Knowledge in the Digital Age: Lessons from 21st Century Unicorns
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My keynote at the Stanford Center for Advanced Studies in the Behavioral Sciences annual summit. How knowledge is changing, becoming a part of real world services rather than a thing apart. Many of the slides are just pictures. The narrative is in the speaker notes, so be sure to download and read the whole thing.
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Knowledge in the Digital Age: Lessons from 21st Century Unicorns
- 1. Knowledge in the Age of Siri, Uber, and Hololens (We’ve Got This Whole Unicorn Thing Wrong) Tim O’Reilly O’Reilly Media @timoreilly CASBS Summit, Stanford November 5, 2015
- 2. @timoreilly#CASBSSUMMIT “Senator, you have to understand…” 2 Reid Hoffman, LinkedIn Senator Sheldon Whitehouse, D-RI
- 5. @timoreilly#CASBSSUMMIT 5 "I've seen no need for more than five computers in the whole world." -Thomas Watson, IBM, 1943.
- 6. @timoreilly#CASBSSUMMIT Moore’s Law has been responsible for a cascade of miracles.
- 7. @timoreilly#CASBSSUMMIT It has given us great powers.
- 8. @timoreilly#CASBSSUMMIT Are we using them wisely?
- 9. @timoreilly#CASBSSUMMIT We’ve Got This Whole Unicorn Thing Wrong
- 10. @timoreilly#CASBSSUMMIT “A unicorn is a startup with a valuation of at least a billion dollars”
- 12. @timoreilly#CASBSSUMMIT “A man breaking his journey between one place and another at a third place of no name, character, population or significance, sees a unicorn cross his path and disappear. That in itself is startling, but there are precedents for mystical encounters of various kinds, or to be less extreme, a choice of persuasions to put it down to fancy; until—“My God,” says a second man, “I must be dreaming, I thought I saw a unicorn.” At which point, a dimension is added that makes the experience as alarming as it will ever be. A third witness, you understand, adds no further dimension but only spreads it thinner, and a fourth thinner still, and the more witnesses there are the thinner it gets and the more reasonable it becomes until it is as thin as reality, the name we give to the common experience.” - Tom Stoppard, Rosencrantz and Guildenstern Are Dead 12
- 15. @timoreilly#CASBSSUMMIT Some Other Early Unicorns
- 17. @timoreilly#CASBSSUMMIT Real Unicorns Change the World And like Tom Stoppard’s unicorn, are eventually taken for granted, becoming “as thin as reality.”
- 18. @timoreilly#CASBSSUMMIT When did this stop being magical to us?
- 19. @timoreilly#CASBSSUMMIT The infrastructure of unicorns No one believed in it. Built for military use, then opened up to the world. Enabled everything from Google Maps to Uber, Lyft, Postmates, Instacart, and self- driving cars.
- 20. @timoreilly#CASBSSUMMIT So what makes a real unicorn? 1. It seems unbelievable at first. 2. It changes the way the world works, and ultimately changes the people who encounter it. 3. It has enormous impact, far beyond that captured by the inventors, entrepreneurs and venture capitalists who birthed it.
- 21. @timoreilly#CASBSSUMMIT “Successful innovators don’t ask their customers to do something different. They ask them to become someone different…. When Apple television advertisements show iPhone users asking Siri questions or telling ‘her’ what to do, the company is doing far more than showing off the versatility of its voice-recognition, artificial intelligence interface. Siri’s company asks its customers to become the sort of people who wouldn’t think twice about talking to their phone as a sentient servant.” Michael Schrage, Who Do You Want Your Customers to Become
- 22. @timoreilly#CASBSSUMMIT Some 21st Century Unicorns, Slowly Fading Into the Ordinary
- 30. #CASBSSUMMIT @timoreilly These knowledge-sharing systems are increasingly real-time #CASBSSUMMIT
- 36. #CASBSSUMMIT @timoreilly Towards a Global Brain We are building a network-mediated global mind It is us, connected and augmented As we add more and more sensors to our devices, its knowledge of the world is getting richer #CASBSSUMMIT
- 37. #CASBSSUMMIT @timoreilly “global consciousness is that thing responsible for deciding that pots containing decaffeinated coffee should be orange” – Danny Hillis (via Jeff Bezos) – http://www.oreillynet.com/pub/a/network/2005/03/16/etech_3.html #CASBSSUMMIT
- 38. #CASBSSUMMIT Text @timoreilly “The message system used in the nervous system…is of an essentially statistical character.” -John von Neumann #CASBSSUMMIT
