Reinventing Societal Infrastructure with Technology

We don’t make most of the food we eat, we don’t grow it, anyway. We wear clothes other people make, we speak a language other people developed, we use a mathematics other people evolved and spent their lives building. I mean we’re constantly taking things. It’s a wonderful esctatic feeling to create something and put it into the pool of human experience and knowledge.” — Steve Jobs

1. The Summary

As a technology optimist I like to say, “what can be imagined technologically reasonably can be invented” is more true than not and more a matter of time and focus. Technology and new inventions have always shaped the human world, and have disrupted the way we live and work, and yet we are only at the beginning. Innovation in the areas of food, digitization, robotics, artificial intelligence, as a few examples, have the potential to achieve food abundance, reshape cities, knit humanity, and enhance human capability exponentially.

The big needs in society, food, health, housing, transportation, financial services, entertainment and more are being and will even more so be reinvented by technology in an “increasingly more accessible to all” way. We need to turbocharge our efforts to utilize technology to accelerate accessibility. Many of society’s GDP and business-related needs are being reinvented everyday in a truly innovative and non-institutional way. Seven hundred million (or so) people have the rich lifestyle, either in environment, energy, housing, healthcare, education, food, that seven billion people on this planet want. Technology is the necessary, though not sufficient, resource multiplier. It’s the only thing that can multiply resources. Technology will enable bridging this gap here, and the key word being “non-institutional” reinvention is not only powerful in increasing innovation, and but more importantly for accessibility.

The future and my admiration belongs to those dreamers who think of these unreasonable possibilities, who aren’t afraid of the high probability of failure, and who take, bold and, radical risks. They are willing to change the world by imagining what’s possible. So, what comes next for reinvention? Public transportation? Construction? Buildings? Healthcare? Food? Cities? Communications? Companionship? Financial system? Imagine the possible and take it from impossible to improbable to possible, but then again unlikely to plausible to probably to real! Individual entrepreneurs and their passion for a vision (and tons of good luck) give the improbable reality a shot. Now, many, even most, of these attempts will fail and the press will denigrate you for hubris, arrogance, fraud, naivety, and much more. Even so, it is these improbable attempts that will, when they occasionally squeak by the “existing reality, institutional noise (and fear)” will change the world (hopefully mostly for good). The future is not knowable, but it is inevitable and inventable so we need great entrepreneurs and technologists to invent the future.

If there is a 90 percent chance of failure on a transformative project then we have a 10 percent chance of transforming the world. That’s pretty great. If we have ten attempts (preferably a 100!) each at many different areas covered in this essay we will really change the world. Even if most attempts fail, change and innovation will be technology driven, non-institutional, let’s break the rules, radical kind of approach. And in this non-institutional way of doing things though less predictable is way more exciting and probably the main way we will get to getting seven billion people the kind of lifestyle they’d all want. Machines and systems can do medicine better than humans. But that’s just one of many. Or that most jobs will be replaced or fusion energy is possible in my lifetime or that AI can make work an option for most people who will work if they want to work, but not need to work because we will have sufficient abundance. Imagine the possible!

As Yogi Berra said “It’s tough to make predictions, especially about the future”, but if there is an answer this speculation is more likely to be right than any other single prediction I can think of. This reinvention will be chaotic, disruptive, unpredictable with many failed attempts, but failure won’t matter; the sparse successes will. The disruption will be temporarily painful to some as being disrupted is never fun. We have to get things right and meet society’s expectations of technology to help equality, diversity and more. New technologies also rock the world by reallocating power and wealth and accentuating inequality. Fortunately capitalism is by permission of democracy and the electorate will have the ability to rectify the inequalities if it isn’t self-regulated by the technologists. All these social factors will become urgent and critical to enable this transformation through democracy and the people who will be impacted. It’s impact in the less democratic societies is harder to predict.

2. We need large innovations!

As a technology optimist, I like to think “what can be imagined technologically can be invented” is more true than not, though on unpredictable timelines. Technology has always shaped the world and currently it is disrupting the way people work, live, and associate by providing radically new tools. New technologies are rewriting human aspirations. Innovations in the areas of clean energy, food technology, digitization, robotics, artificial intelligence, 3D-printing, transportation have the potential to mitigate climate change , achieve food abundance, reshape cities, knit humanity, and enhance human capability exponentially. But the future, as William Gibson wrote, isn’t evenly distributed. Some areas are making rapid progress while others need turbocharging! And though a technology trajectory may be established when it has a few percent penetration of the population, penetration itself may take a decade or more after the path gets cast!

Entrepreneurs are leveraging technology to reinvent the big needs in society, food, health, housing, transportation, financial services, entertainment, and more in a more democratic and accessible way though here again broad accessibility needs more turbocharging. The mechanism of invention by the “drivers of reinvention,” mostly capitalism and entrepreneurship, tends to focus the drivers on shorter term profit maximization (as it should be for them to survive and flourish) rather than societal good maximization, generally. The power of ideas driven often by technology and entrepreneurial energy are laying by the wayside institutional views about society’s providers. What seems most exciting is that many of society’s GDP and business-related needs are being reinvented everyday and all this is done in a very innovative and non-institutional way.

The big needs in society, food, health, housing, transportation, financial services, entertainment and more are being and will even more so be reinvented by technology in an “increasingly more accessible to all” way. We need to turbocharge our efforts to utilize technology to accelerate accessibility. Many of society’s GDP and business-related needs are being reinvented everyday in a truly innovative and non-institutional way. Non-institutional reinvention is a powerful means of increasing innovation, sustainable abundance, and eventually, accessibility. It all comes down to the fact institutions look back on the past to predict the future, instead of reinventing the futures the way entrepreneurs are able to. Such approach, perhaps optimistically, may provide us resources and time to address other pressing societal need, such as socio-emotional or environmental.

Approximately seven-hundred million people live the resource-rich lifestyle (environment-rich, energy-rich, housing-rich, health-care-rich, education-rich, food-rich ) that seven billion people on this planet want. There is a minimal level of basic needs that would make wealth secondary for many if not most people, I believe, and they will focus on other pleasures/passions, goals, interests, etc. I assume that to be roughly 90% percentile level today, or level of the best off 700 million people on the planet. Can we get 7 billion people to that level of resource richness in education, housing, transportation, healthcare without resource shortages and planet destruction? Technology, innovation and invention are necessary, even if not sufficient by themselves, to make this happen. What we really need are dreamers who can imagine the impossible and make it happen. Instead of being pragmatic, such people ask “Why not?” and with their entrepreneurial energy try and make these dreams come true.

Technology is the necessary, though not sufficient, resource multiplier. It’s the principle thing that can multiply resources. We need a 10x in resource utilization multiplication without needing 10x in the number of doctors, the number of buildings, the number of cars. Recently, I looked at all major parts of the non-governmental GDP in the United States and asked “what couldn’t be reinvented?” Not by 5% better, 10% better, but by 100% better, 500%, even 1000% better. Technology will enable bridging this gap here, but the key word here is “non-institutional” reinvention which is not only powerful in increasing innovation, but equally importantly for accessibility.

The keys are individual entrepreneurs and their passion for a vision. No matter how ludicrous their idea might seem, they give the improbable a shot. Of course, one needs tons of good luck, and many, probably most, of these attempts will fail. The press and other critics will have a field day and denigrate them for hubris, arrogance, fraud, naivete, and worse. However, it is these improbable attempts that will, when they occasionally squeak by the “wall of existing reality and institutional noise,” , disbelief, resistance fear and finally competition” will change the world (hopefully mostly for good). The future is not knowable, but it is inevitable and inventable so we need great entrepreneurs and technologists to invent the future they (and we) want. Not all changes are positive, but even in worst cases, there’s room to iterate to solutions. This iteration process and fits and starts are part and parcel of most large innovations.

The future and my admiration belongs to those dreamers and “possibilities” who think of these unreasonable possibilities, who aren’t afraid of the high probability of failure, and who take, bold and, radical risks. They are willing to change the world by imagining what’s possible. So, what comes next for reinvention? Public transportation? Construction? Buildings? Healthcare? Food? Cities? Communications? Companionship? Financial system? Imagine the possible and take it from impossible to improbable to possible to probably to real! Individual entrepreneurs and their passion for a vision (and tons of good luck and high accompaniment of failures) give the improbable reality a shot. Now, many, even most, of these attempts will fail and the press will denigrate the entrepreneurs for hubris, arrogance, fraud, naivety, and much more.

In twenty years when we look back at the pundits, reports, studies, and consultants we will find them to be largely wrong about the future of societal change. I shiver every time I see a UN Report, a McKinsey report, or an econometric projection going beyond the span of five years, especially coming from those pundits who have never done much themselves except pontificate. Instead of networking and all of the talk at Davos, for example, which that has little effect and a lot of retrospective predictors and extrapolation of the past, it’s much better to do and build The future is not knowable, but it is “inventable” and inevitable and discoverable through iterative learning and trial and error. Therefore, great entrepreneurs and technologists, please invent the future you want! The skeptics never did the impossible with their focus on why things won’t work. Optimists attempt more, fail much more, and achieve more.

3. It’s almost always the entrepreneurs, not institutions, that drive big innovations

Let’s take a quick look at things not-imaginable by the institutional view. All you need to do is look back to 1995 and imagine the Internet upending telecom and all that has happened since. AT&T Wireless was sold to Cingular (formed only in 2000) for $40 billion in 2004 (the technical details were more complex — later on in 2005, SBC Communications Inc. acquires AT&T Corp., becomes AT&T Inc. and then in 2006, AT&T Inc. and BellSouth Corp. merge) and Whatsapp was sold for half the price to Facebook a decade later. Why? AT&T was slow to adapt to cellular and the Internet. In fact they insisted that TCP/IP, the core protocol of the Internet, was not appropriate for public networks and ATM was their technology of choice. Outsiders purchased the rest of AT&T during its decline and it ended up in the hands of SBC, the parent company that formed Cingular. Only the AT&T brand remains, and of course the remnant assets.

Why is non-institutional innovation so necessary? Looking back in the last twenty years, the Internet upended telecom (AT&T refused to adopt to the internet and cellular till much later), Amazon upended retail with a clear vision of changing choice, processes, and cost structure that Walmart could not imagine. Google upended libraries, advertising, media, and many undefined industries. Amazon, along with Netflix, Youtube, and others are upending Hollywood and television. Over the last decade, Netflix has reinvented TV/entertainment, and Facebook/Youtube/Twitter reinvented media and may even reinvent elections and politics! And speaking of elections, Trump reinvented political campaigns using Twitter as a destructive tool against a well-managed “proper” political campaign. Even institutional measurements of our goals like GDP are being upended. Google and Facebook’s success, in fact, reduces GDP as it makes previously valuable tasks free! Cellular is dominating landlines. The iPhone, barely existed ten years ago when the venerable Nokia and Motorola ruled the mobile phone world. Uber reinvented the limousine service and the taxi service, and it will likely drive changes to public transportation. AirBnB is starting to change hotels, or at least a subset of that market. Instagram and Google Photos invented or reinvented the way we take, manage, and share memories in our lives. What about many other examples like space (SpaceX), cars (Tesla), pharma (Genetech), etc? Why is non-institutional invention so necessary? Most people in business reduce the risk of failure to the point where the consequences of success are inconsequential on society, but they can make money for their shareholders as they are obligated to. My philosophy is different. I’d rather invest in something with a higher probability of failure if the consequences of success are consequential. There is as much profit and increased social impact to be gained here, although with a higher variability. As I like to say, my willingness to fail gives me the ability to succeed. That is the exact opposite of how incentives are usually set up in larger, non-founder led institutions. Structure, processes, key metrics, and compensation incentives at large institutions oftentimes have the opposite effect to the expected one and often actually fuel and attract risk aversion for true innovation. Without risk and its concomitant failure, large innovation is just the matter of luck.

You get the picture here. These industries were not reinvented by large corporations, but in fact the power of ideas driven by technological advances and entrepreneurial energy. Most people in business reduce the risk of failure to the point where the consequences of success are inconsequential on society (but they can make money for their shareholders which they are obligated to do). Instead, the ideas that change the way we live and work are the ones that originally have a sparser space of higher probability of failure, but the consequences of success are consequential. There is as much profit and increased social impact to be gained through higher variability. As I personally say, my willingness to fail gives me the ability to succeed and contribute in my small way in causing good change to happen. In my view, it is only improbables that are important, we just don’t know which improbable when it comes to large changes and innovations! Most experts and institutions assume improbable is unimportant (with only a few exceptions where true risk can be parlayed to someone else).

We have incumbents, institutions, consultants, and pundits predicting more of the same “extrapolation of the past to predict the future” worldview. Some are well meaning, while others are driven by personal or institutional self interest. They are authoritative and mostly wrong when it comes to large changes or big innovations. McKinsey reports and fancy speeches at Davos notwithstanding. There is a dissonance between them and technology entrepreneurs: The former believe improbable is not important, the latter think similarly of the status quo. Personally, I think mostly the improbables are important, but we just don’t know which one it is.

This is the exact opposite of how incentives are usually set up in larger, non-founder led institutions. We have incumbents, institutions, and pundits predicting more of the same “extrapolation of the past” to “predict the future” world view. They focus on incremental predictable progress from year to year. Most of their predictions are wrong when it comes to large changes or big innovations and their impact. I’d give you odds that few large innovations will come out of any institutional player.

