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2. “…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?”

4. Will there really be nothing left for people to do?
Is there really
nothing left for
humans to do?

5. Our global economy has the
mistaken idea that the goal of
technology is to maximize
productivity, even if that means
treating people as a cost to be
eliminated.

6. That’s a problem
“The people will rise up before
the robots do.”
Andy Macafee
Co-author, The Second
Machine Age
Erik Brynjolfsson and Andy Macafee

7. We’ve seen this happen before

8. The weavers of Ned Ludd’s
rebellion couldn’t imagine…

9. They couldn’t imagine…

10. What is our failure of imagination?

11. It isn’t technology that wants to eliminate jobs
“Technology is the solution to
human problems. We won’t
run out of work till we run
out of problems.”
Nick Hanauer

12. Some global grand challenges
technology can help us to solve
• Climate change.
• Rebuilding and rethinking the infrastructure by which we deliver water,
power, goods, and services like healthcare.
• Dealing with the “demographic inversion” — the lengthening lifespans
of the old and the smaller number of young workers to pay into the
social systems that support them.
• Income inequality.
• Displaced people. How could we use technology to create the
infrastructure for whole new cities, factories, and farms, so people
could be settlers, not refugees?

13. The use of automation by business to reduce labor costs and increase
profits is a social and political choice, not an economic law!

14. The March of Progress

15. But not everyone is equally happy

16. Fitness Landscapes
The way in which genes contribute
to the survival of an organism can
be viewed as a landscape of peaks
and valleys.
Through a series of experiments,
organisms evolve towards fitness
peaks, adapted to a particular
environment, or they die out.
Image source: http://evolution.berkeley.edu/evolibrary/article/side_0_0/complexnovelties_02

17. Fitness landscapes are dynamic
When conditions are stable, a
population chooses one fitness
peak and stays there.
But when conditions change
rapidly, populations must migrate
to a new fitness peak.

18. Local Maxima
Once you are on a peak, it’s
hard to get to another one,
even if it’s higher. You have
to go back down. It may be
easier to get to the top if you
are already starting from a
valley floor.

19. Technology also 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 digitalization of
the overall economy.
Personal
Computer
Big Data
and
AI
Smartphones
Apple

20. Big Data
and
AI
Tim Berners-Lee, 1990
The World Wide Web
Linus Torvalds, 1991
Linux

22. What is the result?
Voters are moving away from the
fitness peak of the neoliberal
consensus. We don’t know yet
where that new fitness peak will
be, but the migration is telling us
loud and clear that the economy
needs some fresh thinking.

23. Yes, things are changing.
But one thing doesn’t change.
A successful ecosystem creates
opportunity for everyone, not just
a few.

24. We will create the economy of the
future when we remember that the
function of technology is to empower
people to do things that were
previously impossible!

25. Government 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,
IBM Fellow

27. 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.

28. This is why Mark Zuckerberg tells his team
“Move fast and break things.”
-
Mark Zuckerberg

29. “Build, Measure, Learn.”
Eric Ries,
The Lean Startup

30. 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
In digital systems, the workers are programs,
and software engineers are their managers

31. “This isn’t just how we should be
developing software. It’s how we should be
developing policy.”
Cecilia Muñoz,
Director, White House
Domestic Policy Council

34. “Doing digital is not the same as being
digital.”
Josh Bersin
Deloitte

35. “We have to go from apps to ops.”
Jennifer Pahlka
Code for America
& USDS

37. “The smartphone is becoming a remote
control for real life.”
Matt Cohler,
Benchmark Partners

38. “Uber is a lesson in building for how the
world should work instead of optimizing for
how the world does work.”
Aaron Levie, Box.net