms decide “who gets what – and why”
Markets are outcomes. A better designed
marketplace can have better outcomes.
Price signaling is no longer the primary coordinator
“Gradually, then suddenly”
Ernest Hemingway
Gradually, then suddenly
Large segments of the economy are
governed not by free markets but by
centrally managed platforms
Rethinking Who Gets What and Why (NABE)
“In an information-rich world, the wealth of
information means a dearth of something
else: a scarcity of whatever it is that
information consumes. What information
consumes is rather obvious: it consumes
the attention of its recipients. Hence a
wealth of information creates a poverty of
attention and a need to allocate that
attention efficiently.”
Herbert Simon
Algorithms have become a battleground
Security: “That word does not
mean what you think it means.”
Users post 7 billion pieces of content
to Facebook a day.
Expecting human fact checkers to
catch fake news is like asking workers
to build a modern city with only picks
and shovels.
At internet scale, we now rely
increasingly on algorithms to manage
what we see and believe.
Gradually, then suddenly
Artificial Intelligence and algorithmic
systems are everywhere, in new
kinds of partnerships with humans
“The hope is that, in not too many years, human
brains and computing machines will be coupled
together very tightly, and that the resulting
partnership will think as no human brain has ever
thought and process data in a way not
approached by the information-handling
machines we know today.”
- J.C.R. Licklider, Man-Machine Symbiosis,1960
We are all living and working inside a machine
It’s no longer just in the digital realm
An Amazon warehouse is a human-machine hybrid
Rethinking Who Gets What and Why (NABE)
It makes things like this possible
68 million monthly users
440,000 employees
336 million monthly active users
~3400 employees
Managing an algorithmic marketplace
Governance in the age of algorithms
 Must focus on outcomes, not on rules.
 Must operate at the speed and scale of the systems it is trying to regulate.
 Must incorporate real-time data feedback loops.
 Must be robust in the face of failure and hostile attacks.
 Must address the incentives that lead to misbehavior.
 Must be constantly refined to meet ever-changing conditions.
Real Time Digital Regulatory Systems
Google search quality
Social media feed organization
Email spam filtering
Credit card fraud detection
Risk management and hedging
Government and central bank statistics, economic modeling,
and regulations are too slow for the pace and scale of the
modern world
“Would you cross the street with
information that was five seconds
old?”
 -
Jeff Jonas,
CEO of Senzing,
Former IBM Fellow
“Why is policy still educated
guesswork with a feedback
loop measured in years?”
Tom Loosemore,
Former Deputy Director,
UK Government Digital Service
Rethinking Who Gets What and Why (NABE)
Rethinking Who Gets What and Why (NABE)
Governance too must be reshaped by the digital
“This isn’t just how we should be
developing software. It’s how we
should be developing policy.”
Cecilia Muñoz,
Former Director, White House
Domestic Policy Council
Algorithmic systems have an “objective function”
Google: Relevance
Facebook: Engagement
Uber and Lyft: Passenger pick up time
Scheduling software used by McDonald’s, The Gap,
or Walmart: Reduce employee costs and benefits
Central banks: Control inflation? Employment?
Interest rates?
When platforms get their algorithms wrong, there can be serious
consequences!
When platforms get
their objective function
wrong, there can be
serious
consequences!
Like the djinn of Arabian mythology, our digital djinni
do exactly what we tell them to do
Rethinking Who Gets What and Why (NABE)
Rethinking Who Gets What and Why (NABE)
Divergence of productivity
and real median family income in the US
“The art of debugging is
figuring out what you really told
your program to do rather than
what you thought you told it to
do.”
Andrew Singer
Andrew Singer
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
We’ve built one of these already
What is the objective function of our financial markets?
“The Social Responsibility of Business Is to
Increase Its Profits”
Milton Friedman, 1970
Is there really
nothing left
for humans to
do?
Rethinking Who Gets What and Why (NABE)
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
“A platform is when the
economic value of everybody
that uses it exceeds the
value of the company that
creates it. Then it's
a platform.” – Bill Gates
Once a platform stops creating more
value for others than it captures for
itself, people migrate elsewhere.
Microsoft crushed its ecosystem
How Industries Mature
1. Some new technology (the PC, the web, the smartphone) lowers the barriers to
participation and innovation.
2. The market explodes as “hackers” push the envelope of possibility, and
entrepreneurs make things easier for ordinary users.
3. The market stagnates as players become platforms, and raise barriers to entry.
Hackers and entrepreneurs move on, looking for new frontiers.
Or (rarely)
3. The industry builds a healthy ecosystem, in which hackers, entrepreneurs and
platform companies play a creative game of "leapfrog". No one gets complete lock in,
and everyone has to improve in order to stay competitive. Value is created for an
entire ecosystem.
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
Google’s share of ad revenue over time
O’Reilly Research
Generous is also “Long-term greedy”
“Self-interest properly regarded”
A new inclusive
opportunity
ecosystem keeps
the game going
Nations fail for the same reason as tech platforms
Inclusive economies outperform
extractive economies. When inclusive
economies fall prey to extractive elites,
everyone is worse off.
Growth goes on forever?
One of the key drivers of
corporate bad behavior is the
command given them by
financial markets that they
must constantly grow and
increase their profits
An alternative: “Doughnut Economics”
Kate Raworth
Oikonomia vs Chrematistike
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
Change the world
by spreading the knowledge of innovators
Rethinking Who Gets What and Why (NABE)
Rethinking Who Gets What and Why (NABE)
Rethinking Who Gets What and Why (NABE)
“The opportunity for AI is to help humans model
and manage complex interacting systems.”
Paul R. Cohen
Rethinking Who Gets What and Why (NABE)
“Computational Sustainability is a new interdisciplinary
research field, with the overarching goal of studying and
providing solutions to computational problems for balancing
environmental, economic, and societal needs for a
sustainable future. Such problems are unique in scale,
impact, complexity, and richness, often involving
combinatorial decisions, in highly dynamic and uncertain
environments, offering challenges but also opportunities for
the advancement of the state-of-the-art of computer and
information science. Work in Computational Sustainability
integrates in a unique way various areas within computer
science and applied mathematics, such as constraint
reasoning, optimization, machine learning, and dynamical
systems.”
Carla Gomes
The great opportunity of the 21st century is to use our
newfound cognitive tools to build
sustainable businesses and economies
Can we build an economic flywheel
that keeps us in the doughnut?
What’s the Future?
It’s Up To us
wtfeconomy.com
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

