“…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?

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.

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

We’ve seen this happen before

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

They couldn’t imagine…

What is our failure of
imagination?

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

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?

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

The March of Progress

But not everyone is equally
happy

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

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.

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.

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

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

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.

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

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!

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

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.

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

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

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

“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

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

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

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

“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