It is only improbables that are important. Large institutions generally believe improbable is not important, while technology entrepreneurs believe the usual is not important. Improbable is what creates the next Facebook, Google, Apple, Uber, or Airbnb, Netflix, Square, Paypal driven, of course, by an entrepreneur’s vision of the unreasonable possibility. Luckily, most of these players I named are still driven by founder vision, and aren’t sensible in the way business school professors would teach their students. These founders ask “Why not?” and “Why not try it?” be it Alexa, AWS, space, driverless cars, global location maps, phones without keyboards. Big companies do help scale innovation and bring gobs of capital later when risk of a new phenomenon is low (the Tesla playing field for the next decade or so). But it’s the seeds — what Uber, Tesla, Google with Waymo and driverless cars will do to completely replace much of transportation, as an example, with a new style of public and private transportation (this was inconceivable even five years ago by anyone in automobile, transportation business or city planning and is still largely being ignored in city planning)? Can we today envision a 10x better hamburger supply chain?

Change happens but is not credible until after the fact. Retrospective predictability by pundits is common, but until large change happens one sees mostly skepticism. I have hence come to believe in the power of ideas driven by entrepreneurial energy by almost foolish, somewhat naive entrepreneurs, by those who didn’t know what could not be done. Almost no major change is driven by institutions that one would expect to have power to cause that change! Did Walmart innovate retail or Amazon? Did Boeing/Lockheed innovate space or SpaceX? Did GM innovate cars or Tesla and Waymo? Did Youtube/Netflix/Facebook/Twitter innovate media or NBC? Is there any area where a major innovation came from an institutional?

4. Beyond the entrepreneur, what does it take?

So imagine the possible in the many of the areas of interest and let’s imagine the axes and tools of innovation. The way I think about it is the greater the number of “axes” — that is the dimensions in which innovation is possible, and the better the tools for innovation, experimentation, and lower the cost of trials for ideas — the faster the rate of change. That means a bigger possibility of a surprise like an Amazon disrupting retail or Tesla and Google changing transportation with electric and driverless cars, respectively.

Computers and computation as a tool allow for innovation in practically any field, be it in biology, space exploration, or information technologies. That was compounded by networking (of people, computers, and things) through the Internet which allowed the lowly landline phone to morph into today’s mobile which, paradoxically, is mostly used for everything other than talking. The device, though, impacted so many areas of our life. This was unimaginable even two decades ago at the birth of the Internet and was still unclear even after its commercialization with the founding of Netscape in 1995.

So, what is in store for us for the next twenty years? It’s hard to forecast, but easier to speculate. It seems likely that 3D manufacturing, artificial intelligence, biology tools especially — new physics-based tools, biology fashions like CRISPR and it’s likely successors for precision biology and computational biology, along with traditional old standbys like increased computing and bandwidth will all form a soup which catalyzes many new ideas and reactions. Now, add to the soup the potential for new types of computing, like quantum computing, which might accelerate AI even beyond our wildest imagination. The possibilities become truly unpredictable. Here I speculate (I never claim to be able to predict anything) basing just on technology paths that seem plausible, even if they are improbable today. I don’t posit yet atomic level assembly of objects, but just using improvements in 3D-printing, voice communication, AI, and basic quantum simulations. I am not imagining here completely new axis that will surely happen like broad quantum computing, fusion energy, or molecular assembly. There are many axes of innovation that are opening up so the next decade or two look promising. I won’t mention all of them here. There are some I expect but seem too speculative even for me. Others, on the other hand, I haven’t dreamed off but are today being developed by smart people all over the world in research efforts.

To make it possible, you need new tools and technical breakthroughs, a visionary and persistent founder, and evangelizing market participants with a passion for the vision. They must understand where this vision is going, and they need to be convinced they need to come along and ultimately change, especially if it’s radical innovation. For instance, automotive companies had little appetite for electric vehicles. Nevertheless, Elon Musk had both the vision and the determination to create electric cars and gain adoption; that that allowed him to disrupt the automotive industry by building a better, more efficient car while paving the way for an autonomous future, as some would say. There’s also a difference between invention and socially effective innovation, and then scaling which the innovator may or may not be involved. For while it’s still not universally accepted, it has taken convincing the likes of government regulators, financial institutions, technology thought leaders, media, and the general public to change behavior and ways of doing what they were doing. As Mahatma Gandhi said, “First they ignore you, then they laugh at you, then they fight you, then you win.” Many institutions have business interests that will cause them to slow down these changes. There are also many pretend social change enrtepreneurs taking advantage of their “story” with little more than financial goals or hollow sincerity to the causes they profess. But the wheat comes with the chaff unfortunately.

There are macro trends, too. Marc Andreessen said “software eating the world” because it was the easiest way to describe what was happening. The same is happening with AI eating the world, as well as computational design, blockchain and 3D-printing. Some of the tools and axes of innovation defined below will end up being transformative, most likely this will be the case of AI, others will just be rapid facilitators. Older technologies, like mobile and Internet, will keep turbocharging these newer innovations.

5. Looking at the infrastructure of society, what can be reimagined and reinvented?

Let’s take a closer, albeit speculative, look at possible ways in which these revolutions fundamental to a better world imagined by the majority of us and the economists, might happen. While other definitions of “better worlds” are possible, that is something left for a different discussion.

Where could a single entrepreneur driven by passion and a vision enter the market with simple products and drive to much larger scale over twenty years or so? Remember that twenty years ago in 1997 Google didn’t exist, and neither did Facebook. Media had not felt the push of Facebook, Youtube, Twitter. Amazon was very nascent and not yet starting to reinvent retail. Apple was under traditional “proper management” struggling to survive, while Uber, AirBnB, Pinterest were not even glimmers. Phones were made by traditional institutions like Motorola and Nokia, the mobile phone as we know it did not exist, and the Motorola and Nokia phones were mostly used for “talking.” There was no “app for that”. India was still trying to scale only landlines!

I was personally ridiculed when I suggested then that the Internet should not be ATM protocols but rather TCP/IP. In fact, Juniper Networks was the only company committed to building TCP/IP Internet protocols for the public Internet (No, Cisco was building routers for the Internet but had bought an ATM protocol company that would be their public Internet network play). Going further back through my career, in 1985 the idea of a computer in every home was considered absurd, grandma using email in 1990 was thought ridiculous, and the Internet was a crazy idea and never going to be an important public network in 1995. AT&T assumed that 64 KBPS ISDN was all the data anyone needed.

What are the non-governmental components of GDP that can be re-imagined/reinvented with an entrepreneurial rather than a policy/legislative/regulatory approach?

Transportation and related city services

Health, disease diagnosis and management, drug discovery

Manufacturing, Construction, Buildings, building efficiency and cities

Food and Agriculture

Financial, insurance and legal services

Energy

Consumer consumption items, services, education, durable goods

Most of the non-governmental components of GDP can be re-imagined and reinvented with an entrepreneurial rather than a policy/legislative/regulatory approach (which will usually follow later) be it 1) Transportation and related city services 2) Health, disease diagnosis and management, drug discovery 3) Manufacturing, Construction, Buildings, building efficiency and cities 4) Food and Agriculture 5) Financial, insurance and legal services 6) Energy 7) Consumer consumption items, services, education, durable goods.

We’ll look at each of these individually, but suffice it to say that almost all the non-government components of GDP can be reinvented with hundreds of percentages change in their resource intensity, cost, quality, and accessibility — be it education, healthcare, transportation, housing, financial services, consumer products and services, and more!

Large change happens, but is not credible until after the fact. Retrospective predictability by pundits is common, but until large change happens one sees mostly skepticism, as witnessed by the number of electric cars forecast in 2010 or the political support for Trump forecast in early 2016. I have hence come to believe in the power of ideas driven by entrepreneurial energy by almost foolish, somewhat naive entrepreneurs, by those who didn’t know what could not be done. Most major change is not driven by institutions that one would expect to have power to cause that change! Skeptics never did the impossible! They are often right, but wrong when it matters the most.

6. The technology soup enabling societal innovations

Fundamental reinvention has never been more possible than it is today. There are a range of new recent technological axes of development that give me hope. Driver technology tools that are plausible and visible today and are feeding on each other and on other research include:

AI and large scale data capability

Robotics

Additive manufacturing / 3D printing

Biotechnology (“omic measurement”, CRISPR, gene synthesis, precision control of genes, pathways…)

Computational design, computational modelling/simulation for materials ot process to biology and more

Social connectivity and networking; distributed access

Software eating the world

Blockchain

Increasing research breakthroughs in all areas

Other new still fermenting ideas I have surely missed or underestimated (open for candidate suggestions)

Fundamental reinvention has never been more possible than it is today. There are a range of new recent technological axes of development that give me hope. Driver technologies that are plausible and visible today are listed above. The “older technologies” that will continue to be axes of innovation that continue to have impact and provide benefit include: software, computing and cloud computing, Internet, semiconductor technologies, financial instruments, sensors, cameras and mobile.

Artificial Intelligence

AI will, inevitably, change the structure of our society. This is a statement about exciting future technical developments, and an observation about what is mostly possible in the near-term , although has not yet achieved widespread adoption. The rate of change of new AI capability, the building block for changing businesses and human activity, is very rapidly expanding.

Fundamentally, we can now or soon will be able to achieve human-like (and occasionally super-human) performance on tasks that were, just a few years ago, regarded as completely out of reach for machines. Probably the greatest example is computer vision. It was stagnant for decades, but has made so much progress in the last years we can now have computers classify images and videos with super human performance, provided we have enough training data in the domain, be it face recognition or reading MRI images. The same is becoming true in recognizing human speech and even generating voice, or reading someone’s mood or mental health status from their voice in superhuman ways. Just thinking about machines with the capability to understand vision and recognizing voice by itself, will fundamentally change how we think of work in general and what our interface with machines will look like in the future.

That being said, there is likely an even greater progress possible near term. Currently, the best performing AI systems require huge amounts of data to train to human-like performance. However, work is underway to reduce this burden in various domains; often all is needed are humans being to feed just a few examples to guide the neural nets. This will enable us to apply AI to domains where little data exists or the data is hard to get for structural or legal reasons, greatly widening the applicability of AI in all business and societal processes.

Model-building of the world as humans do is another dimension of innovation, For example, an AI may be able to predict how much force would knock over a glass of water. AIs are also learning fast from the world of simulations and games. I suspect the Lego blocks of intelligence will expand from a few (names like CNN’s, RNN’s, GAN’s, to more recent additions like probabilistic programming, Bayes nets (redone), graph models, …. to all kinds of new capability hard to predict or name today) to many different types of intelligences capable of being combined to do unusual things; much like today’s lego blocks sets can enable building very complex structures compared to the original red and yellow blocks that allowed us to mostly build simplistic things.

It is not only the ability of AI to “judge” and recognize images and audio that is a driver here. We are now on the cusp of having AI generate images in a domain, at high resolution, and high quality that mimic art or any desired input distribution. The same now goes for music where we can create AI that can mimic and improvise play in any style. “Creativity” used to be one of the standard answers to the question of what defines humanity. Nonetheless, it looks increasingly doubtful that even that claim is irrefutable. One day, we might see a short film,generated solely by an AI or a top ten music hit that never had a human composer or a new art style generated by AI that appeals to humans

One last comment that should make us quite hopeful about the accessibility of these technologies is that most of the fundamental breakthroughs have been out in the open, published, and discussed publicly. Yes, AI talent is hard to come by today. At the same time, it is also one of the most popular areas of study these days and sooner or later this challenge is going to be overcome. Coupled with high-quality frameworks for AI research and deployment now being freely available as open source, rapid progress on both research and applications is at hand.

In a talk to the National Bureau of Economic Research on the “Economic Implications of AI,” I looked at the top twenty employment categories in the US and concluded most jobs in most of these categories would be eliminated or change substantially for humans. Technology will reallocate where and how people spend time and resources. We will have great abundance, growing productivity, and GDP but with increasing income disparity. Further, changes will be slow, almost imperceptible in terms of employment the first five or ten years, and take decades before going exponential in actual number of jobs impacted. But by the time the first 5 percent of jobs are impacted, the future will be inevitable.

Robotics:

The renewed interest in robotics is, to a large extent, similar to the renewed interest in AI. For a long time we had robots that were amazingly durable, amazingly precise, but fundamentally simply examples of good mechanical engineering and careful motor control. This was enough to solve manufacturing tasks in very structured environments where all parts have defined positions and the manufacturing line does not change rapidly. A core example here is the chassis production of cars which has little human involvement today. But no robot could replace a human in the sorting of eggs by size and grade, only human assembly line workers could do that. They were mostly programmed machines, but not rapidly and broadly learning machines.

The new path in robotics involves robots that can make decisions in a largely unstructured environment. Probably the most discussed example of this today are self-driving cars that have to make decisions in the real world and not in a defined, pre-planned environment. But there are other, equally broad implications on the horizon. A company struggling with automation due to dealing with soft materials and rapidly changing product mixes right now faces large costs of automation. However, the next generation robots might change this by being able to learn new tasks rapidly on little data and with no programming

The main driver for this is two-fold. One is straightforward: it is simply the availability of very low-cost, high-resolution sensors, in particular camera systems., microphones, ultrasonics, radar and other environmental acquisition technologies. The other boils down to the fact we can now interpret vision and 3D data by learning from examples instead of having to hand-code the rules. Reinforcement learning, learning from simulation, and understanding how to reduce the training samples required are the core elements of modern robotics. Adding general learning including concepts, concept hierarchies physics, and more will happen.

Those robots are a very different breed from the old and the trade-off space will be vastly different. Formerly, we got precision from adding tighter motor control or heavier arms.. This new class of robots have cheaper, lighter arms and still get the precision back by relying on visual servoing. In essence, it means the vision system is able to correct the robotic arm as it gets close to the object we wish to manipulate. A robot arm capable of doing human tasks should not weigh any more than a human arm does and then scale sub-linearly from there. This makes this next generation of robots cheaper, able to handle very flexible tasks, and quick to deal with environments that have been thought as impossible in robotics before. There will be many contributions to robotics, but AI learning systems will be a big factor.

