The Shapes of 21st Century Stories
Once upon a time, during the production of The HUMAN Project book and app, Juan Ciapessoni from Uruguay volunteered his team at the innovation powerhouse The Electric Factory to help us across the finish line. A friend in need left quite an impression and a trail of gratitude. So when Juan asked me to come to Uruguay to speak at Desachate 2017, the local advertising industry’s annual conference, I gladly agreed. I had an hour (!) and a carte blanche to have fun DJ-ing all the things that are currently on my mind. The talk turned into an exploration of technology-driven narratives that have the potential to bend the arc of human history this century and mess up our personal lives: AI, robots, AI+HI, longevity and space settlement. Below are my non-polished talking notes. Presentation slides are here.
No Browsing, No Milk
My mission today is to feed your cow.
I don’t make, buy or consume much advertising. I stopped watching TV 15 years ago because…ads. I block them on my browser. I press the skip button the very instant the 5 seconds are up on my YouTube videos. Yet, there is a wormhole that connects me to the world of advertising: I was radicalised by an ad man. It all started with a little book “A Technique for Producing Ideas” by James Webb Young, a quintessential American ad man who died before most people in this room were born. It takes just 30 minutes to read but that’s all I needed to become a religious generalist. I blame Mr. Young for all the troubles I got myself into since.
The book’s thesis is simple: the production of ideas is as definable a process as the production of Fords: there is an assembly line and there is a method and principles you must follow. The first principle is that an idea is nothing more than a new combination of old elements. The second principle is that your capacity to bring old elements into new combinations largely depends on your ability to see relationships. The method consists of 5 simple steps. Today I’d like to focus on the first one: relentless, obsessive gathering of raw material. There are two types of raw material you must gather: the specific and the general. I can’t help you with the specific. But I can certainly add some raw material to expand your general knowledge of some of the big technological stories that could define the century we live in.
Back in 1939, Mr. Young described creatives as follows:
“Every good creative person in advertising has always had two noticeable characteristics. First, there was no subject he could not easily get interested in…Second, he was an extensive browser in all sorts of fields of information. For it is with advertising as it is with the cow: no browsing, no milk.”
Many things have changed in advertising since 1939 but I am banking on the assumption that this particular observation is as true today as it was almost 80 years ago and you are all interested in browsing. So let’s eat some grass.
The Tool for Discerning Story Shapes
On the menu today are five themes:
- Artificial Intelligence (AI)
- Robot Revolution
- AI + Human Intelligence (HI)
- Space Settlement
For desert, we’ll look at how these things could mess up the shape of your own life.
The subject matter is somewhat technical, so we need an advanced analytical tool to make sense of it all. I’ll summon another dead eccentric to give you a primer. The man is an American writer Kurt Vonnegut, known for his many profound insights including this one:
“I tell you, we are here on Earth to fart around, and don’t let anybody tell you different.”
I’ll let the master introduce our story shaping tool:
To reinforce the acquisition of this complex tool, let’s do a couple more stories:
A young man is rather unattractive, not particularly fun to be around. His relatives are no fun either. His career is going nowhere. He doesn’t get paid enough to take his girl dancing or to go to the beer hall. One morning he wakes up and turns into a cockroach. It’s a bummer of a story.
My life story
So far insect free. The central plot is a girl’s quest for meaning and, as you can see, she is steadily bumping upwards.
Solid start: the girl has a happy, carefree childhood in Estonia, then a reluctantly Soviet Republic behind the Iron Curtain. She plays tennis, plays chess, is a good student, has few deep friendships, listens to death metal and stays out of trouble.
Politics: Her quest for meaning kicks off with political philosophy. The Iron Curtain falls and the teen promptly gets hooked on the idea of individual liberty and becomes a Libertarian. Reads Hayek, Mises, Rand, all the usual suspects. Interns at the right-wing policy think tank in Washington, DC. Advocates for the privatisation of social security. Travels the world. Meets lots of passionate people. Loves it. Until one day — surprising to no one but herself — the girl grows up, realises that she voluntarily locked herself into an echo chamber with a libertarian-shaped keyhole on the world while all she ever wanted was to be a free-range chicken. So she gets out but loses most of her caged libertarian friends in the process — that explains the downward slide.
