We Get What We Ask For: Towards a New Distributional Economics
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My keynote at the Venturebeat Blueprint conference in Reno, NV on March 6, 2018. The bad maps that are holding us back from building a better world. Technology need not eliminate jobs. It could be helping us tackle the world's great problems, and helping design marketplaces that ensure a more equitable distribution of the proceeds from doing so. The narrative that goes with the deck is in the speaker notes. There is also a summary and link to the video at https://venturebeat.com/2018/03/06/tim-oreilly-to-tech-companies-use-a-i-to-do-more-than-cut-costs/
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We Get What We Ask For: Towards a New Distributional Economics
- 1. We Get What We Ask For: Towards a New Distributional Economics Tim O’Reilly @timoreilly oreilly.com wtfeconomy.com Blueprint March 6, 2018
- 2. Will there really be nothing left for people to do? Is there really nothing left for humans to do?
- 4. 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
- 5. What is keeping us from working on stuff that matters?
- 6. Our maps of the world can steer us wrong In 1625, we thought California was an island
- 7. In 2018, we believe that it is technology that will put people out of work
- 8. What happened when Amazon added 45,000 robots
- 9. Do more. Do things that were previously impossible.
- 10. Don’t replace people. Augment them!
- 11. 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
- 12. The March of Progress
- 13. We Need More Entrepreneurs Like Elon Musk
- 14. In 2018, we still believe that it’s acceptable for companies to maximize their profits, regardless of the social, environmental and human consequences
- 15. This is ever more dangerous
- 16. We are all living and working inside a machine
- 17. AI is “the most serious threat to the survival of the human race” Elon Musk
- 18. 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
- 21. The Equinix NY4 data center, where trillions of dollars change hands
- 22. We didn’t mean to increase inequality and gut our economy “The Social Responsibility of Business Is to Increase Its Profits” Milton Friedman, 1970
- 23. Divergence of productivity and real median family income in the US
- 24. There’s plenty to go around. It’s just not going around!
- 25. In 2018, we are still trying to revive the old economy, rather than inventing the future that is possible now
- 26. “Economic Possibilities for Our Grandchildren” The world of his grandchildren—the world of those of us living today— would, “for the first time . . . be faced with [mankind’s] real, his permanent problem—how to use his freedom from pressing economic cares, how to occupy the leisure, which science and compound interest will have won for him, to live wisely and agreeably and well.” John Maynard Keynes John Maynard Keynes
- 27. “If total US household income of $8.495 trillion were shared by America’s 116 million households, each would earn $73,000, enough for a decent middle- class life.” Brian Arthur
- 28. The fundamental economic question is no longer how to incentivize production but how to incentivize fair distribution of the fruits of increased productivity Brian Arthur
- 29. Creating a “thick marketplace” A platform like the World Wide Web, Google or Facebook, or a service like Uber or Lyft or Airbnb is a matching marketplace. Algorithms decide who gets what and why.
- 30. What’s the Future? It’s Up To us wtfeconomy.com
- 31. Tim O’Reilly Founder & CEO, O’Reilly Media Partner, O’Reilly AlphaTech Ventures Board member, Code for America Co-founder, Maker Media @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
Editor's Notes
- So many companies play defense. Cut costs, watch the competition, follow best practices. Great entrepreneurs like Jeff Bezos and Elon Musk play offense. They see the world with fresh eyes, taking off the blinders that keep companies using technology to make slight improvements to existing products and practices, rather than imagining the world as it could be, given the new capabilities that technology has given us. They also understand that a business model is the way that all the parts of a business work together to create competitive advantage and customer value. Despite appearances, Uber and Lyft have a very different business model from taxi companies, Airbnb has a very different business model than Hyatt or Hilton, Google has a very different business model than Facebook in advertising, and than Apple in smartphones. Understanding how all the parts of your business work together is the key to innovation, because it lets you take advantage of the capabilities provided by new technology without getting sucked into the vortex of me-too thinking that never quite seems to work out the way it does for the startups who first show its power.
- We’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 our current market system is not allocating work and the rewards of that work correctly.
- There’s no work left for us to do? WTF???? That of course is an expression of surprise and delight that stands for What’s the Future? ;-) But many lot of people are reading the news about Artificial Intelligence and are feeling a profound sense of unease. They are also asking themselves WTF? but in a very different tone of voice, and with a different meaning.
- How about: 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 Why aren’t we doing this?