- 39. #CASBSSUMMIT Text @timoreilly “In a pulse-frequency-coded system, meaning is conveyed by the frequency at which pulses are transmitted between given locations - whether those locations are synapses within a brain or addresses on the World Wide Web…Information is being encoded (and operated upon) as continuous (and noise-tolerant) variables such as frequencies (of connection or occurrence), and the topology of what connects where, with location being increasingly defined by a fault- tolerant template rather than by an unforgiving numerical address. Pulse-frequency coding for the Internet is one way to describe the working architecture of a search engine, and PageRank for neurons is one way to describe the working architecture of the brain.” #CASBSSUMMIT George Dyson
- 42. Text #CASBSSUMMIT @timoreilly The Industrial Internet How does our society change when our factories and devices are connected to the internet’s global brain? Jeff Immelt of GE at the Industrial Internet conference
- 45. #CASBSSUMMIT @timoreilly 2005: Seven Miles in Seven Hours #CASBSSUMMIT
- 46. #CASBSSUMMIT @timoreilly 2011: Hundreds of thousands of miles in ordinary traffic #CASBSSUMMIT
- 47. #CASBSSUMMIT @timoreilly “We don’t have better algorithms. We just have more data.” - Peter Norvig, Google #CASBSSUMMIT
- 48. #CASBSSUMMIT @timoreilly AI plus the recorded memory of augmented humans #CASBSSUMMIT
- 51. #CASBSSUMMIT @timoreilly The global brain is us, connected and augmented #CASBSSUMMIT
- 52. #CASBSSUMMIT @timoreilly Human-Computer Symbiosis “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.” – Licklider, J.C.R., "Man-Computer Symbiosis", IRE Transactions on Human Factors in Electronics, vol. HFE-1, 4- 11, Mar 1960. Eprint #CASBSSUMMIT
- 53. #CASBSSUMMIT @timoreilly Lessons from 21st Century Unicorns Still On the Edge of the Extraordinary #CASBSSUMMIT
- 54. #CASBSSUMMIT @timoreilly#CASBSSUMMIT Lesson #1: Integrate knowledge tools into real world situations and processes
- 55. #CASBSSUMMIT @timoreilly This Used to Be a Book #CASBSSUMMIT
- 58. #CASBSSUMMIT @timoreilly Look At Everything Uber or Lyft Does For Me Lets me call a car from anywhere Automatically tells available drivers where I am Lets me know how long it will be till my car arrives Lets me contact the driver by text or voice - anonymously Lets me pay without having to pull out my wallet Gives me a detailed receipt showing exactly where I went and how long it took - which lets me complain if the driver didn’t go the optimal route (and Uber gives refunds) Lets me rate my driver, and uses that rating to manage the quality of service #CASBSSUMMIT
- 59. #CASBSSUMMIT @timoreilly Knowledge is now embedded into applications and devices #CASBSSUMMIT
- 64. #CASBSSUMMIT @timoreilly These are all magical experiences because they bring knowledge to bear right at the point where you need it. #CASBSSUMMIT
- 65. #CASBSSUMMIT @timoreilly This is the key question How do we use the capabilities of our devices to build better human experiences? #CASBSSUMMIT
- 66. #CASBSSUMMIT @timoreilly#CASBSSUMMIT “Uber is a $3.5 billion lesson in building for how the world *should* work instead of optimizing for how the world *does* work” - Aaron Levie of Box.net
- 67. #CASBSSUMMIT @timoreilly#CASBSSUMMIT Lesson #2: These are systems made up of computers and humans working together
- 70. #CASBSSUMMIT @timoreilly “We know about all these new technologies. What we don’t know is how to organize ourselves to use them effectively.” - An IT executive at Fidelity, during Q&A after a talk I gave there in 2008 #CASBSSUMMIT
- 74. #VelocityConf @VelocityConf @timoreilly@conference @timoreilly
- 76. #CASBSSUMMIT @timoreilly Are New Ways of Organizing People #CASBSSUMMIT
- 77. #CASBSSUMMIT @timoreilly#CASBSSUMMIT Lesson #3: Give people super powers
- 78. #CASBSSUMMIT @timoreilly Our Phones Used to Be the Tool of Superheroes #CASBSSUMMIT Dick Tracy: 1946 Star Trek: 1964
- 79. #CASBSSUMMIT @timoreilly An Everyday Modern Superpower #CASBSSUMMIT
- 80. #CASBSSUMMIT @timoreilly Not just consumers. Workers. #CASBSSUMMIT
- 82. #CASBSSUMMIT @timoreilly The Uber or Lyft Driver is an Augmented Worker #CASBSSUMMIT
- 85. #CASBSSUMMIT @timoreilly In the “experience economy” of the future, we need great experiences for workers, not just for consumers #CASBSSUMMIT
- 91. #CASBSSUMMIT @timoreilly Work, not Jobs #CASBSSUMMIT
- 92. What we fight with is so small. And when we win, it makes us small. This is how we grow: by being defeated, decisively, by constantly greater beings. (Paraphrase of “The Man Watching,” by Rainer Maria Rilke)
- 95. Some of the grand challenges we face • Rebuilding the infrastructure by which we deliver water, power, and goods. • 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. “The people will rise up before the robots do.” • Climate change. • Displaced people. How could we use technology to create the infrastructure for whole new cities, factories, and farms, where they could be settlers, not refugees?