Career: She turns her attention to career in management consulting. Has 6 amazing years. Learns a lot. Travels the world. Meets lots of smart people. Loves it. Until one morning, she wakes up and feels her work is empty and meaningless. So the girl gets out but loses most of her McKinsey friends in the process.
(Non-)Enlightenment: The girl decides to pursue spiritual enlightenment. She studies with philosopher kings and Zen Masters. Spends years sitting on the cushion. Learns a lot. Travels the world. Meets lots of spiritual people. Loves it. But in the end, she doesn’t want to shave her head, her bottom is getting sore from all the sitting and she is itching to make herself useful. So the girl gets out but loses most of her spiritual friends in the process.
F*ck entropy: To make herself useful, the girl tries to first figure out what the human civilisation really needs. Spends 5 years researching the most important global challenges. While immersed in research on the global risks faced by humanity, comes across the following thoughts in a chapter on long-term astrophysical processes in an otherwise brilliant volume on Global Catastrophic Risks (2008):
“Our particular world is …likely to end its life in fire. … For the universe as a whole, the future is equally bleak, but far more drawn out. …the cosmos as a whole, is likely to grow ever colder and face icy death. … Ashes to ashes, dust to dust, particles to particles — such is the ultimate fate of our universe.“
First the girl gets supernova angry. What kind of defeatist attitude is that? So we face a little heat death of the universe gazillion years from now and we just throw in the towel? Then she gets black hole depressed: If this whole cosmic sitcom ends anyways, what’s the point of anything? After weeks of the darkest existential despair (waking up as a cockroach starts making sense on some mornings), she emerges defiant and resolute: F*ck entropy. All problems are soluble, so why let a little heat death of the universe spoil a perfectly lovely Tuesday? Right there and then she decides to spend the rest of her life fighting existential risks, no matter the odds. No other path makes any sense.
Space robots: She thinks making life multi-planetary is a no regret, grownup move towards reducing near term existential risks. Since ULA, Elon Musk and Jeff Bezos already have the rockets covered, together with her co-founders, she focuses on the next big thing: robotic workforce to do the heavy lifting required to jump-start outposts on the Moon and Mars. It’s a start.
This story does not have an ending, it’s still developing. If the girl lives as long as her great grandmother, she still has another 60 years to muck about. So many different endings are possible.
Shapes of the 21st Century Stories
All of the stories we are going to investigate next are also developing stories with definite beginnings, some really intriguing middles but no pre-determined endings. That’s what makes these stories such a nerve-wrecking fun.
STORY #1: ARTIFICIAL INTELLIGENCE
The story of Artificial Intelligence so far is a tale of three waves:
1st Wave: Rules-based AI. The first wave was all about arming AIs with human-made knowledge. Want to play chess? Here are the rules of the game. Want to translate? Here is how to make a sentence and here are the rules of grammar. This simple approach produced several useful things like chess playing AIs, logistics and scheduling AIs, tax filing AIs and even divorce negotiating AIs. But it also ran into the problem of the limits of abstracted knowledge. Here is an example. During the Cold War, Americans were trying to use AI to automatically and instantly translate documents and scientific reports from Russian to English. Here is what a rule-based AI did when you translated from English to Russian and back.
This AI lacked common contextual understanding, it wasn’t capable of dealing with new situations unforeseen by the rules, it wasn’t capable of learning anything. This realisation led to the beginning of the first AI winter — a prolonged crash in government and VC funding.
2nd Wave: Statistical Black Box Learning. In 2004, DARPA ran its first Grand Challenge where 15 autonomous vehicles were supposed to complete a 150 mile course in the Mojave desert. All the teams used rule-based AI and none of the teams completed the course. The vehicles did not understand the world around them, they could not distinguish a far away rock from a shadow of a cloud. As the Grand Challenge deputy program manager said, some vehicles “were scared of their own shadow, hallucinating obstacles that weren’t there.”