- What is keeping us from working on stuff that matters? What is our failure of imagination? Why can we only see AI and other WTF? Technologies of the 21st century as engines of disruption and destruction, rather than as engines of creativity and prosperity?
- Our maps of the world can steer us wrong. Henry Briggs, 1625: “California sometymes supposed to be a part of ye westerne continent, but since by a Spanish Charte taken by ye Hollanders it is found to be a goodly land…” In 1705, a Jesuit priest, Eusebio Kino, led an overland expedition across the top of the Sea of Cortez, and argued that what came to be called Baja California was in fact an island. My question is why it took an overland expedition, rather than just sailing up the Sea of Cortez!
- It is a bad map that tells us in 2018 that technology will put people out of work.
- Here’s what actually happened at Amazon as they added 45,000 robots to their warehouses. They added more than 250,000 human workers. The human workers are part of a complex ballet of human and machine, programmers and warehouse workers and delivery drivers, websites and robots, all coordinated by algorithms to work with uncanny speed and precision, delivering many products within a few hours in the luckiest zip codes. Source: https://qz.com/904285/the-optimists-guide-to-the-robot-apocalypse/
- This is the lesson: Do More. Do things that were previously impossible.
- Don’t replace people. Augment them!
- As my friend Nick Hanauer put it “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? I lthink often of Larry Summers’ laconic refutation of the Efficient Markets hypothesis: “There are idiots. Look around.” My refutation to the end of work doomsayers is similar: “There is lots of work to be done. Look around!”
- I highly recommend to doubters This World In Data, the site Max Roser runs at Oxford showing progress over the past centuries. Here’s one showing change in human life expectancy. You can see that for hundreds of years, life expectancy was flat, unless it went down due to wars and plague. Then suddenly in the mid 1800s, it suddenly goes up and to the right. And as you add new countries to this interactive visualization, you see that as they too join the industrial revolution, they follow the same path.
- There’s a wonderful illustration of the power of entrepreneurs to bestow this kind of gift in Wait But Why’s analysis of Elon Musk’s Neuralink startup. 2/3 way through the piece, Tim Urban explains what he thinks is Elon Musk’s company formula: found a company that will have a sustainable business model, but that will also be the match that ignites an industry and leads to a goal with an increased chance of a good future for humanity. We need more people who think like this. https://waitbutwhy.com/2017/04/neuralink.html
- The second bad map that we take for granted in 2018 is the idea that it’s acceptable for companies to maximize their profits, regardless of the social, environmental and human consequences
- This is ever more dangerous as the world becomes more complex and infused with the digital.
- You see, our modern systems are massive hybrid AIs. These Ais are not external to us. We are part of them. We are inside them. They shape what we think and how we act. When you look at a company like Google, you see that humans are working alongside automation in very new ways. Even in a company as driven by computer technology as Google, there are humans who keep things running. There are other humans who write code and AI models, and manage and train the algorithms of search, advertising, and the Google Brai. There are other humans – all of us - who contribute new knowledge and seek it out, reinforcing neural pathways by what we link to, and what we pass on. https://www.google.com/about/datacenters/gallery/#/people/14
- So when folks like Elon Musk say that AI is “the most serious threat to the survival of the human race”, it’s worth asking how that might be so in an age of what you might call “technological symbiogenesis” – the fusion of human and machine into a new kind of superorganism.
- Elon’s fears about AI are based on what you could call the “runaway objective function.” Every AI and every machine learning system has something it is trying to optimize for. And it can be single-minded in pursuit of that objective. Elon explained this well in a Vanity Fair interview: “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.” (Nick Bostrom first articulated the idea of the runaway optimization of an objective function in the context of AI with the thought experiment of a self-improving AI that had been given the goal of maximizing paperclip production.)
- We don’t have to wait for a future AI though to see runaway objective functions at work. I believe that Facebook’s struggle with fake news is a great example of the runaway objective function. Facebook told their systems to optimize for engagement – to show people more of what they liked, commented on, and shared. Their idea was that this would lead to more human connection. It turned out instead to increase hyperpartisanship and to drive people apart, and now they are trying to stop it. Facebook’s engineers are a bit of the same situation as Mickey Mouse in Walt Disney’s retelling of Goethe’s story The Sorcerer’s Apprentice. Mickey borrows his master’s spellbook, and compels the broom to help him fetch water. Unfortunately, he doesn’t know how to stop the broom, and before long
- He is desperately trying to find a way to stop the power he has unleashed. This is what Mark Zuckerberg and team look like right now. That’s a runaway objective function at work.