- 96. Text #CASBSSUMMIT @timoreilly “Technology is the solution to human problems. We won’t run out of work till we run out of problems.” Nick Hanauer
- 97. Text #CASBSSUMMIT @timoreilly Work on stuff that matters.
Editor's Notes
- Four or five years ago, I was at dinner with Reid Hoffman, the founder and chairman of LinkedIn, and Senator Sheldon Whitehouse of Rhode Island. In the course of the conversation, I remarked, “We need a Moore’s Law for healthcare.” The Senator asked, “What’s Moore’s Law?” Reid’s answer was classic. “You have to understand, Senator, that in Washington, you assume that every year, things will cost more and do less. In Silicon Valley, we assume that every year, things will cost less and do more.”
- Of course, Moore’s Law is that famous doubling of chip density every 18 months that has enabled the computing revolution, that, as everyone says, means that your watch has more computing power than we used to get to the moon in 1969.
- Oh, wait. That’s supposed to be a cheap watch, not an Apple Watch. The Apple watch has WAY more computing power than we used to get to the moon.
- Moore’s Law is also responsible from the remarkable evolution in demand for computing. "I've seen no need for more than five computers in the whole world." -Thomas Watson, IBM, 1943. This photo was from considerably later (from an ad from the System 360 introduction in 1965.) Obviously, he had changed his tune by then.
- Moore’s Law has been responsible for a cascade of miracles.
- It has given us great powers.
- Are we using them wisely?
- A few weeks ago, I published a piece on Medium called “We’ve Got This Whole Unicorn Thing All Wrong.” https://medium.com/the-wtf-economy/we-ve-got-this-whole-unicorn-thing-all-wrong-3f3d108cc71d I wanted to take aim at the notion so popular in Silicon Valley these days that
- a unicorn is a startup with a valuation of at least a billion dollars.
- Crunchbase is even keeping a “leaderboard” of Unicorns. http://techcrunch.com/unicorn-leaderboard. There are now 149 of them. Some of them are really valuable, others may have bubble valuations. But I don’t think that this idea is wrong because we’re in a bubble. It’s just that valuation is a pretty sorry test for a real unicorn.
- I prefer Tom Stoppard’s definition, from his play Rosencrantz and Guildenstern are Dead. A man breaking his journey between one place and another at a third place of no name, character, population or significance, sees a unicorn cross his path and disappear. That in itself is startling, but there are precedents for mystical encounters of various kinds, or to be less extreme, a choice of persuasions to put it down to fancy; until — “My God,” says a second man, “I must be dreaming, I thought I saw a unicorn.” At which point, a dimension is added that makes the experience as alarming as it will ever be. A third witness, you understand, adds no further dimension but only spreads it thinner, and a fourth thinner still, and the more witnesses there are the thinner it gets and the more reasonable it becomesuntil it is as thin as reality, the name we give to the common experience.”“
- In other words, a unicorn is something that makes us say WTF?! Landing a man on the moon was a unicorn. There are still people that think it was a fake. But society has been reaping the spillover benefits of that Unicorn investment for the past 45 years. Let me show you a REAL unicorn!!!
- This is one of the original unicorns. Photo, Jameel Winter, https://www.flickr.com/photos/jameelwinter/5362037986/ Can you imagine the first human (or pre-human) who built a controlled fire? How amazed her companions were. Perhaps afraid at first. But soon warmed and fed by her boldness.
- Here are some more unicorns! The wheel. Stone blades. The plow!!! Old oxcart, photo by Cristina https://www.flickr.com/photos/cristinacards/512220671/ Stone age cutting tool https://www.flickr.com/photos/stephaniewatson/3470101545/ Thomas Jefferson’s “Moldboard of Least Resistance” http://www.monticello.org/site/plantation-and-slavery/moldboard-plow I like to include this, because Thomas Jefferson put his improved plow design into the public domain, so everyone could benefit from it
- Here’s another real unicorn: the book, and the library!!!! Widespread literacy completely transformed society. Photo: Tim O’Reilly, The old War Department Library, Eisenhower Executive Office Building, Washington D.C.
- I was reminded of this recently when riding the bus in San Francisco. I was sitting next to two old men. One saw me checking Google Maps to figure out where to get off, and asked what I was doing. The other jumped in eagerly, explaining that the blue dot followed our progress. I left them, one still in wonder, the other confident in the new reality, now demoing Google Maps on his phone to the other, who had never seen it. Photo by Quinn Dombrovski. https://www.flickr.com/photos/quinnanya/5307143490/
- I want to single out the GPS satellite from that last slide to indicate the cascading nature of unicorns. Unless this military program, a project started in 1973, had been opened up to civilian use, we wouldn’t be talking about such wonders as Google Maps (and all the other location-based smartphone apps), self-driving cars, and many other things, some still in the unicorn stage, so now as thin as reality. Satellites are part of the infrastructure of unicorns.