From a societal and economic perspective this enables a completely new way of thinking about production lines. Proximity to the end-customer, thus, becomes more important than the availability of cheap labor for menial tasks in unstructured environments or the need for scale. This is especially true when combined with new technologies like 3D-printing. Custom, personalized, and local may become economically better in areas like producing jeans, sofas and beds or many types of fresh food.

Additive Manufacturing/3D printing

Additive manufacturing -in essence printing objects instead of manufacturing them traditionally — has already made inroads in multiple areas. It consists of a family of technologies that can manufacture polymer parts to high-density metal parts. Even composites are being 3D-printed. The current beachheads for those technologies have been largely in design and prototyping environments. This means shortening the design cycle as we can almost instantly have a prototype part; it has actually already become a standard feature for many industries.

This is, however, changing and with robotics. For instance, we are seeing a complete transformation of supply change and materials with one of our companies, Feetz, that’s reinventing how shoes are made. We are seeing more and more production parts made by additive manufacturing. Using these techniques to create performance critical parts that are not manufacturable with traditional methods is already becoming commonplace. Examples here include turbine parts, rocket engine components, and implants. This acts as the key catalyst to move the industry from using the technology for prototyping to a manufacturing regime. We climb down the cost curve as an ever greater number of parts that used to be hard to customize, not buildable at all, or consisted of multiple assemblies, can now be built with these machines.

We are now tackling some of the fundamental limitations of the technology, such as cost per part, materials we can use, removal or avoidance of necessary support structures to make this family of technologies even more widely applicable. These technologies, in turn, are also changing conventional wisdom like benefits of scale, locations, and schedules for manufacturing, supply chains, spare parts, or maintenance. Do we need to make shoes in China for US consumption or can they be 3D-printed locally and customized to each foot? Do we need to stock every spare part for a Boeing 727 in every airport in the world? Should it take six months to get a sofa manufactured in China only to see it does not fit in your small studio apartment?

This has significant consequences for the way we think about complexity in our design. If complexity becomes in essence free, that is not tied to manufacturing steps, our possible design space explodes. In particular, if manufacturing complexity is not the bottleneck or cost factor anymore, designing structures will be the new bottleneck. Instead of designing by hand, we will likely create them by specifying the input loads and tasks fed into AI systems. Optimization software will process the data to create structures looking a lot more organically than now and producible ONLY by additive manufacturing. The technologies of robotics, AI, 3D printing, will feed on each other making exponential change on products, materials, and supply chains.

Computational Design / Learning Physics

In design of objects we have long used computer tools from EDA tools for the electronics industry to CAD tools for physical objects and from simulations for verification of performance of the designed objects.

We are now moving into a regime where the actual act of designing a structure is now becoming part of the duty of our tools and humans act more as a trainer, judge and specifier of external conditions. And even those roles may change to just specifying goals given constraints and preferences. Let’s take designing a structure for an aircraft. It has to fulfill various structural loads and remain as light as possible at the same time. We will in the coming decades let the algorithms decide the design to minimize weight and specify the external loads. This has been possible before via optimization procedures, but unlike before, we can “learn” from past successful designs and guide the search space and be much less dependent on human guidance or judgement.

In no place is this more apparent than in the design of drug targets. Instead of running quantum simulations to understand the binding of molecules to targets, a slow and costly procedure, at systems in the future be able to learn from past binding data to automatically come up with novel designs that might be good candidates for a new drug. A general principle behind it being that even though we often understand the underlying physics of what we are trying to design, the exploration process is too costly to run by brute force exploration of the design space. Learning from past successful designs, be they molecules designed for a target, physical objects, or different layouts on a circuit board, allows us to meaningfully change the performance of these objects. We may soon see a new range of computationally-designed materials beyond copper, steel, and aluminium alloys for everything, from medical devices to body organs to your car and sofa. A decade ago computers learnt to beat humans at chess by brute force computation. Soon systems like AlphaGo Zero will use “intuition” to do the same to make designs, drugs, and materials.

Biotechnology/CRISPR

Innovations in biotechnology might be grouped into three different levels: measurement, understanding/modeling, and modification. Our ability to measure biomolecules at continually higher resolution and in greater bandwidth is enabling steady improvements of our measurements of individual organisms (like humans), but also groups of organisms (from the microbiome of a human gut to the complex commensal relationships of organisms in a coral reef or in a patch of forest floor). This amount of data acquisition these days is extremely complex and high-dimensional. Currently, only AI is able to create accurate predictive models and, thus, an efficient form of understanding the data. This, however, requires considerable advances in data storage and analytics. The third element is in the increasingly advanced and precise toolkit being developed for editing biology down to a single molecule. Tools like the Cas family of CRISPR associated proteins are enabling very specific, rapid editing of DNA, the blueprint for most of what we consider living things. These capabilities will dramatically improve and become more diverse over time.

George Church has likened studying the diversity and complexity of biology to an advanced alien civilization leaving all its technology in our backyard for us to analyze. Biology has been able to create the machinery to very efficiently convert wide ranges of energy from one form to another,. It is able to harness that energy into vast abilities to transmute forms of matter. This alchemy of biology still produces the vast majority of materials of interest to humanity. We are developing a deep control of the machinery of biology, which is just as crucial as the initial domestication of plants and animals thousands of years ago. Synthetic biology will impact chemicals and materials, energy, and human and animal editing, which will have great economic and societal implications. These and future capabilities will give us god-like powers (with its benefits and danger) over the next decade or two.

Food products and pharmaceuticals are largely the result of biochemical processes. Basic components of our environment, like the oxygen we require to breathe, are the result of biological processes. Changing these systems with tools like a shovel or hammer would be impossible. However, we are gaining the potential to have molecular level control of all living things, giving us powerful new ways of combating issues like food security or climate change.

If human history has been a push to control of the world for human good, then we are at the start a major new type of development. This process started with the quest for control over environmental exposure by development of fire, buildings, and clothing; extending to gaining control over supply of food and materials by domestication of plants and animals, efficient agriculture, creating mining and mineral extraction and the industrial revolution; and then recently control over information and data through the development of language and literacy to modern methods of data transmission, storage, and analysis. For the first time, we are gaining control over modifying ourselves directly Biohackers are already CRISPR hacking their own bodies. It will become systematic starting with fixing genetic defects in babies.

The tools for editing DNA are only the first step in modifying the physiology of an adult living being. In order to do this, we have to target the cells and tissues we want to address specifically. Nevertheless, technological development in that direction is ongoing. We are also developing the ability to modify cells that can be introduced into the body with new genetics and designed molecular biochemistry or to modify and edit embryos prior to their implantation. We are learning to genetically modify a pig embryo to produce human compatible organs for transplantation, or 3D print organs. We can change our body composition, but we may also decide to edit ourselves from the very start. In terms of editing human embryos directly, we as a society need to determine how we want to use this technology; there are clearly many opportunities for improving health and wellness, and some large dangers as well.

One of the more promising avenues is to capture human knowledge in biomedicine, reconcile inconsistencies automatically, and be able to simulate at the molecular level every pathway and all omics in the body computationally. This could lead to true understanding of normal and deviations from normal, the usual definition of disease. Drugs and their effects on a particular person could be modeled and dosages calculated. The possibilities for human or animal biology management are exciting though impossible to specifically predict if we develop this capability.

Social Networking

Social networking has changed our access and rate in which we access communication and how we collaborate. It has spurred new ideas and influenced the way we think about democracy. It has democratized information in a way that enhances education and new ideas. Twitter, as an example, has changed how we get news. It has influenced the end of regimes, and depending on the point of view, has had a positive or negative effect on politics. Social networking is a powerful tool that has allowed people to have a voice and connect globally. And it’s not all just cat pictures and status updates. Slack has brought social networking to industries and enterprises. It enabled more voices to collaborate and be heard, and helped making processes and businesses more efficient.

Like anything powerful, social networks can have negative and positive implications on the world. They are undoubtedly a powerful tool to both spur innovative ideas and, influence them to get traction. They allow us to aggregate opinion, to get feedback for product designs and product reviews, and to have new channels of democracy (and it’s subterfuge, as well as fake news). Scientific social networks accelerate communication and collaboration and increase the rate of progress or discussion. There are many ways in which industrial progress is leveraging these social tools. This tool is speeding the pace of change and innovation across key areas like education, health, and government. AI systems added to social networks and messaging will change them materially again. I am continuously optimistic this will be for the better.

Blockchain

A marriage of the Internet and cryptography created the blockchain which has given rise to the distributed ledger, new payment systems, and cryptocurrencies like Bitcoin. This will be critical axes of innovation that will enable new businesses and paradigms, whether it be smart contracts to rethinking workflows, food traceability, medical records, and other mission critical data tools. Blockchain will be a new way to use technology to rethink complete industries like the financial system or being full transparency and tracing into supply chains. When Haiti was hit by the hurricane, many or most of the records were lost. This could have been easily avoided. Blockchain could allow people, businesses, and governments to rethink how they are storing and using their data, such as documents, information, payments. Keep in mind there are dangers of misuse, volatility, diversion into fraud and illicit use as dangers.

Old tools that still have impact…

The “older technologies will continue to be axes of innovation that continue to have impact and provide benefit include (but are not limited to):Software

Computing and cloud computing

Internet

Sensors and cameras

Mobile

Biology, chemistry, and physics tools

The way I think about it is the greater the number of axes (dimensions in which innovation is possible) and the better the tools for innovation, experimentation, and lower the cost of trials for ideas, the faster the rate of chance and the more possibility of a surprise like Amazon or Tesla or Google or Instagram or Paypal or Uber. Combinations of technology can be exponential and autocatalytic by accelerating each other.

It’s hard to forecast, but somewhat easier to speculate what might be new tools for the next decade. Again though, the best reinvention is seemingly unimaginable. All the “known” axes today form a soup which catalyzes many new ideas and reactions. Add the potential for new types of computing like quantum or AI hardware, which might accelerate computation and AI even beyond our imagination today, are truly unpredictable. New axes will surely happen, perhaps with sophisticated broad quantum-computing, fusion energy, or molecular assembly. Computation remains a fundamentally underutilized resource in physics, chemistry, biology, simulations, materials, and much more in society.

7. Reinventing Transportation

Key drivers: Driverless technology, electric cars, reimagined public transportation, batteries, dedicated self driving public transit lanes, mobile hailing and scheduling solutions.

Transportation Trends:

From public transportation to flying cars… it can all be reinvented. When you take the cost structure of an Uber, multiply its usage by 5–10X in any given city, assume cars that are used 100,000–200,000 miles per year (amortized as a few cents per passenger mile serviced over its million mile designed life) instead of 12,000 and as a result operating costs become much more important than capital costs. Thus, electric cars become much more cost effective. Interest and maintenance costs decline because of scale and the cost of the driver disappears because of driverless technology. At the moment, the driver is the largest part of a Uber or taxi service and would approach a few cents per passenger mile., Scheduling, hailing, and other operations are automated through intelligent AI and mobile devices. It becomes hard to see how owning a car makes sense except for a small fraction of the population. For instance, we could have public transportation in smart cities, enabled by clever legislation, point to point on demand, that is cheaper than today’s fixed route, fixed schedule transit services run by most cities enabled by electric cars/pods and driverless technology.

A little pod that seldom crashes, with streets dedicated to it should not cost more than a dollar a ride. Batteries and electricity would be the main cost per passenger mile. These pods, given the service time, will need to be electric, which incidentally lowers carbon per passenger mile for cities that are carbon sensitive about their electric supply. It also means higher reliability because of fewer moving parts.

Because these pods will be be less prone to crashing, they will be lighter and cheaper, which will allow them to go much further on a kilowatt hour of electricity, reducing battery costs. A light bicycle is 17 pounds. Would a four passenger pod that can be frequently recharged need more than a few hundred pounds to carry 1,000 pounds of four people? Electricity cost would be very small at 50–100 pounds of vehicle weight per person for each mile. One could summon specialty pods for wheelchairs or other specialty loads. For forward-looking cities, we may see these as anywhere to anywhere on demand public transportation for a few dollars or maybe near free!

The Ubers of the world and the Volkswagen’s of the world may be marginalized. Cars will remain a thing for car enthusiasts. However, besides special use cases for the vast percentage of passenger miles cars, trains and public transportation will be reinvented. All that dramatically reduces cost for cities and citizens. And then there will be flying taxis. So, lots of tools allowing for innovation and transportation and its implications for cities. Just as cars changed cities, electric and driverless technology could change them again, especially if applied to public transportation.

Parking lots and spaces could be replaced by parks or housing, or commuter lanes. Commute distances may expand, housing may get cheaper, and environmental pollution decline. Driverless car technology may kill the combustion engine and set the oil industry in permanent decline. Cities could be redesigned to work differently, especially if one adds in improved communications technology. The number of cars could decline five fold or more. The need for natural resources like steel, rubber and plastics decline concomitantly.

Parking lots and spaces could be replaced by parks or housing, commuter lanes by driverless lanes or streets, commute distances may expand, housing may get cheaper and environmental pollution decline. One may need to accommodate new factors such as pickup and dropoff spots on streets. Driverless car technology may kill the combustion engine and set the oil industry in permanent decline. Cities could be redesigned to work differently, especially if one adds communications technology and space efficiency and reuse paradigms. And the number of cars could decline by 5X or more and the need to natural resources like steel, rubber and plastics decline concomitantly.