- Google and Facebook are two of the most visible hybrid human-machine systems out there. But there’s one other of these proto-Ais to consider, and that’s our financial markets. And that’s where we should be worrying about Skynet, that fabled AI gone wrong, hostile to humans. Like Google and Facebook and Twitter, our financial market is a composite organism made up of its human microbiome, which shapes its behavior, combined with machines driven by encoded objectives.
- And what is the objective function of our financial markets? When, in 1970, Milton Friedman said that the social responsibility of business is to increase its profits, and when, a few years later, Michael Jensen began to preach the gospel of shareholder value maximization and the need to align executive compensation with rising stock prices, they didn’t mean to create the devastation they wreaked on the economy, but it’s time to recognize it. (Milton Friedman penned an op-ed in the New York Times arguing that the social responsibility of business was to increase its profits. Anything else was, in effect, taking money from its shareholders. Then in 1976, William Meckling and Michael Jensen wrote a paper outlining the reasoning behind aligning the interests of management with shareholders, which was eventually accomplished with executive pay via stock options. So called “shareholder value” thinking was soon taught in business schools, and that’s when the great divergence between productivity and wages began.
- So, with that in mind, look at the divergence of productivity and real median family income? Why do we see that, despite the continuing growth of productivity, family incomes have stagnated, and as Raj Chetty’s research has shown, most children in developed countries can no longer expect to do better economically than their parents. Inequality has skyrocketed. I believe that it is the result of a very similar objective function gone awry. Our politicians and our businesses bought into an economic theory that said that if we optimized relentlessly for shareholder value, it would be good for the economy as a whole. It turned out not to be true. So just as the Facebook engineers are trying to re-engineer their algorithms, we need to re-engineer the economic algorithms that underly and shape our markets, giving us outcomes that are not those that we really want! Source http://stateofworkingamerica.org/charts/productivity-and-real-median-family-income-growth-1947-2009/ via https://en.wikipedia.org/wiki/Income_inequality_in_the_United_States
- There’s plenty to go around. It’s just not going around.
- There’s a real opportunity hidden in these hybrid systems, though. We’re held back from exploring their potential to make a better world by one more bad map: In 2018, we are still trying to revive the old economy, rather than inventing the future that is possible now
- The time is now to bring into being the world John Maynard Keynes envisioned in “Economic possibilities for our grandchildren.” “how to use [our] freedom from pressing economic cares, how to occupy the leisure, which science and compound interest will have won for [us], to live wisely and agreeably and well.” Keynes was wrong, as visionaries often are. He was too early. But he was right.
- Economist and complexity theorist Brian Arthur recently did a back-of-the-napkin calculation to figure out how far we are from what he calls “the Keynes moment.” And we’re definitely getting close, at least in America. He notes (while admitting that it shouldn’t be our goal to have a flat income distribution, because the competitive instinct, and the desire to improve our lot in life, is a key driver of progress) that “If total US household income of $8.495 trillion were shared by America’s 116 million households, each would earn $73,000, enough for a decent middle-class life.” https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/where-is-technology-taking-the-economy
- The point is that The fundamental economic question is no longer how to incentivize production but how to incentivize fair distribution of the fruits of increased productivity https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/where-is-technology-taking-the-economy
- One of the things that I’ve become obsessed with in this regard is the notion that our great technology platforms, ruled by algorithm, are starting to teach us about new ways to allocate the fruits of productivity that go beyond even the “invisible hand” of supply and demand driven by price signaling that we’ve taken for granted as the guiding for our economy. Economist Alvin E Roth won the Nobel prize for his work on the design of algorithms for markets without money – such as the markets for organ transplants or college admissions where the amount you pay doesn’t determine the outcome – showing that it is possible to design better algorithms for matching up supply and demand and creating what he calls a “thick marketplace.” I’m applying this idea to thinking about what platforms like Google and Facebook, Uber, Lyft, Alibaba and Amazon, or Airbnb might have to teach us about building a better economy through better algorithmic market design.
- The conclusion I’ve come to: What’s the future? It’s up to us. We can create a more equitable distribution of the fruits of human productivity, and it is our great cognitive machines that will help us do it. I’ve written about the topic in my new book WTF. Thank you very much.