- Michael Schrage sums up that second characteristic of unicorns. They change the world, for good or ill. “Successful innovators don’t ask their customers to do something different. They ask them to become someone different…. When Apple television advertisements show iPhone users asking Siri questions or telling ‘her’ what to do, the company is doing far more than showing off the versatility of its voice-recognition, artificial intelligence interface. Siri’s company asks its customers to become the sort of people who wouldn’t think twice about talking to their phone as a sentient servant.” Michael Schrage, Who Do You Want Your Customers to Become
- The world wide web! Try to think back to before it existed. How different was everything we do? How different was our acquisition of knowledge? Here’s the web page for this event? How are we different because we can assume that if we don’t know something, it’s pretty easy to find out?
- Can you think back to a time when you couldn’t ask Google virtually any question, and find a reasonable answer in a few clicks?
- Or YouTube. Some years ago, in Italy, I had a marvelous sea bass baked in a salt crust. How do you cook this? YouTube gave me an instant tutorial. Imagine this: anyone…ANYONE…can upload a video FOR FREE…and anyone can watch it for free. All the world’s information made accessible. We’re not there yet, but massively further along than we were in the age of print.
- And of course, there’s wikipedia,
- It’s particularly striking to watch Wikipedia in action. An event happens - like the 2011 earthquake and tsunami in Japan. The initial wikipedia page appeared only a few minutes after the quake, and before the tsunami had hit.
- As the events unfolded, and more information became available, the page evolved, through updates provided by thousands of people.
- Resulting in an impressively complex and complete entry. This is not only an advance in human knowledge, it’s a real advance in tools for human cooperation in producing that knowledge.
- Consider Twitter, the real time news feed. The other night, even though I don’t really follow baseball, I got the emotional play by play from dozens of friends. And when true breaking news happens, it can spread around the world in seconds.
- Or consider real time traffic information. When you use Google Maps these days, your route is influenced by real-time traffic data. In this case, you can see that traffic from Oakland to San Francisco is really backed up on the Bay Bridge itself. There’s no really good alternative.
- But on another day, when traffic was particularly bad on the approach to the bridge rather than the bridge itself
- Google automatically re-routed us to another route that is longer in miles but shorter in time. Google Maps is constantly learning from everyone who uses the service. We already knew about this shortcut, but usually don’t know when to take it. Now we do. My fiance had an even more remarkable experience when driving recently in Texas. She was using navigation, in an unfamiliar environment. She was told to get on a freeway and drive 9 miles. A mile into the route, the navigation app on her phone told her to get off at the next exit. She did, and saw from the exit ramp an accident up ahead. The app had re-routed her in real time. A huge part of “closing the loop” is learning from your users, paying attention to what they do and responding to it. I’ve often said that one of the key competencies of web applications has got to be “harnessing collective intelligence.” Sensors let Google and Uber do this in real time, but there are lots of other ways you can do this.
- That experience my fiance had was made possible by Waze, acquired recently by Google. Again, internet enabled smartphones, building a real time database... I particularly love how their home page emphasizes the role of people in building the collective database. This notion of collective intelligence has been my theme song since the Web 2.0 days. And pretty early on, I started saying that in the future (that is, now), those collective intelligence applications would be driven by sensors. Or even better, humans and sensors working in concert! Waze drivers report incidents, but their phones report traffic speed and location!
- The google vehicle is only the latest of a long series of developments that show how we are augmenting ourselves and connecting ourselves into something bigger. We are building a network-mediated global mind. It is not the “skynet” of the Terminator movies. It is us, augmented This picture is a routing map of the internet. It’s striking how much it looks like a map of the synapses in a human brain. It’s nowhere near as dense yet, but the imagery is suggestive. But there’s a lot more here than just imagery. The global brain is a human-computer symbiosis.
- At our Emerging Technology Conference in 2005, Amazon CEO Jeff Bezos recounted a conversation he’d had with computer scientist Danny Hillis, in which Danny said [quote above]. Now this is nothing new. Speech, the written word, printed books and newspapers, the telephone, radio and television, and now the Internet, are all technologies for passing knowledge from mind to mind.
- At the very earliest stage of modern computing, computer scientists were thinking about parallels between the computer and the brain.
- George Dyson, the author of that marvelous book about von Neumann and the work at the Institute for Advanced Study, wrote further about these parallels. He wrote: “In a pulse-frequency-coded system, meaning is conveyed by the frequency at which pulses are transmitted between given locations - whether those locations are synapses within a brain or addresses on the World Wide Web…Information is being encoded (and operated upon) as continuous (and noise-tolerant) variables such as frequencies (of connection or occurrence), and the topology of what connects where, with location being increasingly defined by a fault-tolerant template rather than by an unforgiving numerical address. Pulse-frequency coding for the Internet is one way to describe the working architecture of a search engine, and PageRank for neurons is one way to describe the working architecture of the brain.”