More Related Content

More from Tim O'Reilly

Open Source in the Age of Cloud AI
Open Source in the Age of Cloud AIOpen Source in the Age of Cloud AI
Open Source in the Age of Cloud AITim O'Reilly
 
We Must Redraw the Map
We Must Redraw the MapWe Must Redraw the Map
We Must Redraw the MapTim O'Reilly
 
Networks and the Next Economy
Networks and the Next EconomyNetworks and the Next Economy
Networks and the Next EconomyTim O'Reilly
 
Networks and the Nature of the Firm
Networks and the Nature of the FirmNetworks and the Nature of the Firm
Networks and the Nature of the FirmTim O'Reilly
 
The Real Work of the 21st Century
The Real Work of the 21st CenturyThe Real Work of the 21st Century
The Real Work of the 21st CenturyTim O'Reilly
 
Do More. Do things that were previously impossible!
Do More. Do things that were previously impossible!Do More. Do things that were previously impossible!
Do More. Do things that were previously impossible!Tim O'Reilly
 
We Get What We Ask For: Towards a New Distributional Economics
We Get What We Ask For: Towards a New Distributional EconomicsWe Get What We Ask For: Towards a New Distributional Economics
We Get What We Ask For: Towards a New Distributional EconomicsTim O'Reilly
 
Towards a New Distributional Economics
Towards a New Distributional EconomicsTowards a New Distributional Economics
Towards a New Distributional EconomicsTim O'Reilly
 
How AI Can Create Jobs
How AI Can Create JobsHow AI Can Create Jobs
How AI Can Create JobsTim O'Reilly
 
Amazon.com's Web Services Opportunity
Amazon.com's Web Services OpportunityAmazon.com's Web Services Opportunity
Amazon.com's Web Services OpportunityTim O'Reilly
 
WTF - Why the Future Is Up to Us - pptx version
WTF - Why the Future Is Up to Us - pptx versionWTF - Why the Future Is Up to Us - pptx version
WTF - Why the Future Is Up to Us - pptx versionTim O'Reilly
 
WTF? Why The Future Is Up To Us.
WTF? Why The Future Is Up To Us.WTF? Why The Future Is Up To Us.
WTF? Why The Future Is Up To Us.Tim O'Reilly
 
What's the Future?
What's the Future?What's the Future?
What's the Future?Tim O'Reilly
 