Statistical learning to the rescue! Ideas underpinning the current buzz around statistically learning AI was inspired by research into the microscopic structure of the brain by the father of neuroscience Santiago Ramon y Cajal at the turn of the last century.
The drawings of the first neural nets used to do statistical learning looked remarkably similar.
The big idea here is not give AIs any rules, but train algorithms on mountains of data, let them find patterns and infer their own implicit model of the rules that underpin the patterns. The wind powering this wave was the dramatic increase in access to cheap computing power and the fact that we have generated a ridiculous amount of digital data that could be used for training our neural networks. We could now cheaply unleash our neural nets to chew through millions and billions of data points to learn what a cat looks like, translate or drive autonomously.
In the second DARPA Grand Challenge, five of the participating teams used these statistically learning AIs and made it to the finish line. So far these AIs can outperform humans at face recognition, speech transcription, identifying objects and animals in pictures. They are starting to do pretty well at translating, driving cars and flying drones. The dark side of these AIs is that we don’t understand the models the construct based on the data we feed them — there are too complex for us to understand. Furthermore, what they learn completely depends on what data they see. Case in point: Microsoft’s twitter bot called Tay.
Tay was meant to learn the slang of American teenagers…who promptly proceeded to prank Tay with fun suggestions like 9/11 was an inside job, Hitler was a great man, immigrants are the root cause of all evil in the US. After a few hours of this “education”, Tay turned into a Hitler’s surrogate, and tweeted such pearls as “bush did 9/11”, “Hitler would have done a better job than the monkey we have now” and “Donald trump is the only hope we’ve got.” Microsoft had to shut Tay off.
The misadventures of Tay aside, the second wave AI has been seriously successful. It is like air, it’s everywhere. Thousands of AI applications are deeply embedded in the infrastructure of every industry. Just in our personal lives, statistically learning AI powers our Google searches, serves us recommendations on Netflix and Amazon, targets ads, tags photos and curates our newsfeeds on Facebook. It’s behind all translation apps. It animates an army of chat bots and personal assistants from Google Now, Microsoft’s Cortana, Apple’s Siri, Amazon’s Alexa and x.ai’s Amy. Watson’s IMB can even do something as important as diagnose cancers better than humans. Several AIs are on the road, learning to drive. They are also trying their hand at creative direction for ads. Weaponized AI propaganda machine has contributed to Brexit in the UK and the election of Trump in the U.S.
3rd Wave: Contextually Aware AI. The third wave takes us straight to the present moment. It’s not yet a real wave, more of a twinkle in the eyes of select AI researchers. The big idea here is to create an AI that can construct explicit models to explain how the world works and then apply these models from one context to another, learn pretty much how we humans learn today.
If you look at this picture of our browsing cow, wave two AI would look at it and say “there is a 92% probability this is a cow.” But it would not be able to explain how exactly it came to this conclusion. Our future wave three AI would take a look at the picture, identify it as a cow and will be able to give a coherent explanation, e.g.,
· The object of interest has four legs, so probably an animal.
· The body is black and white spotted, so higher probability it’s a cow.
· The animal has udders and hooves, so almost certainly a cow.
· And then it would probably crack a joke about how cows are like admen — no browsing, no milk!
Third wave AIs would be using several statistical models, or potentially a hybrid of rules-based and statistical models. They would be able to relate data from various domains and put the bigger picture together. These AIs would be able to teach themselves, think abstractly and even reprogram themselves.
Pushing the second wave AI and developing the third wave AI are all multi-billion dollar efforts at the Silicon Valley’s tech titans and thousands of startups, each following the same formula: “take X, just add AI.” Everyone sees the chance to make money on getting the most out of customer data, putting self-driving cars on the road and finally getting to the nirvana of predictive medicine. Some say these days are reminiscent of the early internet days, with research laying the foundation stones for new industries.