- The Global Brain is now starting to make choices about what kind of content to produce. Every media site is now constantly responding to feedback signals from its audience, grooving deeper pathways of attention to some things, and some kinds of things. But we are also starting to make conscious choices, as when people collectively decide to fund a creative project on Kickstarter.
- Kickstarter and other crowdfunding sites are the closest we’ve come yet to the society of abundance that Cory Doctorow described in his first novel, Down and Out in the Magic Kingdom. It takes place in a world in which nanotechnology has led to physical abundance, and instead of a monetary economy, there’s an economy of attention, whose currency is called “whuffie,” and whose government is referred to as “the ad-hocracy.”
- Just to give you an even more exciting view of the future, I ask you to consider Jeff Immelt’s vision of the Industrial Internet? What happens when machines tell us when they need to be serviced, or have open data APIs so that we can study the data to compete to increase their efficiency? How does our society change when our factories and devices are connected to the internet’s global brain?
- My answer: every industry and every organization will have to transform itself in the next few years. The internet is not just something that affects media. It’s coming to every real-world service. I’ve organized a new event on this subject - how are AI, robotics, platforms for on-demand work, augmented reality, and other Unicorn technologies going to change the way we work, the way our companies are organized, and the kinds of problems we can solve? The event is being held Nov 12-13 at the Palace Hotel in San Francisco, and you’re all invited. There’s a special rate for startups and for nonprofits.
- The global brain is now on a collision course with the real world. Collective intelligence shows up in unexpected places, such as the Google self-driving car. This car is thought-provoking on a number of levels.
- You see, back in 2005, the car that won the DARPA Grand Challenge went seven miles in seven hours.
- Yet only six years later, Google announced a robotic car that had driven over a hundred thousand miles in ordinary traffic.
- It was surely that. But there’s another important factor that is easy to overlook. Google’s former chief scientist, Peter Norvig, says that the algorithms aren’t any better. Google just has more data. What kind of data?
- It turns out that the self-driving car was made possible by Google Streetview. Google had human drivers drive all those streets in cars that were taking pictures, and making very precise measurements of distances to everything. The autonomous vehicle is actually remembering the route that was driven by human drivers at some previous time. That “memory”, as recorded by the car’s electronic sensors, is stored in the cloud, and helps guide the car. As Peter pointed out to me, “picking a traffic light out of the field of view of a video camera is a hard AI problem. Figuring out if it’s red or green when you already know it’s there is trivial.”
- And then of course, there’s Waze
- And now Tesla is getting into the act, slipstreaming autonomous driving into the system as part of the every day driving experience rather than as a separate innovation. The car learns from its driver.
- So, in a surprising way, the self-driving cars are another unexpected example of Harnessing Collective Intelligence. It’s another miracle of computer-mediated human cooperation!. This is a thread that runs through all the great inventions of the web, from Google itself, Wikipedia, to social platforms like Twitter and Facebook. They are all technologies for harvesting and coordinating the products of thousands or even millions of minds, increasingly in close to real-time.
- JCR Licklider, the legendary DARPA program manager who funded the original development of TCP/IP, wrote about this idea in his 1960 paper entitled Man-Computer Symbiosis. He wrote:
- Just to give you an even more exciting view of the future, I ask you to consider Jeff Immelt’s vision of the Industrial Internet? What happens when machines tell us when they need to be serviced, or have open data APIs so that we can study the data to compete to increase their efficiency? GE’s data challenge with Kaggle.com is focused on precisely this problem. An improvement of 1% in the efficiency of jet engines would save airlines $3B per year.
- Now let’s talk about some Lessons from 21st Century Unicorns Still On the Edge of the Extraordinary
- So here’s my first lesson: The current wave of technology isn’t just “online” - it’s integrated into real world situations and processes.
- Think about it. The Google self-driving car used to be a book! First we put the book online - the universal atlas. We now embed the knowledge directly into a device that can use it without human intervention.
- This is the Unicorn that makes services like Uber possible.
- How many of you have used Uber or Lyft? If you have, you know how transformational it is to be able to know just how long it will take for a car to pick you up - to summon one whenever you need one, with the confidence that it will actually show up when and where you want it.
- Look at everything that Uber does for me. All knowledge-based: Lets me call a car from anywhere Automatically tells available drivers where I am Lets me know how long it will be till my car arrives Lets me contact the driver by text or voice - anonymously Lets me pay without having to pull out my wallet Gives me a detailed receipt showing exactly where I went and how long it took - which lets me complain if the driver didn’t go the optimal route (and Uber gives refunds) Lets me rate my driver, and uses that rating to manage the quality of service
- Knowledge is now embedded into applications and devices
- And with the advent of voice interfaces like Siri
- and Google now, we are talking to our devices and getting real world services and information back. One of the biggest changes in user expectation that technology will bring into our everyday lives in the next few years is going to be via “agents” like Siri and Google Now, which will bring predictive analytics to bear on routine tasks that we already depend on our computers for. Google Now routinely alerts me to leave early for work when traffic is bad,
- It is quite remarkable to be able to say to your phone “OK, Google Now, remind me to buy currants next time at Whole Foods” and have an alert show up the next time I am at the store!