Automobiles as a large part of GDP could change dramatically. Even trains could become autonomous pods on roads or tracks, dispatched on demand, instead of being enormous beasts carrying 100,000 pound cabins (that go empty much of the day) that only make economic and climate sense when fully loaded and whose schedule is limited by when they can carry a breakeven number of passengers. A key metric might be average pounds and costs of material required to carry a human. Ideally, we start with key arteries. Let’s take the airport to the strip section of Las Vegas and reimagine it as a driverless-only free service. Then, let the service spread spread organically from there, with more reserved streets to offer anywhere to anywhere public transportation on demand which could be cheaper than today’s transit tickets and more economical for the city. More and more of the city streets might become driverless and public utility only, much like today’s “reserved lanes” in a city like San Francisco. Cities will have increasing incentive to make more of the publicly paid for streets driverless only for public “transport pods” only.

If residents of a city get closer to their destination, they might even walk the last half mile, which could have beneficial influence on their health. Incidentally, with the increasing number of driverless pods, the “reach of the city” or distance possible within a certain fixed commute time will increase. Thus, it can ease housing shortages and improve housing affordability. Parking land would be freed up for parks and low-cost housing. The city without automobiles would be a different animal. To understand what drives cities check out A Physicist Solves the City!

The city without automobiles (mostly in most but not all places) would be a different animal. With 80% fewer resources we could have dramatically more transport capacity, speed, and convenience. The pattern of adoption is not yet clear. The rate of adoption will depend upon how the technology is targeted at social solutions. It might happen first on elder care communities, with free taxi service to avoid the disadvantages of having average age 70 drivers and enable everyone in age restricted communities to have more freedom.

On the other hand, it may be an incentive to make affordable housing more prevalent by guaranteeing a certain commute time with free service in dedicated lanes from certain communities to work centers? Or it may be used in order to relieve traffic congestion in cities like inner London; offering near point to point convenient and affordable service can render private transportation unnecessary. Another likely development is to relieve truck drivers of tedious jobs by letting driverless trucks ply the freeways and the drivers to take over when off the freeway initially? Adoption and social acceptance in my view will have a huge path dependence and a range of adoption options are available.

Possibility 2050:

Driverless automotive technology will be pervasive. Public transit might replace cars as we know them in small pods instead of large buses and will be unscheduled and point to point, on demand. Certain streets will be dedicated to autonomous public transit pods only. Larger distance travel will also be autonomous, possibly on “tracks” (evolution of today’s trains but with small “rail pods” instead of large trains); autonomous driving, except in special circumstances, will drive us towards smaller “pods” of less than 200 pounds of vehicle (think grown up “weather protective” scooters or golf carts that seldom crash) per passenger rather than today’s 2000 pounds of steel per passenger. These will be augmented by flying autonomous taxis changing our notion of commute distances and navigable terrain/roads/rivers/mountain passes/bays. Trucks on freeways will be completely autonomous and autonomous vehicles will dominate local transport too and become much more diverse in size and configurations from sidewalk or bike lane delivery robots to small local delivery vehicles to larger freeway vehicles. The focus will be on throughput per lane for each modality of transportation and safety. And just maybe, if we are optimistic, we will have Shanghai to San Francisco in a 30 minutes rocket flight.

Transportation 2025:

Early driverless robo taxi services and trucks on many routes, often the simpler and easier to map ones, and possibly flying electric planes. Electric and driverless technology maturing for cars, trucks, trains, planes, helicopters and more, driving major shifts in economics and land use patterns and transportation resource consumption from steel to oil to roads. Even though “market penetration” may only be a few percent in each category, the inexorable trends will be evident and on a rapidly improving and iterating path. Freeways will be routinely plied by autonomous trucks but city driving will be largely human drivers. Flying cars may be common personal curiosities with small penetration. Electric transport airplanes will be starting to enter service.

8. Reinventing Health, Disease Diagnosis and Management, Drug Discovery

Key drivers: Artificial intelligence for comprehensive understanding of medical knowledge, new measurement techniques enabled by and for machines allowing for 1000x or more data for algorithms to use, new algorithms to discover new knowledge in medicine, new tools for imaging the body and biomarker data acquisition from blood to physiologic (ECG, HRV, BP etc) to phenotypic biomarkers (wearables, voice, etc), better research based on more data, more , better drug discovery using AI, and AI guided robotic surgery. And eventually, much more causal models of disease and computational models of the human system.

Healthcare Trends:

Is it likely that technology could multiply doctors including many, if not most, specialties many-fold? Perhaps it could even, invent a better doctor, making them always available everywhere, accessible, and affordable or near free like Google search? A personal, broadly knowledgeable AI doctor for all 7 billion people on this planet is possible, even likely. Maybe people should only provide the human element of medical care? There are probably a million doctors in the United States, give or take, but with AI systems, we could create ten or a few hundred million doctors worth of expertise and use human doctors only for what they love to do, which is interfacing with patients, making health more personal, accessible, convenient, and less costly.

We imagine an idealized doctor today but the reality of medicine today is very different. Doctors have a few minutes per patient visit for the top half of the planet’s population and little to none for everyone else. In the future, almost certainly data science and AI will provide much better diagnosis, monitoring, and follow-up than most human doctors, as per my paper in 2016. It will do much better prescription, whether prescribing a drug or a procedure. We will have real science behind medicine. Doctors today learn mostly from constantly improving iterative practice and that has resulted in better medicine than we have ever had before. But it could be substantially better with rapid acceleration in quality as we move from the practice of medicine to the science of medicine. Every AI agent will be updated with the latest research and up-to-date with every specialty, instead of being knowledgeable in just their own vertical specialty. That will allow for a holistic approach to treating patients because of integrative knowledge, as opposed to the current separating of the specialists, like patient’s cardiologist from their orthopedist or endocrinologist. AI will do much better diagnosis, monitoring, and follow-up than most human doctors and complement the human element of care humans might provide.

Medicine is much better than it has ever been, so we have to acknowledge every aspect of medicine has improved over the last ten years, thirty years, hundred years. That, however, does not mean it cannot be even better. At the moment, the “iteration of practice” has done a good job to improve medicine; when AI does medicine, it will be so much better. AI will enable less errors in doctor diagnosis and surgery, better drug discovery, and personalized prescriptions. Care will be based on thousands of biomarkers, genes, transcriptome, proteome, sometimes called “all omics medicine”. We will be able to measure many more variables (thousands or millions per sample/patient/time point or more) and make decisions based on complexity no human doctor could master. It will be possible to even specify dosage for drugs for each patient’s current state and monitor disease progression as well as side effects at the molecular level.

It seems silly there is one dosage prescription for aspirin or opioids for seven billion people on the planet. Drug discovery and surgery will change primarily to computational techniques, opening up more possibilities. Procedures like surgery and anesthesia could get roboticized, either with a human assisting robot or the other way around. Should you have bypass surgery or a stent? Most of that medicine is based on debatable evidence. According to the American Heart Association, there is class A evidence for only about 11 percent of their cardiac-related recommendations, meaning evidence from multiple randomized trials or meta-analyses exists to support the diagnosis. Whereas 45 percent are based on recommendations founded on expert opinion (level C evidence, the worst kind).

And great quality will only be possible to achieve because of very low marginal costs, as has happened in so many other computationally based services. Better and faster patient outcomes, lesser healthcare costs, and more accessibility to all people are most likely to happen simultaneously. Technology has generally increased healthcare costs, but hopefully, it will be different this time as marginal cost will be much lower, as opposed to those of proton beam accelerators.

Much has been discussed about precision medicine. Unfortunately, however, it is mostly focused on genomic data. That is mostly tunnel vision; a much more promising “all omics” medicine has the potential to use your genome, your microbiome, your blood transcriptome, proteome, metabolome, exposome and generally “all omics” as well as custom computational models of each human body to precisely characterize the state of each human body and body subsystem. Network medicine will treat all the metabolic pathways in the body simultaneously as a connected network system, not as individual pathways. Such approach would be more personalized than precision medicine. I suspect most diseases will be defined and diagnosed this way, with broad terms like “diabetes” becoming obsolete and patients being classified by the molecular pathways, causing the high blood sugar “symptom” to become obsolete just as the term “dropsy” has, thus marginalizing symptom-based medicine. One of the fundamental limitations in medical practice has been the propensity to collect data that people can interpret. What is promising to me is the number of fundamental technologies being attempted to collect large AI scale data from everything, from an MRI image to a blood sample to the lowly ECG. If one had 30,000 biomarkers from every drop of blood for the same cost as today’s blood test and diabetes was defined and differentiated based on patterns of these markers, one would be able to predict which diabetic was at risk of cardiac disease and which of diabetic neuropathy. All this would be much better for the patient. Imaging is also ripe for reinvention, using computational capabilities and consumerized components. Much more is possible than we settle for today, in X-rays, ultrasound, MRI, CT scans, fMRI and more, with reimagined imaging with new math and physics offering more detail, faster at higher resolution and lower cost and increased accessibility. Looking into the body should be routine, radiation-free and inexpensive.

In my view, very little about medicine needs to stay the same. We have to get away from the idea that we use symptoms to diagnose disease. Data science should diagnose disease and monitor progress or recommended dosage of a medication and therapy to best treatment. We should get away from the notion of one prescription for all seven billion people on the planet based mostly on their weight. As I described on Quora last year, one should take a million people, measure hundreds, if not thousands of variables, their blood and their microbiome and their physiology, every week, for a year. That way we’d have fifty million data points, each data point being thousands of data points in itself. Such a data set could predict most diseases, diagnose most diseases, and do it early — when it is truly beginning, not when it becomes symptomatic. This can not only contribute to preventive health. It can and will combat diseases and cancer by very early diagnosis. Plus, layer this into gene editing techniques and microbiome research. There is much to be done around personalization and targeted medicine. That’s the startup I would do and get excited about doing. We have already seen entrepreneurs working on it in bits and pieces. While it’s very complex and cannot be done in one step today, we will get there in the end. As I only half jokingly told the Stanford Medical School audience about it three years ago: “If I wanted to be a really good doctor in fifteen years, I would not go to the med school, I’d go to the math department.”

Here are the facts: if you give a doctor five thousand data points, they wouldn’t know how to diagnose you. If you give a system five-thousand data points, it can do really good diagnosis, and if you do fifty-thousand more, it’d be better. We can get enough information to recommend whether you really, are at high risk and should get a colonoscopy This analysis will get better and, eventually lead to generalized early cancer detection.

Disease will be detected early. Right now, most people with heart disease learn about their disease from a heart attack, not twenty years earlier when it started. When this is no longer the norm, we will move closer to healthcare from the sickcare we have today. We should have real science behind medicine. Medicine is much better than it has ever been, so we have to acknowledge every aspect of medicine has improved over the last ten, thirty or hundred years. But that doesn’t mean it’s as good as it can be. The people who object to this, don’t realize that at least three billion of the seven billion people on this planet have never seen a doctor, don’t have access to one, or cannot afford one. They definitely couldn’t afford the drugs that pharma companies have been putting out recently. It is criminal that they cannot, especially if medication exists.

Possibility 2050:

Every consumer will be the CEO of his own health informed mostly by AI. Not subject to the whims or availability or opinions of a doctor. We will go from the practice of medicine to the science of medicine with the ability to see how every personal parameter, among hundreds, is affected as one administers a drug or procedure. We mostly eliminate the notion of symptom-based medicine or symptom-based diagnosis with predictive capability dramatically predicting most disease onsets days, weeks, months and even years in advance.

Imagine near free physicians for everybody (nursing specialties will still cost money and back offices which account for a lot of healthcare personnel will be dramatically reduced). Every person on the planet will have access to a 24/7 personal AI “near free” physician which is also an integrative “all specialty” physician. All seven billion people on the planet may have this personal AI “primary care” or “all care” doctor when they need it, a personal psychiatrist, a personal oncologist, a personal cardiologist and more for about the cost of Google search. We will treat patients holistically because of integrative knowledge and not separate their cardiologist from their orthopedist or endocrinologist. The annual physical will be dramatically more quantitative and predictive of future health without costing more. Routine (even checkup) blood and other tests will massively multiplex data (10,000 or more biomarkers periodically at costs below that of a simple blood draw). Imaging will be much higher resolution, more functional and detailed compared to today, liely with full there 3D dynamic/functional models of hearts and brains. Full body ten minute scans and functional characterizations (like arterial flow rates, perfusion rates, or fMRI ) will be routine. Fine grained mental health treatments will be based on hundreds of quantitative biomarkers not the current DSM-5 manual for psychiatrists. Disease progression measurement for diseases like Alzheimer’s will be quantitative.

Drugs, including narrowly specific biologics will be personalized. Humans will have fully computational models to predict the affects of interventions like drugs and personalized testing options like organoid systems before serious interventions for in vitro testing in addition to in silico systems. Network medicine using interactions among large number of biomarkers and pathways simultaneously will be dominant with models with hundreds or thousands of parameters.

Disease will be detected early (it’s a shame that most people with heart disease learn about their disease from a heart attack, not twenty years earlier when it started) and we will move closer to healthcare from the sickcare we have today. Data and AI technology intensive healthcare could be a lot cheaper, accessible and better. And just as a library research project is as cheap and more comprehensive generally through a google search, medicine will follow similar cost and quality curves (though healthcare incumbents, from hospitals to the AMA will still be fighting this better, lower cost care with fud and scare tactics).