Where this story goes next depends on who controls AIs and whether they can be controlled at all. Here are two potential endings to this story:
Game Over or Slave-God?
Game over: Bill Gates, Stephen Hawking, Nick Bostrom, Elon Musk started ringing the alarm bells a couple of years ago because they believe we are “summoning the demon,” creating the means of our own destruction. They see advanced AI or super-intelligence engaged in recursive self-improvement as a human-made existential risk that would wipe out humanity, whether intentionally (like you would not hesitate to squash an annoying mosquito, quite a few of those in Uruguay!) or unintentionally while pursuing some other goal where humans happen to stand in the way (e.g., the most effective solution for eliminating spam mail is to eliminate humans). If you think about it, given how dependent we are on our digital infrastructure, a runaway algorithm that lives on the net could actually do quite a bit of damage, e.g., it could take over the control of our power systems, autonomous weapons or turn fleets of self-driving cars into kinetic weapons. You can see how this can go terribly wrong.
Musk is not just seriously worried, he is putting his money where his fears are: he started investing in AI just to keep his eye on the arc of this story and more recently, he co-founded a billion-dollar non-profit, OpenAI to ensure we take the safer AI route. It’s now a 50-people outfit turning out useful research. Musk’s strategy here is to try to get to super-AI before anyone else and then distribute the tech to the world. This is one way to make sure that master algorithms are not concentrated in the hands of the few tech titans or government elites. And if an AI goes rogue, you’d have a human-controlled AI collective to stop it. On the other hand, many people in the field see these fears as a bit hysterical and entirely premature, like worrying about over-population of Mars. In January 2016, Musk and Stephen Hawking won a Luddite Award for their AI alarmism.
Slave-god: At the other end of the story-ending spectrum, we succeed to develop super-AI and that’s pretty much the last invention we ever have to make. We retain full control of our creation and it becomes our #1 problem solving tool that accelerates the speed of scientific and technological progress and pretty much solves every problem we ever encounter. Demis Hassabis is charging full speed ahead at Google DeepMind, running what he has described as Apollo program for AI. Facebook’s Yann LeCun says they have got this. Google’s Ray Kurzweil is predicting that we are barely 28 years away from Singularity, the moment self-improving AI exceeds human intelligence — after which point it becomes impossible for us mere mortals to predict what’s going to happen next.
Elegant arguments have been constructed in favour of both endings. Personally, I am too close to the grindstone and too unconvinced our current track will take us to super-AI to be able to take the game-over scenario seriously. At the same time, if the game-over ending has a non-zero chance of materialising, we must take it seriously. We can’t afford to kid around with a potential existential risk.
STORY #2: ROBOT REVOLUTION
So far we have been talking about AI without a body. A disembodied AI can do a lot of damage, but it won’t be able to make itself a cup of Turkish coffee and throw it into your face because it finds your joke offensive…which brings us to our next story.
We have been dreaming of artificial servants and companions for thousands of years. In 322 BC, Aristotle wrote in Politics that automatons could someday make it possible to abolish slavery and bring about human equality:
“There is only one condition in which we can imagine managers not needing subordinates, and masters not needing slaves. This condition would be that each instrument could do its own work, at the word of command or by intelligent anticipation.”
Since then humans have created plenty of mechanical machines that automated lots of tasks. However, if we define a robot as a machine that has some degree of awareness of its environment and ability to choose its course of action based on its reading of the environment, then this story is only starting now. The current population of industrial “robots” globally is approaching 2 million, working in cages in factories around the world. But as recently as 2016, 90% of these so called robots had no sensors — this means they are as aware of their environment as your toaster. In other words, these are not real robots, but souped up, high precision, digitally controlled automatons.
A small but rapidly growing population of real robots work in Amazon’s warehouses, snap birds’ eye pictures, drive on the roads and now sidewalks to get you your takeaway or groceries . We are at the very beginning of migrating our statistically learning AIs into physical bodies. But you can already see how these real robots could make our lives a whole lot more interesting.