- And when I’m traveling, automatically assembles everything from my boarding pass to alerts about the weather and even events at my destination.
- You can even tell Google Now to automatically remember where you parked your car. No action required beyond the additional setup. Sensors in your phone identify when you were driving, when you stopped, and when you began to walk. That you parked is an easy inference. And of course, your phone knew exactly where you were!
- These are all magical experiences because they bring knowledge to bear right at the point where you need it.
- But this is the key question. How do we use the capabilities of our devices to build better human experiences?
- box.net founder Aaron Levie put it perfectly in a tweet. “Uber is a $3.5 billion lesson in building for how the world should work instead of optimizing for how the world does work.” I believe their latest valuation was $40 billion, but you get the idea.
- That leads me to the whole topic of feedback loops. It isn’t just that this information is going mind to mind. We are increasingly taking this information and creating electronic feedback loops, which might include humans in different ways. Increasingly, technology is solving what we advertisers call “the Wanamaker problem” after 19th century department store magnate John Wanamaker, who said [quote above] What Google did with pay-per-click advertising was to solve the Wanamaker problem, by building a business model that only charged advertisers when consumers clicked on their ads, and harnessing collective intelligence to predict which of those ads would be most likely be clicked on.
- We’re now seeing this same idea spread to other areas of the economy. For example, these kinds of feedback loops enabled by data are part of what the US government is trying to do in healthcare with Accountable Care Organizations.
- Another really important lesson from consumer technology is that the systems we are building are not only for the benefit of people, but are in some fundamental ways still made of people...
- We’ve talked earlier about all the implicit data that people contribute to many modern apps, but on demand apps like Uber and Lyft, Postmates and Instacart literally have people inside of them.
- This has profound implications for the nature of the firms that we use to organize human labor.
- The challenge companies and other institutions face was well expressed by this quote from an IT executive at Fidelity investments, during a Q&A after a talk I gave there in 2008. “We know about all these new technologies. What we don’t know is how to organize ourselves to use them effectively.”
- Because of course, every new technology involves massive changes in how people are organized. From factory assembly lines....
- through more modern examples like open source software
- and the web itself,
- as well as new services like AirBnb
- Uber
- And even the Apple Store
- These are all based on new ways of using technology to organize people and the work that they do for each other. Think about how Uber and the Apple Store have both completely rethought the workflow of their respective industries - hailing a cab, and the retail store - by using the sensors and connectivity of smartphones to augment and empower the people using them. In a way, these services are actually made OF PEOPLE and computers in a new kind of symbiosis.
- So here’s my next lesson: Use technology and on-demand knowledge to give people super powers.
- This kind of superpowers. Our phones used to be the tool of superheroes.
- The first role of AIs is to give super-powers to humans. We don’t think of GPS-based navigation as “AI”, but it is a kind of limited Artificial or Augmented Intelligence. Think about it. Drop a smartphone enabled human in a strange city and they can still find their way around. (Of course, we could do this with a much earlier augmentation, the printed map, but the key characteristic of modern technology is that information access is much faster, and more complete. And the downside - we are much more dependent on it!)
- But it’s also important that we think about how to give superpowers to workers, not just to consumers.
- Think about GPS and Waze. They are a technological augmentation that makes virtually anyone almost as good as the superhuman black cabbies of London, who have passed “The Knowledge,” the most difficult exam in the world. OK, maybe only 80% as good in some respects, but better in others. But it’s super important to realize how these technologies cascade.
- The Uber or Lyft Driver is an Augmented Worker. These services wouldn’t be possible without the technology that upskills an occasional driver into someone who can find you where ever you are, and get you anywhere by the fastest route.
- This augmentation is spreading into other fields. IBM Watson is focusing on healthcare, providing doctors with deep knowledge of the relevant medical literature, and now even the ability to look at medical imaging and draw conclusions from it.
- Augmented reality technologies like Microsoft Hololens are aimed squarely at productivity and educational applications, versus earlier attempts focused solely on entertainment.
- But I want to highlight another aspect of our changing economy. In the “experience economy” of the future, we need great experiences for workers, not just for consumers
- This is the subject of another recent piece that I published on Medium called Workers in a World of Continuous Partial Employment. It addresses two ways to use algorithms to manage workers. In one, stores like Walmart, McDonalds, or the Gap, use scheduling programs and employee monitoring to control every aspect of workers’ lives. They set the algorithm to make sure that no one gets more than 29 hours, to avoid offering health benefits, and schedule people in short shifts to meet demand - all for the convenience of the company, not the worker. On-demand companies like Uber and Lyft, on the other hand, use a marketplace algorithm that lets workers show up whenever they want, and quit whenever they want, and offers to pay more if there aren’t enough of them to meet demand.