Healthcare 2025:

We will start to do short to medium term prediction of disease, disease prognosis, dosing, prescription and new forms of imaging. AI will be preeminent in its features though not deeply penetrated. Diagnostics will include all omics but in a physician assisted way but the amount and cycle of testing for everything from blood biomarkers will be based on larger scale multiplexed techniques and will be more immediate and much lower cost. Human physicians will be bionically assisted by AI systems but will be primary caregivers, diagnosticians, prescribers. Consumers will, when they are so desirous, will be much better informed by AI systems. Microbiomes and foods will become start to be important in everyday physician prescriptions with both recognized by the mainstream medical world as important “drugs” and curatives. New techniques from AI and robotics will dramatically improve drug discovery, drug targeting to personal omics and even dosing. The number of gene specific biological drugs like anti-sense oligos will start to accelerate and small molecule drugs will significantly improve their approval rate. New biomarkers like HRV, vagal tone, EEG and ECG sub-features, detailed ultrasounds will augment traditional less precise markers like blood pressure, heart rate, ECG, temperature and physical exams. Genomics, transcriptomics, proteomics, metabolics will enter traditional medical practice.

9. Reinventing Manufacturing, Construction, Buildings, Building Efficiency and Cities

Key drivers: automated construction using manufacturing techniques, 3D printing, new materials, robotic delivery, “transformer” type spaces, shared and higher percentage reusage, 3D printing of buildings and furniture, social networking and increase in community spaces and relationships.

Buildings are a big part of our urban landscape and a large consumer of resources. Construction and building account for more carbon emissions in the US than transportation or industry. LED lighting is enabling 80 percent less electricity use, although unfortunately efficiency in light generation goes hand in with the increase its use.

Possibility 2050:

Buildings are a key part of our urban landscape and a large consumer of resources and given their lifetimes, they will overtly look similar. But techniques ofr new building construction will change dramatically. Housing will be dematerialized and manufacturing techniques including partial 3D printing and lessons from automotive will be applied universally to construction.

What if space was reconfigurable and we would need half only as much to live comfortably? Some startups are building cost effective “transformer furniture” systems powered by modular robotics, so that they can seamlessly adapt space to activities and can be installed in a true plug and play fashion. Affordability and availability would go up and land use would decline for housing of large numbers of people. Space would become more cost-effective, and developers would be able to adopt their buildings retroactively. Buildings purpose built for WeWork-like uses and reconfigurable could add additional virtual space. And new community spaces through reuse may change the equation further.

Further imagine buildings were manufactured like automobiles, reducing costs dramatically. Possibly, next generation buildings would be 3D-printed in concrete or other materials and maybe steel or carbon fiber reinforced and designed with AI. For example, using generative design, they could possibly weigh a 50–80% less with much better insulation and use fewer quantity of materials. Structural elements like beams could use far less steel or could be 3D-printed with composites. For instance, 3D-printed carbon fiber beams can be five times stronger than titanium, and when 3D-manufactured with no human labor, more cost effective. All unnecessary material unneeded for structure could be subtracted with AI design and 3D-printed. And what if shared office spaces could turn into residences or hotels at night or be “WeWorked?”

Could we accommodate twice as many people twice as affordability in the same city? Of course, we won’t take down buildings or rebuild a whole city immediately. Yet, all those freed up parking spaces and new construction would be an opportunity to transform the city gradually over the course of two to five decades. A very large percentage of buildings are non-compliant with current code; the combination of forced compliance and upside economic opportunity with much more cost-effective space may motivate developers.

One can imagine delivery robots reducing chores as well as traffic using sidewalks. Or virtual clinic visits reducing medical visits. The complex ecosystem is hard to predict but will offer many opportunities. Robotic kitchens for burgers and delivery robots for home delivery would reduce the need for restaurant space. Here, I’m sticking with more linear ideas that might motivate an entrepreneur to pursue the change by themselves and build the next Google or Tesla.

Manufacturing, starting from cars to furniture and other durable goods, could also use techniques dreamed about above. Construction would put them on a different cost trajectory than in the past, and could potentially end up messing up our GDP numbers as much as computing has! They could be printed locally on-demand when possible (from walls to sofas) and minimally assembled locally; this might not be feasible for automobiles, but easier for furniture.

Autos would have different material consumption curves because of these techniques and others, like autonomous driving, would eliminate most accidents and hence reduce the need for bulk and crash protection! Add new battery technologies that cut weight in half and accelerate the decline of the internal combustion engine and its pollution. 3D-printed composite structure could mean crashproof automobiles. Public transportation in small pods travelling 10x more miles per year than today’s automobile on average will put pundits prognostications about our transportation needs to smithereens over a few decades. In general trends towards dematerialization of things will have accelerated.

Cities and urban living can be hundreds of percentages more efficient, sustainable, and with dramatically less costs and more community. Imagine a city world where we need less restaurant space because of robotic kitchens, robotic food delivery, self picking mini grocery store warehouses for Instacart like ordering with robotic delivery, virtual entertainment and get togethers, more parks for being outdoors that substitute for parking lots, or houses that multiply space because of AirBnB like models to reduce need for hotel rooms and increase space efficiency. WeWork like space efficient buildings that are further reused for homeless housing or hotels in the evenings with transforming furniture? New housing could half the space because of robotic transforming furniture improving space efficiency. Our assumptions about space, cities, density, efficiency, transportation, parks could change in unpredictable ways. This is a far cry from the 5–10% building efficiency environmentalists talk about and it will involve very little sacrifice of convenience.

What might manufacturing look like in 2050? Dematerialized, efficient, just in time, very local. Little inventory, no long supply chains, nothing made in China taking 3 months to ship — you get the idea. The nature of a car or shirt or furniture may or may not change but need for cars will and how shirts are made will change. Blockchain-based supply chains will transform our efficiency. A Kuka robot arm shouldn’t weigh 3 tons and could be replaced by smarter arms used for broader scale manufacturing and 3D printing. More technologies could invert the supply chain to more local, product cycles and costs in unpredictable ways. Customized, dematerialized composites or metals 3D printed in generative design derivatives may make manufacturing a different world with very different tradeoffs of cost, complexity of design, supply chain, materials, inventory, and customer preferences including retailing. And all this would apply to many if not most parts of our consumption from buildings and houses to transportation to appliances. Materials choices for building things will be numerous.

Manufacturing and construction 2025:

Housing will be start to be dematerialized and manufacturing techniques including partial 3D printing and lessons from automotive will be applied to construction. Space will start to be reused or used more efficiently with robotics. Every restaurant in San Francisco is underutilized during certain times of the day. That shouldn’t be the case. WeWork and Airbnb are starting to address space efficiency and that may become more of the norm for many use cases. Making a 500-square-foot apartment behave like a 1,000 square-foot apartment through robotic transformation of furniture. Because the furniture moves and transforms, the bed goes in and out. You don’t need 3 feet in front of your closet when you’re not using your closet. All this kind of space efficiency. Robotics companies are reducing or eliminating kitchens in restaurants. Robotic deliveries. Rethinking how construction has to be done and the start of AI software driven design, planning, scheduling and building of construction.

We will have AI robotics driven assembly lines with ease of configurability replacing lines in China locally with the intelligence and dexterity to replace much of human capability be it assembling an iPhone or selecting eggs by size. We don’t need humans doing mind-numbing robotic jobs. 3D printed composites or metals based consumer goods and industrial goods will be common from shoes to bicycles and maybe even some houses. Your normal wrench will have much less material in it and complexity in furniture may be near free. New materials will proliferate. The supply chain from the far east to the west will start to invert for specialty items from small volume manufacturing to shoes to clothes and furniture, though the east will start to create new local demand that will be locally filled.

10. Reinventing Food and Agriculture

Key drivers: Robotics, machine vision and AI, plant by plant care eliminating much of herbicides and insecticides, meat alternatives, sensory technologies to pack sensation with nutrition, better land use, drone and satellite imaging, better seed and chemical technologies, microorganisms, precision agriculture, fermentation & synthesis technologies, indoor farming, dense farming, microorganisms.

Whether any of the current “meat equivalent” food production companies changes the world or not, in order to get past the ills of animal husbandry and return our planet and land to its healthy, diverse ecosystem, something like Impossible Foods is necessary to match the taste of red meat. Whether it becomes a huge googlesque impact, a role model, or a footnote in history, it proved the possibility of food reinvention. Multiple entities working on reducing the impact of meat production, consuming a very large part of the planet’s usable land mass and a humongous percentage of freshwater use on the planet. It takes 1,800 gallons of water to produce a pound of beef. Growing the amount of feed grains necessary for just raising livestock accounts for 56 percent of the U.S water consumption. Similar efforts are underway in dairy alternatives. It is possible to reduce the land required for animal husbandry by 50 percent or more, despite the increasing demand. New sensory tools are being developed.

Traditional agriculture companies developing robotic technologies are dramatically reducing the need for herbicides and eventually other chemicals. Even plant-by-plant care, dosing of fertilizer or herbicide or insecticide in a million plant field is entirely feasible with robotic technologies. This can lead to higher yield, lower inputs, and lower environmental damage. Why spray herbicides on the whole field when one can weed mechanically, and, perchance, eliminate herbicides all together? Perhaps we can using robotic mechanical weeding to mostly eliminate herbicides in agriculture and get rid of the hated Roundup and dramatically reduce insecticide use? Maybe we can even allow GMO plants that are generally good for society but much maligned because of the negative impact that glycophosphates (Roundup) has on environments and GMO plants are most closely associated with Roundup Ready plants, can be freed from it. Eventually, these technologies will allow for plant by plant care even in a field of millions of plants. They will allow for far less nitrogen use, more yield per plant, less chemicals, and far less land use. Any technology that can reduce land use is very valuable given the amount of land is fixed on this planet, and we need to reforest millions of acres to find the easiest path to pulling carbon out of the air. Over a hundred out of the 116 models in the IPCC carbon reduction scenarios involve using some technology like reforestation to pull carbon out of the air). It is encouraging that area under farmland worldwide is finally declining and there is potential for the decline to accelerate.

Possibility 2050:

There could be be far less land use for farming, far less chemicals, and far less factory farming of animals. Many drugs will be replaced by “medical foods” and food may become among the more important pharmaceuticals.

Precision agriculture also implies the use of such technologies as data science, aerial imaging, early disease detection. Further development of AI for imaging and data analysis, more easily and frequently accessed satellites, bio techniques like increased microbial communities, all aided by the use of fewer chemicals that would traditionally sterilize the soil because of new roboticized weeding and insect targeting will dramatically reduce the impact of and land use for agriculture. And it might even be that for specialized crops, vertical farms and data science lead to yield maximization coupled with robotic labor make a real change in the yield or resource or acres used. Of course, driverless tractors, drones, satellites, driverless trucks and sidewalk delivery robots to take care of the deliveries may change resource needs broadly.

Another dimension of innovation is the creation of new foods, such as beef without cows, milk from plants, eggs without chickens, all far less environmentally harmful at that. For example, 30–50% of our planet’s land is dedicated to animal husbandry. Impossible uses 90–97% less land and 70% less water — being both good for the environment and people’s health. This new foods will not only shift food production processes, be healthier for end consumers, but reduce environmental issues with very dramatic changes to land use for agriculture. Replacing animal husbandry may become one of the better tools for mitigating climate change and animal husbandry cruelty. Our factory food system with its many benefits and ills is due for massive disruption which will be substantially in progress by 2050.

2025:

There’s so many axes of innovation in food. I used to think food isn’t open to innovation but when I looked the possibilities surprised me. Every area I looked into was open. Even hamburgers was open into innovation and it was clear we could use far less land, water fertilizer, chemicals, animal husbandry. The Impossible Burger is an example. This is how we go from 10% of the world’s population to the 100% being fed well and healthier. And of course, my favorite, 80% less cruelty to animals.

Eggs and dairy are being reinvented. Blue River, which John Deere acquired, used AI to do mechanically robotic weeding so you don’t have to use chemical herbicides. You can do plant by plant fertilizer dosing in a million plant field because it’s robotic. Far less fertilizer, far less insecticide, herbicide. Vertical farming and indoor farming will start to establish itself as a material force from what is a curiosity today. Food production systems worldwide change slowly so trends visible in 2025 will likely take much longer to achieve material penetration of the ecosystem.

11. Reinventing Financial, Insurance and Legal Services

Key drivers: AI technology to replace people functions and judgement (biases and cost), blockchain, mobility, data, software automation, secure reliable software services.

The pundit economists/Goldman Sachs/JP Morgan/Citibank view of financial systems and economics we are used to is being significantly challenged. Even basics like GDP as the right measure is being questioned. Entrepreneurs keep getting outraged that financial services, which should just be a service to real products and services being produced, are taking up such a large share of profits of all industry. It is possible to reinvent most of these services and especially those that rely on human labor or intermediaries. Though companies like Square, Stripe and Affirm are changing things for consumers and small businesses by disrupting incumbents, much more can be done and will likely happen. Others are creating radical new business models, like Even, hourly employee payment insurance, the bank app that plans so customers do not have to. Financial institutions impose massive taxes on fundraising organised by different industries. Those should diminish by order of magnitude based just on cost of providing this service and shared crowdsourced research. Research analysts provide valuable services in capital formation, but the costs are multiplied and much of capital formation is mispriced. The tax reduction should also apply to consumer banking and financial services costs. It could be that blockchain-based services and software contracts in finance and insurance, which could dislodge centralized control or “financial tax”. It could have identity verification, as well as traditional fraud and illegal activity controls like AML, KYC added on to the blockchain.

