How AI Can Create Jobs

Editor's Notes

• #3: The future is full of amazing things. On my way here, I spoke out loud to a $150 dollar device in my kitchen, asked it if my flight would be on time, and then asked it to call a Lyft to take me to the airport. A few minutes later a car showed up. And in a few years, that car might well be driving itself. Someone seeing this for the first time would have every excuse to say “WTF?” That can be an expression of surprise and delight that stands for What’s the Future? But many lot of people are reading the news about technology and the economy and are feeling a profound sense of unease. They are also asking themselves WTF? What’s the Future? But in a very different tone of voice.
• #4: They read that researchers at Oxford University project that up to 47% of human tasks, including many white collar jobs, could be eliminated by automation within the next 20 years.
• #5: They’ve heard that self driving cars and trucks will put millions of people out of work.
• #6: They’ve seen calls for Universal Basic Income, with the assumption that there will be nothing left for humans to do once corporations outsource all the work to machines. While I think Universal Basic Income is an intriguing idea, I don’t think we need it because there will be nothing left for humans to do. There’s plenty to do. The problem is that
• #7: Our 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.
• #8: Our 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. Increased productivity is the true source of wealth, but when it is used only to drive “shareholder value,” the rest of society suffers.
• #9: Even leaving aside the obvious problem of injustice and inequality, this is the stuff of revolutions. Andy Macafee, the author, with Erik Brynjolfsson, of the Second Machine Age and the forthcoming book Machine, Platform, Crowd once said to me, talking of the fear that robots will take over, “The people will rise up before the robots do.”
• #10: We’ve seen this happen before. In England, back in 1811 and 1812, a group of weavers waving the banner of a mythical character named Ned Ludd staged a rebellion, smashing the steam powered looms that were threatening their livelihood. Ludd and his compatriots were right to be afraid. The decades ahead were grim, as machines replaced human labor, and it took time for society to adjust.
• #11: But those weavers of Ned Ludd’s time couldn’t imagine that their descendants would have more clothing than the kings and queens of Europe, that ordinary people, not just kings and queens, would eat the fruits of summer in the depths of winter, luxuries brought from all over the world.
• #12: They couldn’t imagine that we’d tunnel through mountains and under the sea, that we’d fly through the air, crossing continents in hours, that we’d build cities in the desert with buildings a half mile high, that we’d put spacecraft in orbit, that we would eliminate so many scourges of disease! And they couldn’t imagine that their children, grandchildren, and great grandchildren would find meaningful work bringing all of these things to life!
• #13: And those in power couldn’t imagine that their failure to address the economic problems these advances were causing would lead to revolutions that would topple them from power. As Bill Janeway put it, The laws of welfare economics assert that when some people are made better off as the result of an economic policy change, the winners must compensate the losers. But “Unfortunately, the winners rarely do so except as the result of political coercion.”
• #14: What is our failure of imagination?
• #15: It isn’t technology that wants to eliminate jobs. Here’s what technology really wants. Nick Hanauer, who was one of the speakers at my Next:Economy Summit last year, put it best when he said: “Technology is the solution to human problems. We won’t run out of work till we run out of problems.” Are we done yet? Are we done yet?
• #16: Victorian England eventually rose to the challenge. Instead of sending children to work in the factories, they learned to send them to school. They shortened the work week and paid higher wages. And society became more prosperous. What is our failure of imagination? Why are we using technology to put people out of work rather than using technology to put people *to* work on the jobs of the future? What is our equivalent of sending kids to school instead of to work in the factories or the chimneys? What is our equivalent of the wonders that the industrial age brought to the world?
• #17: Charts like this one, from Max Roser’s Our World in Data, documenting the march of progress during the 20th century, are what we must aspire to.
• #18: This is a picture of the devastation in Syria. But you know what, this could have been Italy or France or Germany after World War II. Or London. Do we just accept that as the cost of doing business? Or can we solve for that, rebuilding as the US helped rebuild Europe after the scourge of World War II?
• #19: When I see Silicon Valley’s ambitions, they seem remarkably modest to me. Even the bold idea of rethinking the infrastructure of cities, as Google’s Sidewalk Labs is trying to do, seems like a pallid reflection of what is needed. We have 20 million refugees already, with more to come. Why are we looking to build a new digital city in the developed world rather than using the refugee crisis as an opportunity to build the cities of the future for people who need them!
• #20: Individual entrepreneurs are tacking the refugee problem. Josh Browder, the young British programmer whose bot-based Robot Lawyer helped people to challenge traffic tickets, has adapted his code to help refugees apply for asylum.
• #21: Climate change is for our generation what world War II was for our parents and grandparents, a challenge we must rise to or else be destroyed. We will need all the help we can get from technology to surmount this challenge.
• #22: OATV portfolio company Planet is well on its way to imaging the entire surface of the earth every day. Machine learning is used to notice small changes in this enormous flood of data, with uses ranging from noticing illegal logging, climate change patterns, agricultural productivity, and much more. Humans could never digest this flood of data without the help of AI.
• #23: In tests, Deepmind was able to predict data center power needs so effectively that Power Utilization Efficiency was improved by 40%. Think about applying those kinds of efficiency savings to our entire society. Deepmind is now in talks with the UK National Grid.