Why We'll Never Run Out of Jobs
Why We'll Never Run Out of JobsWhy We'll Never Run Out of Jobs
Why We'll Never Run Out of JobsTim O'Reilly
 
Reinventing Healthcare to Serve People, Not Institutions
Reinventing Healthcare to Serve People, Not InstitutionsReinventing Healthcare to Serve People, Not Institutions
Reinventing Healthcare to Serve People, Not InstitutionsTim O'Reilly
 
Government as a Platform: What We've Learned Since 2008 (ppt)
Government as a Platform: What We've Learned Since 2008 (ppt)Government as a Platform: What We've Learned Since 2008 (ppt)
Government as a Platform: What We've Learned Since 2008 (ppt)Tim O'Reilly
 
Government as a Platform: What We've Learned Since 2008 (pdf with notes)
Government as a Platform: What We've Learned Since 2008 (pdf with notes)Government as a Platform: What We've Learned Since 2008 (pdf with notes)
Government as a Platform: What We've Learned Since 2008 (pdf with notes)Tim O'Reilly
 
The AIs Are Not Taking Our Jobs...They Are Changing Them
The AIs Are Not Taking Our Jobs...They Are Changing ThemThe AIs Are Not Taking Our Jobs...They Are Changing Them
The AIs Are Not Taking Our Jobs...They Are Changing ThemTim O'Reilly
 
By People, For People
By People, For PeopleBy People, For People
By People, For PeopleTim O'Reilly
 

More from Tim O'Reilly (20)

Open Source in the Age of Cloud AI
Open Source in the Age of Cloud AIOpen Source in the Age of Cloud AI
Open Source in the Age of Cloud AI
 
We Must Redraw the Map
We Must Redraw the MapWe Must Redraw the Map
We Must Redraw the Map
 
Networks and the Next Economy
Networks and the Next EconomyNetworks and the Next Economy
Networks and the Next Economy
 
Networks and the Nature of the Firm
Networks and the Nature of the FirmNetworks and the Nature of the Firm
Networks and the Nature of the Firm
 
The Real Work of the 21st Century
The Real Work of the 21st CenturyThe Real Work of the 21st Century
The Real Work of the 21st Century
 
Do More. Do things that were previously impossible!
Do More. Do things that were previously impossible!Do More. Do things that were previously impossible!
Do More. Do things that were previously impossible!
 
We Get What We Ask For: Towards a New Distributional Economics
We Get What We Ask For: Towards a New Distributional EconomicsWe Get What We Ask For: Towards a New Distributional Economics
We Get What We Ask For: Towards a New Distributional Economics
 
Towards a New Distributional Economics
Towards a New Distributional EconomicsTowards a New Distributional Economics
Towards a New Distributional Economics
 
How AI Can Create Jobs
How AI Can Create JobsHow AI Can Create Jobs
How AI Can Create Jobs
 
Amazon.com's Web Services Opportunity
Amazon.com's Web Services OpportunityAmazon.com's Web Services Opportunity
Amazon.com's Web Services Opportunity
 
WTF?
WTF? WTF?
WTF?
 
WTF - Why the Future Is Up to Us - pptx version
WTF - Why the Future Is Up to Us - pptx versionWTF - Why the Future Is Up to Us - pptx version
WTF - Why the Future Is Up to Us - pptx version
 
WTF? Why The Future Is Up To Us.
WTF? Why The Future Is Up To Us.WTF? Why The Future Is Up To Us.
WTF? Why The Future Is Up To Us.
 
What's the Future?
What's the Future?What's the Future?
What's the Future?
 
Why We'll Never Run Out of Jobs
Why We'll Never Run Out of JobsWhy We'll Never Run Out of Jobs
Why We'll Never Run Out of Jobs
 
Reinventing Healthcare to Serve People, Not Institutions
Reinventing Healthcare to Serve People, Not InstitutionsReinventing Healthcare to Serve People, Not Institutions
Reinventing Healthcare to Serve People, Not Institutions
 
Government as a Platform: What We've Learned Since 2008 (ppt)
Government as a Platform: What We've Learned Since 2008 (ppt)Government as a Platform: What We've Learned Since 2008 (ppt)
Government as a Platform: What We've Learned Since 2008 (ppt)
 
Government as a Platform: What We've Learned Since 2008 (pdf with notes)
Government as a Platform: What We've Learned Since 2008 (pdf with notes)Government as a Platform: What We've Learned Since 2008 (pdf with notes)
Government as a Platform: What We've Learned Since 2008 (pdf with notes)
 