It could be simpler disintermediation of everything from foreign exchange to lending and insurance services. Insurance could be based on real costs, better actuarial tables, regulation around what is or is not legal to differentiate on, and low overhead. It is likely that legal services are automated by AI; there are only about seven million cases in US legal history. They are more structured and seem easier to computerize based on federal and state laws that these cases interpret than a technology like Google Home or Amazon Alexa which cover a far less structured and much broader range of conversational topics. Computerizing law and lawyers with or without software contracts will enable every citizen to have a personal lawyer(s)at a low cost or no cost at all? A few hundred thousand dollars a year of legal and medical services will cost almost nothing. It is possible that AI will replace many of the supposed value added functions, as it has already been proven in stock trading and financial planning. Judgement and estimation tasks in this data rich segment should be algorithmically driven and AI will likely replace human judgement where there is enough transaction volume (read volume, margins, profits), and much of the back office work done by humans can be replaced by AI. One firm has already appointed an AI as a board member. What is clear is the ten percent of all financial transactions (a wild guestimate) actually add value to society. Industry can be done at a fraction of the cost with less overhead or transaction taxes, and it can be done more fairly by more objective algorithms. The rest is speculation and circular trading worth trillions of dollars daily! This will add a lot more transparency, although it may introduce other problems.

Financial, insurance, and legal services will be freed of capitalistic lock-in and open to much more competition from relatively more transparent players; this could translate into far more affordable and accessible services. For instance, in Jordan, refugees are able to pay for food with blockchain technology, which is faster, cheaper, and more secure. Blockchain enables and creates trust, reduces risk, opens up banking to those who might not have bank accounts. In traditional banking, there are middlebank and inefficiencies in the more formal system that exists today, whereas with blockchain that’s not the case, thus breaking socioeconomic challenges. Another example, is making access to legal services more affordable through AI, essentially replacing the lawyer. Whether for contract law, IP, or personal law, most if not all the work will be done through technology.

Possibility 2050:

Human mediation of financial, legal and insurance services will be relatively small compared to higher quality services offered by AI systems. Wealth advice, legal advice, insurance, lending, fraud, trust will be AI driven worlds to a large degree. The nature of services and needs is almost impossible to predict. Some form of Universal Basic Income will likely be a more broadly accepted concept though at a lower level than needed to provide full income support for recipients. The nature of the “firm” will be different but hard to say how. The nature of “work’ will trend towards jobs people want to do and not what they have to do. Whether the speculation and circular trading worth trillions of dollars daily that will be minimized to the bare essentials is harder to say! Many if not most aspects of finance can be replaced with technology that make financial services more affordable and accessible.

By 2025:

The basic functions of banking, lending, borrowing, investing, capital formation, insurance, mortgages and legal can be done much better, more fairly, cheaper with less overhead and broader accessibility. All the people with fancy wealth advisors will do far worse than somebody who just relies on AI at very little cost. Credit should be pervasive, easier and not mediated by humans. Algorithms will be biased but we will identify how to detect these biases and often correct for them. In any case algorithms will be much less biased than the current state of affairs with humans making judgements. Mortgages and supply chains may start to take advantage of blockchain and likely the cost of centralized agents (like banks or bankers) will be substantially reduced because of competition from distributed trust systems.

The financial tax of intermediaries will start to be minimal in most routine transactions and AI’s may construct many unique transactions and services. The same will happen in financial services whether it’s insurance or loans or access to investment opportunities. They will be dematerialized with few humans needed. Lots of new axes of innovation and data will allow for much more lower cost insurance from salary insurance for hourly employees to helping small business do what larger businesses do with AI based systems at low cost. So many new services will appear that suddenly don’t need big banks or big financial institutions. We will start to remake most consumer and business financial and insurance services and put pressure on larger institutions to adopt or get left behind. Risk bearing assets will have more direct access to markets with fewer intermediaries.

12. Reinventing Energy Services

Key drivers: Scientific talent and long view funding.

The best minds getting PhDs are not going into energy or cleantech today, which poses a fundamental problem. Entrepreneurs realize it is hard to get funding, and for that reason, we are not seeing as many startups as we’d like to see. And energy services need technology as a driver to make environmentally great energy services market competitive. Cleantech is very capital-intensive and although there was a period of too much exuberance in the area, now it is met with investor disinterest. While it will slow down innovation long-term, hopefully, it won’t stop it altogether.

Organizations like Breakthrough Energy Ventures are trying to address this. There are a number of audacious fusion projects and equally unlikely geothermal energy projects where linear cost for deeper drilling instead of exponential cost per foot when drilling at depth is the key breakthrough needed, storage, new materials and manufacturing, building materials, new agriculture and food. It is possible but the going has been slow.. This is the hardest area in which to visualize breakthrough step impact progress. I am still hopeful and feel that many high-risk projects with high probability of failure must be attempted. Though 5–10–20 percent improvements are still fundable, 500–1000 percent change innovations are less clear to me. There are many areas in which it must be attempted: from fusion to geothermal to storage to new materials and new agriculture and food. Food is the easiest area to see radical resource efficiency.

That is likely the way to providing seven billion people a rich lifestyle as defined earlier without destroying the planet, depleting its resources (can we produce 10x the steel, copper, glass, cement, or use 10x less of each), and irreversible climate change. Low-carbon/low-cost power is a major need and achieve extremely hard to find solution to. Nevertheless, a much worse option from trying and failing will be failing to try. I have personally failed at trying to do this and had only limited success. Others like Tesla and Waymo/Google serve as role models and are changing the transportation industry forever. Additionally, AI may help accelerate progress in energy, and with quantum computers help with design, and exploration like at least fusion reactor containment structure, or find a solution for dark matter physics. Perhaps, it could help in designing more energy-efficient buildings or design cities that align more with structures in nature (highly recommend reading Scale by Geoffrey West.

One of the largest inefficiencies in energy, is when it comes to agriculture. The production process is wildly broken. The Alliance for Water Efficiency estimates that $13–15B boost to the U.S. economy could be possible through more water and energy efficiency efforts, in general. With technology and innovation, water can be better conserved and utilized across the full agricultural process — whether it is in irrigation, crop yield, or distribution. Satellite advancements, robotics in fields, vertical farming, soil sensors, analytics using AI (for things like weather information or when and how to take actions or utilize water will increase efficiencies.

I am hopeful that a few breakthroughs, with fusion and geothermal (where linear cost for deeper drilling instead of exponential cost per foot when drilling at depth is the key breakthrough needed) being my best candidates, will help us over the next few decades. A caution is in order. Most attempts in energy look for 10–20–30% improvements in energy r resource efficiency. We need 100–500–1000% improvements in energy, water, land use, minerals and mining and in general everything that uses physical resources. Buildings have to for example use 80% less materials by weight and water efficiency of meat and ag production has to improve by similar amounts. This is hard.

Having said that the decline of oil as an energy source in transportation has clearly started and will be even more firmly a trend by 2025. The path to clean nuclear like fusion energy will take luck and persistence for stationary energy services. Alternatives will be EGS geothermal or large scale energy storage by 2050 to complement intermittent sources like solar and wind.

13. Reinventing Consumer Services from Retailing, Entertainment to Elder Care to Delivery

Key drivers: Mobile, AI, internet, communications, social networking, voice and image technology, sensor and cameras, data, mass personalized manufacturing.

The way we shop and consume products and services has started to change over the last decade. The decline of traditional brick and mortar companies is clear but this does not necessarily point to the downfall of brick and mortar itself.

Technology is changing the way we discover products (Pinterest), how we order them (Instacart), how we make purchases (Apple Pay or Square), and how we find what’s right for us. The supply chain is being reinvented, starting from one hour deliveries from a virtual pantry within minutes from many homes, all the way to completely reinvented grocery stores. Wallet share is changing as well from physical products to technology-enabled experiences like more personalized hotels or “stay rooms” such as AirBnB. Space is transforming to be more efficient and serve people for multiple purposes — the brick and mortar as we know it will shift, and we are already seeing this. 3D printing will allow us to print items on-demand, and even recycle, whereas AI will transform the experience to be truly personalized, whether that is tailored furniture or food plan unique for each individual. Lastly, robotics are changing how we interact from food delivery to Amazon Echo.

Yet we are seeing more physical local bookstores, which might actually mean a rebirth of the community experience, unlike product experiences of Amazon! We might even see more display retail rather than full inventory stores to provide community and shared time experiences with friends. However, these dynamics are hard to predict to the point it is hard to gauge the direction of change. Will the future hold more or less local retail? More of less community experiences and spaces? Instacart is disrupting the need for full grocery stores, while retail stores are also doubling as coffee shops or yoga studios when not in use. Retail will be more efficient for more than just selling products or serving as local distribution hubs and product display hubs. We may even see the rise of mobile spaces taking over parking lots or having the ability to use space better and reach out to people.

Experiences, especially shared and community experiences, will be more in demand, be it Sephora or yoga or coffee. Retailing may take on other manifestations too hard to predict, but inventory carrying stores may be passe. As costs are lower to create products, strong branding will be more important and values based brands will become more important. On the other hand, custom clothing on the spot fit to your body, made robotically, may not be too far away. 3D-printed custom items from sofas to shoes? As a result, with tools like robots and AI, we will be more efficient and will reduce costs to redistribute to other places. For instance, will we see roboticized restaurants building customized, fresher, and less expensive, or more accessible, fresh, fast food with no food deserts?

In the future, we will be able to fully customize fabrics or outlets, we may be even able to 3D print these on-demand, disrupting supply chains. Sensors will become smaller and cheaper to enable more, if not most, things to be connected and controlled in a seamless way. We will have more data about us (whether it’s microbiome/genetic data for food, size/fit data for clothes, or music taste for buying composed music just for us using AI), that will allow for further personalization of our shopping list. Microbiome/genetic data could influence our for grocery shopping, size/fit data — clothes, or music taste for buying composed music just for us. All that can be enabled by the use of AI. Nevertheless, the use of such detailed data carries a possible danger connected to it, too. Regulation will have to strengthen on who controls and owns what data.

When it comes to services, the current labor force will shift. Large companies will have less of a hold on workforce. Because of technology, workforce will become more independent and flexible based on how these workers will want to spend their time. Whether a dog walker works for Wag on his/her own time, or a hairstylist no longer works at a Salon and goes direct to the consumer via an on-demand app, services will come to the person in a higher quality, more affordable, and more personalized way. Labor mobility and nature of jobs will change substantially.

I want more data about me and I want to control it, share it temporarily for a particular purpose to provide me services and rescind permission at will. Will the blockchain allow this without centralized trust? AI is also allowing us to have more tailored experiences to either design the right furniture for our home. It can, make new foods using algorithms, be it Watson cookbook or startups using AI to characterize proteins and design new foods., It can redefine our interactions with customer service when ordering an item. Robotics are also changing the game — starting with Amazon Echo which changes how we interact with our environment, including shopping, e.g. via voice in our home.

Consumer facing robots will become more functional and empathetic. For instance, Elderly care robotics can take care their needs or prevent elderly from getting lonely, to robotics that optimize manufacturing times and deliveries. Robots will monitor elderly for their food and drink consumption and remind them to take their prescriptions but more importantly will entertain then and engage them in conversation and community connections, combating loneliness. Technology will also enable families and kids of elderly to have a better grasp of their loved one’s health and status. Robots will also transform the way kids can learn, creating more interactive, personalized education, and also robots for special needs people will create new ways to provide care.

When it comes to entertainment, TV, music, and other media are transforming. Music that was once the creation of songwriters and popstars, will be taken over by AI music and the same goes for TV shows. Whether it be Netflix or Amazon, shows will be created based on what people want. Entertainment will transform to be more than just 2D in the way we watch it today — whether it be holographic or virtual reality, entertainment will use more of our senses than what it exists today. The future will be dominated by new kinds of light field displays, new sound and haptic capabilities, AI driven robotics, AI driven music, art, entertainment and comedy in conjunction with human entertainers, artists, musicians enhancing the entertainment that can be done. Plentiful designs, local supply chains, almost transparent retailing, AI driven and AI robotic assisted elderly care with human supplementation of elder services on an exception basis.

14. Reinventing Education

Key drivers: AI to personalize education, open source content, AI tutors, mobile and internet create more accessibility to knowledge and education, AI/AR/VR changing how students can get information.

I recently asked a simple question: Is majoring in liberal arts a mistake for students? The problem, I argued, is that the current liberal arts education does not teach critical thinking and scientific progress in the way that it should or in the way that STEM does. Now, STEM perhaps, doesn’t teach enough of liberal arts — how to create real businesses from science and technology, and applications for best impacting the world.

Ironically, the more AI-driven changes we postulate here happen, the more necessary a real liberal arts education will be, something I now call “Modern Thinking.” Liberal Arts was what Greek elites indulged in when they did not have to work and servants and slaves did much of the work. Schools teach “in the box” thinking, standardized bubbles tests versus encouraging creativity and thinking in new paradigms. The education system is full of opportunity, and yet, it’s an industry that’s challenging and complex to change. The purpose of education will be less about employment and more about inquiry (scientific and other), stimulation, curiosity, ethics/values and similar more ephemeral less quantifiable goals. I have argued for a new discipline called “Modern Thinking” as the principal curriculum for non-professional majors. By 2050 this trend will be clear as will be clear we need to redefine the nature of work and education to “understand, pursue passion, pursue inquiry, not to get a job” as many routine jobs get roboticized or AI’ed. Communities of people, virtual or physical, will play a large part in education and intellectual pursuit.