- But at the same time, there is trouble ahead. There was a good Atlantic article recently talking about technological unemployment. Its title refers to the fact that even though things tend to work out in the long run, there can be real pain and disruption in the short run. We need to come to grips with what kind of social safety net we need as this next technology wave hits. This is also a major theme at the conference.
- There are a lot of folks coming at this from the point of business disruption. This IBM report focuses on the risk to established businesses from startups “coming out of nowhere with a completely different business model.”
- There are folks like the Markle Foundation, with whom I worked for a year and a half on the Rework America report, who are making policy prescriptions on how to invest in the middle class and harness technology to make America more competitive.
- There are prescriptions for rewriting the rules to help address built in economic biases that cause income inequality.
- My own policy prescription: Think about work, not jobs.
- I’d like you to remember this advice from Rainer Maria Rilke’s poem, The Man Watching. He describes how Jacob and the other wrestlers of the Old Testament used to wrestle with angels. They had no hope of winning, but they were strengthened by the fight. Rilke goes on to say, “Winning does not tempt that man. What we fight with is so small, and when we win, it makes us small. What we want is to be defeated, decisively, by progressively greater beings.” So, relish your challenges, and keep picking big fights. We need to invest in the future.
- There’s another lesson here. When you think about Uber, it’s easy to see that it isn’t just a smartphone app. It’s an entire system, with different apps for passenger and driver, and a big data backend that does dispatch and billing. Healthcare is also a system. And what’s important to realize is that you can build great user experiences even when you don’t control every bit of the service. In fact, today’s web apps are almost all composed out of services that are sometimes run by others.
- I first heard this wonderful formulation of the essence of the technology future from Microsoft’s one-time open source software leader, Dave Stutz, when he retired from Microsoft in 2003. His parting advice is still worth reading.
- This “software above the level of a single device” is a SYSTEM with multiple users on multiple devices. And ultimately, it’s a system built on a big data back end! Some of that data is from sensors. Some of it is from stored memory (e.g. names and faces of driver and passenger, payment credentials). Some of it is calculated and reported in real time. And some of it (e.g. reputation) comes from explicit user input.
- It’s really important to understand that the internet of today is a vast web of data services you can build on. And of course that the applications of the future are not just multiplexing data services, they are multiplexing real world services!Don’t just think about building tools for managing data. Build actual data services that people can build on. Many of the components of the system, such as anonymized communications between you and the driver by text message or voice, or cashless billing, are made possible by third party providers (in this case Twilio and Braintree) The internet really is becoming an “operating system”, as I first claimed nearly fifteen years ago. Use its capabilities! Mapping, identity, payment are only a few of the many things that we can now take for granted when building online services. But Uber is a great example of how to assemble these into more than the sum of their parts. Don’t build everything from scratch. There are so many useful services available by API.
- By contrast, even the simplest forms of interoperability still seem to be an enormous challenge in healthcare. We’ve made great progress in sharing digital medical records, with big incentives from the US Federal government driving a lot of change. But in general, the state of composable services in healthcare is pretty miserable. There’s a lot of opportunity here for entrepreneurs.
- Another way to think about Uber and data is that it is using data to “close the loop.” You no longer call a cab, and just hope. Drivers no longer just cruise the streets looking for passengers. Information bridges the gap, and makes the whole system more efficient. Uber uses data to close the loop and take the uncertainty out of the experience.
- I picked up this framing from investor Chris Sacca, who who was an early investor in Uber, and before that used to run special projects for Google. He once remarked “What I learned...”
- One recent example that shows Uber doing this was their recent 25% price cut, formally expressed as a 3-month experiment. If prices were lower, would more people ride Uber, abandoning their cars and increasing utilization of the service, thus making more money for Uber and its drivers even as passengers pay less?
- When I see things like “the Uber for dry cleaning”, a small part of me dies. Really? That’s the best we can do?
- I’m much more interested in the Uber of healthcare, the Waze for energy usage.
- Here are some of the grand challenges we face. Rebuilding the infrastructure by which we deliver water, power, and goods. 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. “The people will rise up before the robots do.” Climate change. Displaced people. How could we use technology to create the infrastructure for whole new cities, factories, and farms, where they could be settlers, not refugees?
- Nick Hanauer, who is one of the speakers at my event, put it best. he said: “Technology is the solution to human problems. We won’t run out of work till we run out of problems.” Some of the other folks referenced in this talk are also speakers. Jeff Immelt, Logan Green of Lyft, Satya Nadella of Microsoft, Felicia Wong from the Roosevelt Institute, which published the Rewriting the Rules report, Zoe Baird of Markle, Sebastian Thrun, who kicked off the whole self-driving car thing. See the full roster here: http://conferences.oreilly.com/next-economy/public/content/speakers
- So, in the end, what we need to do to make more unicorns, applying knowledge to change the world, is to work on stuff that matters. Thank you very much.