Robots’ pets or wabi-sabi work?
Robots’ pets: Let’s start with the potential unhappy ending. We could become boot-loaders for robots. A boot-loader is the small program that launches the operating system when you turn on your laptop. If we combine super-AI with dexterous bodies, it’s not hard to imagine a scenario where humans become the biological boot-loader for digital super-intelligence. If all goes well, we’ll become robot family pets. I suppose it’s better than being a cockroach but probably not by much.
Wabi-sabi work: If disembodied AIs can take over all the digital work, AIs with bodies could eventually take over all work. And we are not talking remote future here. Robots are expected to be capable of doing almost half of all human jobs today within 20 years. Is that a good thing or a bad thing? In the short-term, it won’t be pretty. It could turn out to be more disruptive than the transition from agriculture to manufacturing in the early 20th century.
If we survive the short term without robot smashing, then in the long run it’s probably a good thing. If we handle it wisely (have we ever?), this development could conceivably usher in that human equality Aristotle was talking about. At the very least, we’ll certainly need to seriously start thinking about that idea of universal basic income or universal basic services. Imagine for a second that none of us need to worry about working for a living. We’d be free to re-imagine what makes a good, meaningful life if you don’t have to work for a living, what it means to be human. In many ways, the bar goes up. If our super-intelligent robots can learn everything that could be learned statistically, create all ideas that can be created by combining and testing every possible combination of pre-existing elements, what does that leave for us mere mortals? Wabi-sabi.
That’s what the Japanese call unique, handmade things that are perfectly imperfect, the opposite of precise, sterile, uniform products made by machines. Humans could make wabi-sabi ideas, artefacts and relationships. But of course, the second you made your wabi-sabi anything, it goes straight into the AI’s data set and sooner or later they find patterns in uniqueness. And the bar is raised higher again! So what’s that thing only you can do?
STORY #3: AI+HI
We’ve been augmenting our own intelligence with external devices and constructs for centuries: language, writing, abacus, printing press, scientific method, the internet. Our phones and laptops are extensions of who we are and what we can do. But the interface is external and a slow as we have to use fingers or speech.
So a big idea that was first floated back in the 1950s and 1960s by the cybernetics pioneers was to use information technology to directly augment and amplify human intelligence. In the words of J.C.R. Licklider, the author of the seminal Machine-Computer Symbiosis (1960):
“The hope is that, in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.”
These ideas were also developed by Douglas Engelbart, the quintessential visionary of the computer age who gave us the mouse, hyperlinks, and dozens of other inventions we now take for granted. Engelbart thought of intelligence amplification as almost universally relevant increase in capability:
“…more-rapid comprehension, better comprehension, the possibility of gaining a useful degree of comprehension in a situation that previously was too complex, speedier solutions, better solutions, and the possibility of finding solutions to problems that before seemed insolvable. And by complex situations we include the professional problems of diplomats, executives, social scientists, life scientists, physical scientists, attorneys, designers — whether the problem situation exists for twenty minutes or twenty years.”
Many in the field viewed the quest for Artificial Intelligence (the creation of independent agent) and Intelligence Augmentation (making humans smarter) as being at odds with each other. If we truly succeeded at augmenting our own intelligence, why would we even need AIs?
The devil is of course in the detail — how do you connect the human brain directly with our computing systems? We have dozens of amputees and paralyzed people around the world who can now control robotic arms by thinking. This miracle requires implantation of electrodes into patients’ bodies. Somewhat less invasively, we can now scan people’s brains while they are watching movies or looking at faces and reconstruct what they are seeing.
Last year, a tech entrepreneur and visionary investor Bryan Johnson invested $100M in Kernel. The original goal of the company was to develop a memory implant to help restore cognitive function to people with debilitating brain diseases and then move on the intelligence augmentation. Turns out it’s not easy, so six months later Kernel changed the team and its scientific advisors and pivoted to developing a more general-purpose technology for recording and stimulating the brain using electrodes, intended to treat depression and Alzheimers. It’s a “15 year endeavour”.