With technology and new tools, accessibility and equality in education will change, no matter what style or subject of education you want. The ideal “tutor” for the task will always be available. AI tutors will not only allow for more affordable or free accessibility 24x7, but they will personalize education for each person. They will be able to assess where a student is, know the map of their knowledge and gaps in it and be able to guide a student through to their personal learning objectives. With technology and new tools, accessibility and equality in education will change, no matter what style or subject of education you want. The ideal “tutor” for the task will always be available. AI tutors will not only allow for more affordable or free accessibility 24x7, but they will personalize education for each person and widely accessible at low marginal cost.

Even for traditional grade or employment-oriented education this is a massive multiplier of teacher resources, letting them be the human element of teaching and not stranding those for whom teachers and tutors are a luxury. And for skills or humanities education AI and social networking enable community learning is an additional multiplier. In the near future, there will be more diverse, location independent education at low cost. No need to go to Stanford, there will be AI discussion in groups which will change cost structure. In the case that a majority of jobs get displaced by AI over time, this will also focus education to shift to teach other skills and change the curriculum. Perhaps, because of this personalization, the very notion of majors such as STEM or Liberal Arts will change altogether. These systems will serve humans.

15. Reinventing Business, Cyber, defense, Governmental Services

Without too much elaboration, it is worth point out that business services, resource uses, and products have been changing and will change even more. The change will continue and even accelerate on both the production and services side. No business, be it fintech, consumer goods design and production, industrial products design, drug research or manufacturing, materials design, manufacturing, spare parts, sales AI agents, or customer support agents, will remain untouched. The entrepreneurial opportunity will be immense, but the areas are too diverse to cover individually.

Technology will have an impact all of these, though my focus here is on things an individual entrepreneur can drive, not on governmental or regulatory services. Space and cyber will be often entrepreneurially driven, although the latter will have many state actors. I am less concerned here about governmental parts of GDP, except to note that safety nets for citizens will be easier to provide and such things as our traditional notions of taxes or redistributions will have to change. Tea party folks, you have not seen anything yet.

On cyber services I refer you to AI: Scary for the right Reasons but suffice it to say that massive entrepreneurial opportunities in defensive and offensive cyber tools and services will exist. There will be a large overlap with state institutions though corporate needs and markets will also escalate and grow. AI will dramatically escalate incidents of cyber warfare as rogue nations and criminal organizations use it to press their agendas, especially when it is outside our ability to assess or verify. This transition will resemble what we see when wind becomes a hurricane or a wave becomes a tsunami in terms of destructive power. Imagine an AI agent trained on something like OpenAI’s Universe platform, learning to navigate thousands of online web environments, and being tuned to press an agenda. This could unleash a locust of intelligent bot trolls onto the web in a way that could destroy the very notion of public opinion. GAN type AI approaches will make these continuously learning, continuously stressed and hence improving machines. Alternatively, imagine a bot army of phone calls from the next evolution of Lyrebird.ai with unique voices harassing the phone lines of congressmen and senators with requests for harmful policy changes. This danger, unlike the idea of robots taking over, has a strong chance of becoming a reality in the next decade. My biggest concern in the next decade is that AI will dramatically worsen today’s cyber security issues and be less verifiable than nuclear technology.

Massive entrepreneurial opportunities in defensive and offensive cyber tools and services will exist. Entrepreneurs will need to push further innovation across these areas for true innovation to happen. Much danger also lurks in these areas.

16. Some Khosla Ventures companies addressing these areas:

At Khosla Ventures, we look for companies who are aiming to make strides in the areas mentioned above. There will be many attempts, many will evolve, most will fail, and a few will hopefully become radical transformers. Though, many seem like small efforts, as a group they will form a tsunami, and will sweep through impacting innovation and change.

Health and medicine:

AI and data driven change from “practice of medicine to science of medicine” and specialty by specialty reinvention of the expertise, meaning virtual primary care doctors, cardiologists, psychiatrists, oncologists, is happening in our portfolio. Companies like Alivecor enable personal cardiologist-like functions around ECG like diagnosing atrial fibrillation or reading an ECG for normality, although nothing as forward as a full cardiologist yet and definitely not the interventional cardiologist yet; to partially substitute a therapist like Ginger.io, or perhaps the primary care doctor experience like Forward, or create an AI physician like Curai.

Others impact health by making accessible, population-scale genetics services like Color, or transforming xenotransplantation into an everyday, lifesaving medical procedure. Genalyte is tackling blood testing results and making it easier to get them in almost real-time in the doctor’s office versus a third-party lab. Rethinking Oncology is the domain of Guardant Health or Oncobox, which is personalizing genetic profiling to help oncologists decide which drug to use. Conquering infectious diseases through the innovative use of next-generation sequencing to analyze microbial cell-free DNA is something Karius does, being able to scan for 1,300 viruses simultaneously.

Other companies are using data-centric design to entirely rebuilding the next-gen health insurance company, like Oscar does. How about anticipating diseases with tools that enable physicians to predict Alzheimer’s disease before the symptoms appear like Neurotrak? Viome is using predictive biomarkers to your microbiome’s transcriptome and your blood transcriptome at the strain ro RNA level. Using the microbiome, others are creating microbial therapeutics for inflammatory diseases (Siolta) or to target bacteria based on genome (Eligo).

Two Pore Guys is building a digital, hand-held, testing platform for DNA and RNA that’s as accurate as medical lab equipment, but is as inexpensive and easy to use as a blood glucose monitor. Zebra is using AI to rethink most radiologist functions for MRI, CT, x-rays for as little as $1, while Vicarious Surgical is enabling surgeons to do much much more with robots and AR (augmented reality). Heartvista is developing a robust commercial MRI system that will give comprehensive cardiovascular evaluation — real-time data with much less skilled technicians! Q Bio is trying to reinvent the annual physical to be far more quantitative and useful

Pharmaceuticals:

We believe that there will be AI-based reinvention from small molecule chemicals to precise regulation of genes using biologicals in the pharmaceutical space. Companies are predicting potential drug cures with the use of supercomputers, artificial intelligence, and a specialized algorithm that runs through millions of molecular structures. This can potentially reduce the cost and time involved in making new drug discoveries as our company Atomwise is doing, or combine world-leading expertise in machine learning and genome biology to transform medicine. Such is the case with Deep Genomics who are designing biologicals, or offering low-cost personalized genetic profiling to help cancer doctors decide which drugs will be most effective like Oncobox.

Food and food production:

AI, plant by plant robotics, and new methods to reducing chemicals, and precision agriculture are changing the way we produce and consume food. From reinventing the burger to be all plant-based to end animal husbandry,while at the same time reducing environmental impact, like Impossible Foods to creating a new plant-based egg substitute using science like Hampton Creek. What if you could develop sustainable and nutritious food products by matching the protein, fat, and carbohydrate distribution and content of traditional dairy products with a mixture of the proteins, fats, and carbohydrates from plants like Ripple?

In terms of food production and restaurants, companies are using robotics to make restaurants more efficient, increase food safety, and reallocate funds to higher quality food. On the agricultural process side, imagine using computer vision and robotics to improve agriculture like Blue River (sold to John Deere), who specifically enables farmers to spray herbicides only where weeds are present. Or to make farms more manageable with Granular (sold to Dupont) or climate insurance more accessible with Climate Corporate (sold to Monsanto)? Satellite imaging is allowing farmers to better predict and optimize farming practices like, the services provided by both Rocket Lab. Imagine a world where we can use robotics and AI to reduce pesticides, increase efficiency, and create healthier foods — we are only at the beginning.

Financial system:

Large institutional bodies are often the most posed for disruption from financial services, risk and insurance, blockchain and software contracts-based services, efficient exchanges, accessibility, and even legal services. New small business and consumer services like are provided to by Square. Affirm or Fundbox can make larger purchases, banking, loans, professional help more accessible without credit risk, while Stripe can make payment processing easier.

Even, as an example, is rethinking insurance and credit for the modern consumer — managing one’s salary, allowing the customer to allocate a small portion per month to an “emergency” amount to be used when a customer may be in a financial bind. Other companies are using blockchain to reimagine aspects of the financial system — for instance, digitizing experimental money to support blockchain to render it more liquid like BlockStream or allowing users to build Bitcoin applications using an enterprise-grade blockchain API like Chain. Adding to liquidity and efficiency are companies like Opendoor which make home selling much easier and faster.

Construction and buildings, Housing:

3D-printing, modular factory built, and housing efficiency are a few areas that have opportunity. Imagine 3D-printing a house, or using manufacturing techniques to create lower cost units like Katera, or using robots to transform a small apartment into what feels like a larger space like Ori. Other companies are using robotics to make kitchens and restaurants more efficient like Spyce, and Momentum is changing city spaces by fully roboticized restaurant kitchens. Arevo, as an example, makes ultra-strong 3D-printed carbon fiber composite materials, while Vicarious is creating robots who can help construct and build, replacing human workers.

Education:

AI and open source reduce need for infrastructure as well as manpower for education. Imagine a platform for academics to share research papers like academia.edu or an online platform that facilitates interaction among students and instructors like Piazza. New platforms from Piazza (college) a and Kiddom for K-12, now used by one in ten of all US teachers, allow for teachers and students to share assignments, provide feedback, grade, and review reports all in one place are enabling more collaboration and better results in education. CK12, a related non-profit, is making K-12 content free and multi-dimensional while also building AI tutors to make quality education accessible.

Manufacturing:

3D printing, robotics, new materials, AI design. Imagine 3D-printing metals like Digital Alloys. Velo3D develops a technology that will disrupt 3D-printing in metals and Arevo that is changing composites manufacturing and affordability. Add robotics technologies like Vicarious, Berkshire Grey and manufacturing, which has been relatively isolated from change is feeling the pressures and innovation.

Transportation:

Imagine rethinking transportation with autonomous cars and ways to help people get where they need to go faster, cheaper, and with less impact on the environment. In the future, we will simply have self-driving cars as part of a fleet of taxis such as Voyage, or perhaps have alternate shorter destination methods of getting around, such as electric skateboards, like Boosted Boards. Hyperloop, Arevo.

Energy and climate, including water:

Some companies are developing a completely new high-power, long-cycle life, low-cost battery technology for stationary applications like Natron, or building a flexible solar cell design that minimizes the amount of semiconducting material used like Caelux. There are breakthroughs in energy storage for automotive such as Quantumscape, a company developing the first commercial solid state electrical energy storage devices for automotive applications. Others are trying to develop and commercialize new battery technology or develop stabilization for electric grids like Varentec or minimize home electricity consumptions like Bidgely or View making window glass more efficient.

There are companies who are using new techniques and approaches with technology for geothermal energy and Altarock or Lanzatech using waste gases form steel and other industrial process to turn that into useful products. Like all great technology, nuclear energy can be used to create new options for converting low-level waste into vast energy sources like Terrapower, while companies like View Glass and Soraa reduce building energy consumption. And, of course, efforts like Breakthrough Energy Ventures have the potential for incubating long-term technologies for decarbonization.

17. The Silicon Valley culture

I’m very optimistic about Silicon Valley. The way to look at Silicon Valley is to ask “How many new things are starting up?”. It is especially important in contrasting it to the rest of the world. The rest of the world thinks they know what’s important, but the Silicon Valley psych (to me Silicon Valley is a culture not a place and is starting to spread into many parts of the world from Shanghai, Bangalore, Helsinki to Tel Aviv) is to be open-minded. It means to discover and not assume, learn not know, be unreasonable but pragmatic, and determined in not giving up when the going gets rough. It is not being foolish and yet foolish enough to try things others won’t, to be naive enough to not be dissuaded easily, ask fundamental questions around “Why not?”, and not “How has it been done before or tried before”….

Ask anyone in Washington or Wall Street or any other institutional agent what’s important in energy, in climate? It’s General Electric and Siemens. I’d give you odds that no large innovation will come out of any institutional player. Silicon Valley doesn’t know what’s important either, but what Silicon Valley does really, really well is originated interesting ideas and experiments to test these ideas, instead of opining, pontificating or asserting specialty or seniority without proof of merit.

You think Uber is a mess. I think of Uber as having started the change in our notion of transportation, started with a limo service at the very high-end; just like AirBnB started with brokering rooms in Philadelphia in 2008 during the Democratic National Convention and the brokering of rooms. That seed of an idea ends up being way more important than Hilton Hotels after almost a hundred years since they have been around. That’s what is crucial. To me, that is what’s really most important about Silicon Valley. While the world thinks they know what’s important; that Volkswagen or General Motors is important to innovation in cars, the fact is they’re largely irrelevant to innovation (except incremental innovation). It is ‘some improbable’ that really matters. These improbables, once they get a toehold, expand, evolve and improve and can become disproportionate compared to their humble start. They also feed on other new innovations. When they fail their efforts appear to be hubris but apriori categorization of what is hubris and what is world changing is near impossible.

That improbable initially was Tesla (and they can still fail), but will be supercharged by the Google/Waymo and the Uber experiments. The combination almost certainly will upend public transportation in the future, whether either of these efforts fails or succeeds because they have put the world on a different trajectory. It will enable anywhere to anywhere ride on-demand for $1 in most cities in America with public, transportation while providing better service and lower cost than any public transit service of consequence. Incidentally, it may remove the need for large scale city parking spots and open space for parks or housing. It may shrink distances and commutes, eliminate more than half the auto industry and its needs for steel and rubber, and collateral GDP! This loss of GDP (near zero if service is free or near free like libraries or information search are today) will be a good thing. It’s the improbable, like Uber, Tesla and Waymo in 2010, that’s important. The seed of ideas along with passion to try it starts new paradigms and it almost doesn’t matter who best commercializes them.