The AIs Are Not Taking Our Jobs...They Are Changing Them
The AIs Are Not Taking Our Jobs...They Are Changing ThemThe AIs Are Not Taking Our Jobs...They Are Changing Them
The AIs Are Not Taking Our Jobs...They Are Changing Them
 
By People, For People
By People, For PeopleBy People, For People
By People, For People
 

Recently uploaded

OpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureOpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureEric D. Schabell
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfJamie (Taka) Wang
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IES VE
 
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDEADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDELiveplex
 
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfDianaGray10
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationIES VE
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesMd Hossain Ali
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...Aggregage
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostMatt Ray
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdfPedro Manuel
 
Governance in SharePoint Premium:What's in the box?
Governance in SharePoint Premium:What's in the box?Governance in SharePoint Premium:What's in the box?
Governance in SharePoint Premium:What's in the box?Juan Carlos Gonzalez
 
UiPath Studio Web workshop series - Day 5
UiPath Studio Web workshop series - Day 5UiPath Studio Web workshop series - Day 5
UiPath Studio Web workshop series - Day 5DianaGray10
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaborationbruanjhuli
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Commit University
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfinfogdgmi
 
Cybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxCybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxGDSC PJATK
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Will Schroeder
 

Recently uploaded (20)

OpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureOpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability Adventure
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
 
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDEADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
 
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
 
201610817 - edge part1
201610817 - edge part1201610817 - edge part1
201610817 - edge part1
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
 
20230104 - machine vision
20230104 - machine vision20230104 - machine vision
20230104 - machine vision
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdf
 
Governance in SharePoint Premium:What's in the box?
Governance in SharePoint Premium:What's in the box?Governance in SharePoint Premium:What's in the box?
Governance in SharePoint Premium:What's in the box?
 
UiPath Studio Web workshop series - Day 5
UiPath Studio Web workshop series - Day 5UiPath Studio Web workshop series - Day 5
UiPath Studio Web workshop series - Day 5
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
 
Cybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxCybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptx
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
 

Rethinking Who Gets What and Why (NABE)