Facebook is running a secretive project in Building 8, after hiring a bunch of neuroscientists and Zuckerberg declaring that people should be able to share not just pictures but also “full sensory and emotional experiences.”
In the meantime, Elon Musk sees the merger of artificial and human intelligence as a way for us to escape becoming irrelevant. He has been talking up the idea of neural lace — an injectable mesh that would physically hardwire our brains to communicate with computers. With our brains neurally laced, we would be able to upload and download data to and from the AI cloud that would have virtually unlimited computing power. In Musk’s opinion, we are four to five years away from “a meaningful partial-brain interface.” After teasing his fans with talk about neural lace, Elon Musk recently announced that he has invested in Neuralink. We won’t know what Neuralink is exactly working on until next week.
Interfacing with the brain is tough and has a laundry list of problems that need solving (nice piece on the key issues here). Electronics and brain tissue were not made for each other, the tissue gets irritated and after a while electronics stop working. Even if you crack the interface problem and can communicate directly with the brain, we don’t yet know how to read all the brain signals. And last but most certainly not least, few people are willing to have their skull cracked open just to be able to send an email or switch on the lights in the house with the power of their thoughts.
Our cyborg future: So don’t count on shocking your parents with the whole cyborg thing next Christmas. But give it time and there is really only one logical ending to this story: most of us will eventually be cyborgs. All of us will be Star Trek’s Seven of Nine. We might have our brains “neurolaced” courtesy of Mr. Musk. Or as Google’s Ray Kurzweil predicts, we could have nanobots the size of blood cells connecting us to synthetic neocortices in the cloud by 2030s, giving us access to virtual and augmented reality from within our own nervous systems. So expect a funnier, wiser, more musical, more everything you coming to you in a mere 20 years. If the guy next door is suddenly acting as the guy from the movie Limitless, would you not also be tempted?
STORY #4: LONGEVITY
If God came up with biological evolution, he must be a lazy/clever fella but not particularly considerate. The lazy/clever part is that he automated creation. Instead of needing to create every life form himself, he just defined the rules and let the program run its course: Core designs are in the DNA, each time a life form reproduces, DNA is copied imperfectly with all sorts of random genetic errors. Some of these genetic mutations turn out to be useful and allow its carrier to live long enough to reproduce and pass the mutation to future generations. Mutate, reproduce, die, repeat. An voila, that’s how you get from a couple of single cells to 5–50 billion species that have ever existed on Earth. The inconsiderate part is the dying. This whole pyramid scheme is built on dying — lots and lots of dying. Of course, God is rumoured to be immortal himself, so that guy has no clue what it feels like to die. He just doled out random life spans left and right. Bowhead whale — 200 years, giant tortoise — 100 years, dog — 12 years, bumblebee — 28 days.
For most of human history, our average life expectancy was 30–40 years. Since 1800, we have doubled it in the developed world with a few clever hacks: we slashed child and mother mortality, took on infectious disease with hygiene, antibiotics, and vaccines, dramatically improved nutrition and finally quit smoking. The human who has lived the longest so far was, ironically, a chain smoker Jean Calment who died at 122.
So today, we are in this interesting place where average life expectancy is above 70 and, in some places like Japan is edging closer to 90. When Social Security was introduced in 1935 in the U.S., life expectancy was 60. The retirement age was set at 65 to keep the few survivors out of extreme poverty. But now all the long-living baby boomers have the expectation of several decades of sunny retirement. Average retirement age is 62 and life expectancy 79 — the model is unsustainable. Some companies are already dropping retirement age requirements, others are offering “returnships” to retired employees looking to re-join the workforce.