• #24: What’s the next step? I wanted to highlight Elon Musk’s new company, Neuralink, as an example of the kind of big, bold problems we should be tackling with AI. Brain-machine interfaces could help repair brain injuries, control prosthetics, or let us work more efficiently with AI.
• #25: But what I especially loved in Tim Urban’s story about Neuralink was his exposition of Elon Musk’s fundamental business model, which is to prove that something hard can be done, as a way to get “the Human Colossus” working on the problem. Tesla, SolarCity, SpaceX, and now Neuralink are all examples of this design pattern.
• #26: My point: work on stuff that matters, stuff that is hard and really make the world a better place. Don’t use technology just to eliminate people and cut costs. Use it to do things that were previously impossible, that will be as astonishing to people as the great works of the 19th and 20th century were to those who benefitted from them.
• #27: Yes, amazon has used robots for cost reduction, but they’ve simultaneously used them to DO MORE. The robots allow them to pack more different products into their warehouses, and ship them more efficiently, allowing them to cut delivery time. More and more products are delivered same day, leading to more demand, and making Amazon a more successful business, hiring even more people. When you reinvest in the flywheel of progress, rather than simply extracting profits, amazing things can happen.
• #28: Use technology to radically reinvent what is possible. Zipline, a California startup working in Rwanda, is a great example of reinvention. It shows how two of the latest technologies, on-demand and drones, can utterly transform how we think about healthcare delivery. They have been doing a pilot project, delivering blood and critical medicines to isolated local clinics. The country has poor, often impassable roads, and lacks developed hospital infrastructure. Postpartum hemorrhage is a major cause of death. By drone, blood can reach any corner of the country in 15 minutes or less. We should be thinking about how technologies like on demand and self-driving cars would let us reinvent public transportation and the shape of our cities, not regulating them as a threat to incumbent 20th century industries! The key to making good use of new technology is to keep your eyes fixed on the fitness function of government, which is the greatest good for all of society. Embrace the future. Don’t fight it. WTF can also stand for “Welcome the future!” Thank you very much.
• #29: I believe that AI is one of the foundational technologies for transforming our economy. Let’s think about how increasing efficiency and new kinds of work go hand in hand. Al is already being used in both clinical practice and in research. Google’s Deep mind is sifting through millions of eye scans, working to make the UK National Health Service more efficient.
• #30: Yet, at the Royal Free Hospital, where DeepMind is running its pilot program, they report “Within a few weeks of being introduced, nurses who have been using [Deepmind] Streams report that it has been saving them up to two hours every day, which means they can spend more time face-to-face with patients.”
• #31: This is a great example, once again of what Clayton Christensen called The Law of Conservation of Attractive Profits: “When attractive profits disappear at one stage in the value chain because a product becomes modular and commoditized, the opportunity to earn attractive profits with proprietary products will usually emerge at an adjacent stage.” I used this law to explain how open source software and the open protocols of the internet would lead to a new age where big data and collective intelligence would become valuable, and now I’m seeing it again as AI creates new opportunities for human caring and creativity.
• #32: As machines commodify certain types of human mental labor—the routine, mechanical parts—the truly human contributions will become more valuable. Sam Lessin of AI assistant company Fin put it well…
• #33: Paul English, who was the CTO and co-founder of Kayak, which put travel agents out of work, now wants to reinvent the travel agency using AI. He’s betting that humans plus machines can provide better service. He says, “I want to make humans cool again.”
• #34: The same pattern is true in healthcare. Uber lost the plot when they started talking about self driving cars. Rather than crowing about how they’d finally get rid of those pesky drivers, they should have been talking about an experiment that they’ve run since 2014, delivering flu shots. “Sure, we won’t always have drivers. But just imagine how many other jobs we can restructure and make more magical and on demand once the transportation is even cheaper and more convenient!”
• #35: So when you see news that AI is better at spotting cancer in X-rays and other radiology scans than human radiologists, celebrate! After all
• #36: After all, there are already huge job shortages in healthcare. AI and other technologies could allow us to fill these gaps by “upskilling” workers who need less specialized training, creating both more jobs and better service than the current system. Will we have the courage and vision to seize the opportunity?
• #37: In countries with less-developed hospital infrastructure, we’re already seeing the shape of the future. Partners in Health trains community health workers in place of doctors. Imagine if they could be augmented with AI, Augmented Reality and Telepresence.
• #38: The fundamental technology design pattern is to augment humans, so they can do things that were previously impossible. This is as true in the age of AI as it was with the discovery of fire and the invention of the wheel and the stone axe.
• #39: Catalyte is a remarkable company in the US that uses machine learning to identify people with the skills to become good programmers, hire them, train them, and then put them to work. They’ve hired top performing programmers out of fast food jobs. Understanding that we have to invest in the productive workers of tomorrow is key to getting out of the technology as cost-savings trap.
• #40: That’s also what we’re about with Safari, O’Reilly’s online learning platform. It’s migrated from just being a platform for ebooks to a full-fledged platform for on-demand learning. And we’re increasingly using AI to help understand how to better match people with what they need to know.
• #41: This is the subject of my new book, out from Harper Business in October. Pre-order from Amazon! https://www.amazon.com/WTF-Whats-Future-Why-Its/dp/0062565710/