  • 1. TIM O’REILLY Founder + CEO O’Reilly Media, Inc. Twitter » @timoreilly Rethinking Who Gets What and Why
  • 2. How is work changing? What does technology now make possible that was previously impossible? What work needs doing? How do we make the world prosperous for all? Why aren’t we doing it? wtfeconomy.com
  • 3. “My grandfather wouldn’t recognize what I do as work.” Hal Varian, Google Chief Economist
  • 5. Many of today’s workers are programs. Software developers are actually their managers. Every day, they are inspecting the performance of their workers and giving them instruction (in the form of code) about how to do a better job
  • 6. Software has become a set of ongoing business processes, not an artifact
  • 7. New skillsets are needed User Centered Design Site Reliability Engineering Data Science Deep Learning API Design Economics Market design
  • 8. We have to let go of the maps that are steering us wrong In 1625, we thought California was an island
  • 9. In 2018, it’s our maps of business and the economy that are wrong
  • 11. What happens when there’s only one queue? And it’s personalized for you?
  • 15. And what happens when there’s only one price for everything?
  • 17. Algorithms decide “who gets what – and why” Markets are outcomes. A better designed marketplace can have better outcomes.
  • 18. Price signaling is no longer the primary coordinator
  • 20. Gradually, then suddenly Large segments of the economy are governed not by free markets but by centrally managed platforms
  • 22. “In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently.” Herbert Simon
  • 23. Algorithms have become a battleground Security: “That word does not mean what you think it means.”
  • 24. Users post 7 billion pieces of content to Facebook a day. Expecting human fact checkers to catch fake news is like asking workers to build a modern city with only picks and shovels. At internet scale, we now rely increasingly on algorithms to manage what we see and believe.
  • 25. Gradually, then suddenly Artificial Intelligence and algorithmic systems are everywhere, in new kinds of partnerships with humans
  • 26. “The hope is that, in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.” - J.C.R. Licklider, Man-Machine Symbiosis,1960
  • 27. We are all living and working inside a machine
  • 28. It’s no longer just in the digital realm
  • 29. An Amazon warehouse is a human-machine hybrid
  • 31. It makes things like this possible 68 million monthly users 440,000 employees 336 million monthly active users ~3400 employees
  • 32. Managing an algorithmic marketplace
  • 33. Governance in the age of algorithms  Must focus on outcomes, not on rules.  Must operate at the speed and scale of the systems it is trying to regulate.  Must incorporate real-time data feedback loops.  Must be robust in the face of failure and hostile attacks.  Must address the incentives that lead to misbehavior.  Must be constantly refined to meet ever-changing conditions.
  • 34. Real Time Digital Regulatory Systems Google search quality Social media feed organization Email spam filtering Credit card fraud detection Risk management and hedging
  • 35. Government and central bank statistics, economic modeling, and regulations are too slow for the pace and scale of the modern world “Would you cross the street with information that was five seconds old?”  - Jeff Jonas, CEO of Senzing, Former IBM Fellow
  • 36. “Why is policy still educated guesswork with a feedback loop measured in years?” Tom Loosemore, Former Deputy Director, UK Government Digital Service
  • 39. Governance too must be reshaped by the digital “This isn’t just how we should be developing software. It’s how we should be developing policy.” Cecilia Muñoz, Former Director, White House Domestic Policy Council
  • 40. Algorithmic systems have an “objective function” Google: Relevance Facebook: Engagement Uber and Lyft: Passenger pick up time Scheduling software used by McDonald’s, The Gap, or Walmart: Reduce employee costs and benefits Central banks: Control inflation? Employment? Interest rates?
  • 41. When platforms get their algorithms wrong, there can be serious consequences! When platforms get their objective function wrong, there can be serious consequences!
  • 42. Like the djinn of Arabian mythology, our digital djinni do exactly what we tell them to do
  • 45. Divergence of productivity and real median family income in the US
  • 46. “The art of debugging is figuring out what you really told your program to do rather than what you thought you told it to do.” Andrew Singer Andrew Singer
  • 47. 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
  • 48. We’ve built one of these already
  • 49. What is the objective function of our financial markets? “The Social Responsibility of Business Is to Increase Its Profits” Milton Friedman, 1970
  • 50. Is there really nothing left for humans to do?
  • 52. 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
  • 53. 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
  • 54. “A platform is when the economic value of everybody that uses it exceeds the value of the company that creates it. Then it's a platform.” – Bill Gates
  • 55. Once a platform stops creating more value for others than it captures for itself, people migrate elsewhere.
  • 57. How Industries Mature 1. Some new technology (the PC, the web, the smartphone) lowers the barriers to participation and innovation. 2. The market explodes as “hackers” push the envelope of possibility, and entrepreneurs make things easier for ordinary users. 3. The market stagnates as players become platforms, and raise barriers to entry. Hackers and entrepreneurs move on, looking for new frontiers. Or (rarely) 3. The industry builds a healthy ecosystem, in which hackers, entrepreneurs and platform companies play a creative game of "leapfrog". No one gets complete lock in, and everyone has to improve in order to stay competitive. Value is created for an entire ecosystem.
  • 58. 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
  • 59. Google’s share of ad revenue over time O’Reilly Research
  • 60. Generous is also “Long-term greedy”
  • 61. “Self-interest properly regarded” A new inclusive opportunity ecosystem keeps the game going
  • 62. Nations fail for the same reason as tech platforms Inclusive economies outperform extractive economies. When inclusive economies fall prey to extractive elites, everyone is worse off.
  • 63. Growth goes on forever? One of the key drivers of corporate bad behavior is the command given them by financial markets that they must constantly grow and increase their profits
  • 64. An alternative: “Doughnut Economics” Kate Raworth
  • 66. 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
  • 67. Change the world by spreading the knowledge of innovators
  • 71. “The opportunity for AI is to help humans model and manage complex interacting systems.” Paul R. Cohen
  • 73. “Computational Sustainability is a new interdisciplinary research field, with the overarching goal of studying and providing solutions to computational problems for balancing environmental, economic, and societal needs for a sustainable future. Such problems are unique in scale, impact, complexity, and richness, often involving combinatorial decisions, in highly dynamic and uncertain environments, offering challenges but also opportunities for the advancement of the state-of-the-art of computer and information science. Work in Computational Sustainability integrates in a unique way various areas within computer science and applied mathematics, such as constraint reasoning, optimization, machine learning, and dynamical systems.” Carla Gomes
  • 74. The great opportunity of the 21st century is to use our newfound cognitive tools to build sustainable businesses and economies
  • 75. Can we build an economic flywheel that keeps us in the doughnut?
  • 76. What’s the Future? It’s Up To us wtfeconomy.com
  • 77. 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