- This kind of thinking is expressed very well in books like The Lean Startup by Eric Ries. Eric spoke earlier today here at SxSW.
- One of the key ideas of the Lean Startup is of the “Minimum Viable Product”, which Eric Ries defines as “that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.” And it really is at the core of most modern startups, who view their product as an ongoing series of experiments. These products are really produced through what is called “continuous deployment”, in which a series of minimum viable products are deployed in sequence.
- We’ve taken this for granted in web applications. But now, with Internet of Things applications powered by big data back ends, Lean Startup principles apply to every real world service!
- One obvious area is in personalized medicine, which requires new kinds of diagnostic feedback loops. Pascale Witz of GE Medical Diagnostics explained how “Only 1% of healthcare spend now goes to diagnosis. We need to shift from the idea that you do diagnosis at the start, followed by treatment, to a cycle of diagnosis, treatment, diagnosis...as we explore what works.”
- I wrote a paper a few years ago about the increasing role of big data and feedback loops in healthcare. I described how healthcare is now solving what advertisers call “the Wanamaker problem” after 19th century department store magnate John Wanamaker, who said “Half the money I spend on advertising is wasted; the trouble is I don't know which half.” What Google did with pay-per-click advertising was to solve the Wanamaker problem, by building a business model that only charged advertisers when consumers clicked on their ads, and harnessing collective intelligence to predict which of those ads would be most likely be clicked on. That’s what we’re now doing with data for health - genetics and data from various kinds of sensors can be used to provide smarter care, and public health statistics and models can be used to manage better usage and cost controls.
- Think about what Google did with advertising, figuring out how to predict what ads people would click on. They close the loop in a million small ways, measuring what people link to, what they click on, how long it is before they come back to the search (were they satisfied?) in order to deliver better search results. We will want to return to this topic when we start thinking about government services. How many times do citizen requests to government go into a black hole? How could things be better?
- And in health care - new services like 23andMe
- and PatientsLikeMe are also creative new ways of collecting data from massive numbers of people, and making it possible to extract insight, and eventually fulfill the promise of personalized medicine. What a shame that our regulatory system is working hard to hold back a service like 23AndMe! It’s quite clear that we need some fresh thinking on healthcare data and privacy. Most people are quite willing to share their health data - what they are worried about is adverse selection by insurers and employers! Instead of regulating to prevent these abuses, we try to keep the information secret. That’s not the right approach any more!
- Uber collects information automatically from the phone’s sensors, and packages up in a useful format to confirm the details of your trip. And that’s just the beginning.
- But that’s not all! Now, through integration with Expensify, you can not only have your receipt automatically turn into an expense report, if you’ve forwarded your flight details to Expensify, it can automatically have an Uber waiting for you when you arrive!!! This example highlights another key point: namely, that the new inputs to the systems we build are often internet data services, not just data from sensors. In the end, it’s not just local sensing that matters, its sensors connected to a big data back end.
- So what do I think when, weeks after my visit to the doctor, I get something like this in the mail. I may or may not have received a bill from my doctor or hospital in the meantime, but I don’t know whether to pay it until I get the insurance confirmation. Truly broken. Truly user hostile. So let’s compare the Uber experience with what we will soon expect from our healthcare experience.
- Look at everything that Uber does for me.
- In modern society, “the market” is another great engine of cooperation. It works not through any explicit coordination, but via what Adam Smith referred to as “the invisible hand” of overlapping self interest.
- Collective intelligence is not a new phenomenon. In a lot of ways, the fundamental notion of the “invisible hand” of the market is a notion of collective intelligence. As Leonard Reed outlined in his 1958 essay “I, Pencil” the global intelligence and coordination required to make something as simple as a pencil is beyond any one person. The sourcing of materials - the wood, the graphite - the manufacturing, the sales and distribution, are all magically coordinated without any central authority. What is new is the speed and scope of the knowledge transfer, the speed and scope of the coordination.
- By the way, these are the kinds of movements that we’re looking for at O’Reilly AlphaTech Ventures, our early stage venture firm. I know that you’re doing great things at Amazon, but I also know that some of you will one day move on. If you want to apply the principles I’ve outlined in this talk to build another great business that also just happens to make the world a better place, we’d love to hear from you. plans@oatv.com
- One of my best experiences with doing this was when I gave a talk at my Emerging Technologies Conference in 2008 entitled, “Why I love hackers.” They work on what is hard. I recited a poem by Rilke, the Man Watching, which talks about Jacob wrestling with an angel. He knew he couldn’t win, but came away strengthened from the fight. The poem ends with something like this: “What we fight with is so small, and when we win, it makes us small. What we want is to be defeated decisively by successively greater beings.”