I will even admit that Silicon Valley driven change will sometimes be scaled because of or by large companies (we welcome GM to driverless cars!) but the initiation of new directions is what is socially important. You know, Volkswagen’s not going to reinvent transportation. Big companies do help scale innovations and bring gobs of capital later when risk of a new phenomenon is low (Walmart in retail?) but they’d rather stay safe and not be wrong. Uber can get lots of flack . Nevertheless, the fundamental innovation they have caused, what Uber started, Tesla started; Google started with Waymo and driverless cars, will completely replace all public transportation, whether Uber succeeds or fails, with what is the new style of public transportation. This seemed completely inconceivable five years ago by anyone in auto or transportation businesses and inconceivable coming from and driven by any large institutional thinking.

Self-driving cars and even electrics were fifty years away till Waymo asked “Why?”! What will be interesting and completely unpredictable is whether cities will run it, like they do public transportation or will they contract it out to a Waymo or a Google or a Tesla, or somebody else. In 2004 I gave a talk titled “The device that used to be a phone” (I had stolen that title idea from somebody but not sure who) and I got right the basic idea that a phone would not be used mostly for talking, but what I got embarrassingly wrong was the cases it would be used for. I was wrong in unimportant ways, but spot on in the most important trends, the general direction of other uses for a mobile device. This is the essence of Silicon Valley, and why reinvention will be driven by Silicon Valley and not the institutions we rely on and take comfort in.

What people confuse outside of Silicon Valley is this notion that I’m almost certain of that the big guys are unimportant to real “big step” innovation. What’s hard to say is the opposite. Improbable, like Uber was, or AirBnB was, or Google was in 1998, is not unimportant. In fact, the only thing that’s probably important is the improbable. We have no way of telling which improbable is important. And because Silicon Valley runs so many experiments and people love to write about all the failures, the hubris, the messes, the trivial, the fraudulent, or self-aggrandizing claims because they, Uber, Theranos, Juicero, Soylent, make best headlines. These same factors are critical to get the self-delusional attempts at grandiose or evolutionary innovation. If these entrepreneurs had normal expectations, they would not attempt the things they do attempt. And their failures and diversion into societally good or bad business is a necessary side effect. Most businesses are improbable and fail but the few (1 in 1000? 1 in 10,000?) that emerge as game changers have disproportionately large impact. As Martin Luther King Jr. said, human progress depends upon the socially maladjusted. And George Bernard Shaw said that reasonable people adapt themselves to the world, the unreasonable man (he should have added “and woman” but he didn’t) adapts the world to them. Hence, human progress depends upon the unreasonable man.

Writers can write about or rail against or laugh at all the naive attempts, the hubris, the pretend unicorn valuations and the vast amount of drama that is Silicon Valley. However, all these things are largely irrelevant in the long run though they make a good “People’ magazine for Silicon Valley and cause clicks on headlines. They do keep the media in business though with salacious content! Yes, investors get mislead or just plain lose their money. Yes, they cause false hopes and even collateral damage to helpful institutions. But it’s the 1 percent or even 0.1 percent that succeed that cause the majority of technology-driven change in society.

All I’m saying is startups drive the vast majority of innovation, not the institutional incumbents. It is this non-institutional driven change that frees us from the straitjacket of conventional wisdom and lets us really change the world. The experts that inhabit this world are experts in a previous version of the world and live by extrapolation. They do not aim at inventing a new future and as skeptics never do the seemingly impossible. Great entrepreneurs, and there are plenty of incremental ones too that do good work, invent the future they want. I would also state without proof but with plenty of experience across many industries, from Wall Street to more mainstream businesses, that Silicon Valley entrepreneurs have a larger percentage of people who are mission-driven, whether the mission is societal or local or silly, than most other businesses I have seen. Though it is important to acknowledge that Silicon valley has its good and bad apples and public scrutiny will help improve things. And that it’s generally positive impact has many downsides we must consider and worry about as discussed in one dimension in “AI: Scary for the Right Reasons ”.

Some of these innovations, not surprisingly, have disruptive effects, both good ones and bad ones. But in areas with large changes most of the effects are unpredictable or unknowable in advance. With every large advantage comes some disadvantages but contrary to punditry about “they should have known” or it “causes job losses” the discovery and fixes necessarily have to be iteratively discovered and iteratively fixed, sometimes with regulatory or public activists oversight. The counter push for “no change” is often driven by those disrupted who are in an uncomfortable business position of being disrupted (the car business or taxi business or the advertising business for example) and who may leverage the genuine concerns of activists or press. This part of the “process” comes from inability to foresee “how and driven by whom”, companies and ideas develop (the alternative is not to do anything innovative, not to know in advance every consequence or path). Naivety of traditionalists can and does slow down great benefit to society from these disruptive changes. The traditional ugly factory farming cattle business or egg business has no love for much better food alternatives like better burgers or better mayonnaise.

It is these improbable sounding experiments that are really, really important about Silicon Valley. What is becoming even more exciting and healthy isn’t IPO’s, but the number of new areas the Valley is attempting to innovate in. A few years ago, we invested in this hamburger company Impossible Foods. Now, there are probably forty or fifty PHDs and another probably forty or fifty other technologists working on designing the perfect hamburger. Why? The founders have started it, because thirty to fifty percent of our planet’s land area (and until Elon Musk gets us to Mars, this is the only planet we have) is dedicated to animal husbandry, and he wanted an environmental better way of producing meat. In addition to other practices, he wants to avoid cruelty to animals, unhealthy food, environmental degradation, antibiotics in our food chain, etc. He wanted a couple of million dollars to run an experiment. Could he do this? This kind of entrepreneur is the core of the Silicon Valley culture and though there are others abusing the public trust as has been widely and accurately reported, there is far more good than bad in this culture. There are good and bad people in any culture but Silicon Valley feels to me much more mission driven than most other cultures.

It’s now gotten into a robust product that’s today a niche product, but the goal, clearly, for the founder, is to replace all animal husbandry. You are not going to get that from Cargill or Archer Daniels Midland or Chevron or Exxon. They won’t innovate because they don’t really care as much about the mission of a sustainable planet, despite their proclamations and Madison Avenue ads saying the contrary. And this disruption may disrupt their income statements. To be fair, anything else goes against their promise to their shareholders.

Do you think you could have innovation outside of this region? The one thing to realize is innovation can happen anywhere and everywhere. It is much more about the mindset and a culture than it is about a place. What makes it harder in other places is that when somebody innovates, they don’t get that support around them. Silicon Valley is different. I’m sorry to say if you have been fifteen years at Hewlett-Packard or Cisco, you’re not qualified to do any important job in the startup world. Every other part of the world people say “Wow, you work for GE or Citibank!” Here, they say “You’ve been working for GE and Cisco for fifteen years?” You’re not hirable by anybody trying to really experiment and innovate. You’re not qualified in any way if you’re at Cisco for fifteen years, or IBM for fifteen years, or Cargill for fifteen years, or United Healthcare for fifteen years. Again, it’s the mindset that enables new ideas or new tools for testing that creates the disruptive innovation that matters. Here too much experience can be a handicap.

I have gone through an exercise of trying to just see if I could find a large innovation coming out of big companies in the last twenty five years, a major innovation (there’s plenty of minor innovations, incremental innovations that come out of big companies) but I couldn’t find one in the last twenty-five years. You look at retail, did Amazon innovate this or Walmart? Media: Did ABC, NBC, CBS do it or Twitter/Youtube/Facebook? Did Boeing or Lockheed innovate space or SpaceX? Did GM which started early in electric cars and spent more money change cars or Tesla/Waymo/Uber? Did Wells Fargo or Bank of America change financial services or did Square/Stripe/Affirm do that? Did IBM change computing or Sun/VMWARE/Amazon AWS? Yes, the credit card 40–50 years ago was “credit on plastic” was the largest existing company, “barely large innovation” I could come up with though I am sure there are a few others. No, 3M does not qualify with the yellow sticky in my view.

18. Conclusion

The way to look at the world is seven hundred million people or so on the planet have a rich lifestyle. It’s energy rich, it’s resource rich, it’s healthcare services rich, it’s transportation rich, it’s a rich lifestyle. Seven billion people want it. Can we do ten times as much of everything the same way? The obvious answer is no. Technology is the necessary, albeit not sufficient, resource multiplier. It is the only thing that can multiply resources. Now, politics can still screw all that up, and that’s why I say technology is necessary and the only thing that can multiply resources, but it is not sufficient. Social, political and cultural issues matter immensely. This is why I am so bullish about the role Silicon Valley can play in meeting social needs. And it’s fun to do and do it in a non-institutional way, meaning CitiBank won’t solve financial inclusion, Square will. If anybody does it.

The vast majority of U.S. jobs in 1900 were in agriculture. By the year 2000, it was approximately two percent of all jobs, so most jobs got displaced. I have recently looked at the top twenty job categories in the United States, and it was very clear that at least fifteen of them will have more than fifty percent of the jobs replaceable. I cannot say with precision whether it will happen in twenty-five years or fifty years. It depends on which entrepreneur takes it upon themselves to go innovate that job category. Such dramatic social change will render all the economic metrics that everybody in Washington pays attention to, “mostly meaningless but looking great”. And it will feel very painful to the people who are affected as this The Next Technology Revolution will Drive Abundance and Income Disparity. That’s the inclusiveness part. This is what worries me about technology. I’m a technology optimist, but there are consequences and side effects that aren’t great — that we should all worry about. We will, however, have the resources to address them adequately.

It is important to note the cautions here. There is extreme variability in the timing and even the nature of the innovations that will emerge. There is also a huge path dependence based on when, who and why they innovate and that may cause the end result to be different. There are all kinds of entrepreneurs with good, bad and indifferent objectives in Silicon Valley. Who does what matters to where we get.

There are a huge number of unknown unknowns in this speculation (and yes it is all speculation, not forecast). Almost certainly this document will look naive in twenty five years. But the biggest of the big unknowns is artificial intelligence (AI) and even more so artificial general intelligence (AGI). I have had intelligent people forecast it as 5–10 years away and others say 10x that time. Personally, I’d peg that at the boundary of this document or around 5–10 cycles of 2–3 year individual innovation cycles in AI. That could change everything. It may only need a few hardware breakthroughs to scale computing 1000x or it may need many years of software invention. Regardless, when it happens it may be impact equivalent of a 100x nuclear-like technologies (again for good and evil!). And unlike nuclear it may not be verifiable as to who has what technology. The world would be very dramatically different. In short time we may need to adjust capitalism which was designed for economic efficiency to a new era of abundance, concentration of power and much more of a winner take all world. Life will be very, very different. Fortunately, capitalism is by permission of democracy and I hope that the means to reduce disparity and minimum living standards will be taken advantage of by societal choices.

If there is a 90 percent chance of failure on a transformative project, then we have a 10 percent chance of transforming the world. That’s pretty great. If ten such fusion projects were attempted, we would possibly change the world. And if we have ten attempts (or a hundred) each at many different areas covered in this essay, we will really change the world. Change and innovation will be technology driven, non-institutional, breaking the rules, all radical approach. Let’s not throw the baby out with the bathwater when things go wrong but instead focus on net societal benefit. And in this non-institutional way of doing things, though less predictable, it is way more exciting. It is probably the main way we will get to getting seven billion people the kind of lifestyle they’d all want.

As Yogi Berra said “It’s tough to make predictions, especially about the future,” but if there is an answer, this speculation is more likely to be right than any other single prediction.

On a more personal note, I’m going to keep making mistakes, because I’m speculating on a lot of things and then backing them. My willingness to fail allows me to succeed. And if I was too afraid to fail, I wouldn’t try the things and I would, well, fail to try, instead of trying and failing. There’s a world of a difference difference between those two. I think most people fail to try and so they never fail, but in my view, they always fail, because they fail to even attempt something. It is a really important cultural difference.

Another thing you learn in our business is humility. How often you’re wrong. The best of you entrepreneurs (I’d love to see a large institution prove me wrong on my mostly non-institutional reinvention thesis) work on these kinds of problems, and that’s what’s so exciting to me, that is what keeps me motivated. That is why I am working eighty hours a week at age sixty two. I get so much flack for believing machines and systems can do medicine better than humans. However, that’s just one of many. Or that most jobs will be replaced or fusion energy is possible in my lifetime or that AI can make work an option for most people who will work if they want to work, but not need to work because we will have sufficient abundance. It may or may not work but these ideas are worth attempting. Imagine the possible!

To elaborate more on founders — if you don’t have strong religious beliefs about what you’re trying to do, you tend to not succeed. So, you have to be totally obstinate about your vision, but flexible about your tactics. Most founders don’t get to their vision in a straight line. It zig-zags, goes left, goes right, survives long enough, evolve, get lucky. No one has yet reached Everest without getting to multiple base camps. So while being obstinate about one’s vision, one has to be flexible on one’s tactics. A pragmatic visionary so to speak in a world where most people are one or the other. And above all luck plays a huge part of success, and good founders give themselves multiple shots on goal. You want founders to think flexibly, listen but not be agreeable with everybody who gives them advice.

This reinvention will be chaotic, disruptive, unpredictable with many failed attempts but failure won’t matter; successes will. Media folks will have a field day with stories of hubris, missed or misled expectations and failure. The disruption will be temporarily painful to some as being disrupted is never fun. We have to get things right and meet society’s expectations of technology to help equality, diversity and more. New technologies also rock the world by reallocating power and wealth and accentuating inequality. Fortunately, capitalism is by permission of democracy, and the electorate will have the ability to rectify the inequalities. All these social factors will become urgent and critical to enable this transformation through democracy and to be fair to the people who will be impacted. It’s impact in the less democratic societies is harder to predict.The future is not knowable, but it is inevitable and inventable so we need great entrepreneurs and technologists to invent the future now.