There is still a mountain of work to do to close the life expectancy gap in the poorer countries. But at the leading edge, the battle of clawing extra years of healthy life from Jack the Ripper is getting harder. We have picked up all the low hanging fruit and are now up against a tricky enemy — aging itself. Aging is like a game of wack-a-mole, you wack heart disease but then cancer or Alzheimer’s pops up. Evolution does not really care about us once we have had our babies. It’s all downhill after 40 — wholesale increase in frailty. Billions of dollars are now being poured into understanding the mechanics of aging and ways to slow it down.
So where does this story go from here? This story only gets seriously interesting if some of the research dollars start making a difference in humans, not just extending the lives of lab mice and C. Elegans.
If we keep extending life at any cost but all these years are just extra years of disease and disability, some fear our society will turn into “a giant nursing home.” Think lots of unhappy sick old people. Then add a few healthy younger people who too are unhappy because most of their savings and tax dollars are going to support everyone’s grandmas and grandpas while their own future is looking increasingly bleak.
Alternatively, we could crack aging and head to “90 is the new 60” scenario. It could get even weirder. For the last 175 years, life expectancy has been increasing at 3 months per year. Now imagine if we made a leap and quadrupled that rate, so now we add one extra year of life per year. All of a sudden, we reach an “escape velocity” where you can live indefinitely, unless you get blown to pieces by an exploding car battery, or your self-driving car gets you in a deadly accident.
There is also a tiny chance that we end up somewhere in the middle, on ice — cryopreserved indefinitely, until scientists figure out how to solve your particular fatal disease.
STORY #5: SPACE SETTLEMENT
Expanding our presence to Mars is not going to save us from demonic AI, if that scenario came to pass (they’d just find a way to follow us there), but it can certainly protect us from several other existential risks that could decimate our civilisation on Earth — an all-out nuclear war, global pandemics, asteroid impacts, super-volcanic eruptions.
We’ve been dreaming about going to space forever. But the real action did not start until mid-last century — courtesy of World War II and the Cold War arms race. Our prime reasons where what they were but that does not make the accomplishments of the Apollo program less magnificent. 24 American men flew to another celestial body and 12 of them walked on the surface of the Moon! How amazing was that? And can you believe it’s now such ancient history, most people in this room weren’t even born yet when it happened.
Inspired by the out-of-this-world success of Apollo, people dared to dream:
“The year 2000 is approaching fast… every job on Earth will have its match in space… should you decide to take a job in space, picture yourself riding in a Shuttle to work… by the turn of the century, look to permanent bases on the Moon, trips to Mars, and full-sized cities in the sky. The Space Age will have truly arrived!” — From The Cheerios Space Shuttle Adventure Kit, 1981
But instead, what followed was 42 years of very little. This brings us to the present moment. Here is what we’ve got in the inner solar system: 6 to 9 people live in a tin can that orbits Earth some 330–435 km above our heads. So far about 560 people been up there in low Earth orbit. We have one poor frozen Chinese Jade rabbit robot on the Moon. We’ve got a diseased Spirit, a diseased Opportunity and one active Curiosity rover still driving around and snapping beautiful pictures of blue Martian sunsets. That’s all we’ve got in terms of boots on the ground right now in the inner solar system.
But you can definitely smell hope in the air again! Our resident alien, Elon Musk is building Mars Interplanetary Transport System and is hoping to start with a dozen of people and over 100,000 flights build up to a million strong self-sustaining settlement. UAE wants to build a city on Mars in a hundred years. Jeff Bezos is talking about having millions of people living and working in space. China is relentlessly moving ahead with its impressive development of lunar capabilities.
Space enthusiasts certainly have a giant black eye from the previous attempts at predicting how this story ends. But that won’t stop us from trying, again:
Lunatics & Martians: So let’s imagine for a second that we manage to establish a foothold on the Moon where we mine polar ice for rocket propellant and water, and use it as our test lab for Mars missions. We could even have a couple of Bigelow’s hotels for extreme tourists. Make no mistake, the Moon is no lunar park. It’s barren and low gravity and high radiation and without an atmosphere, and covered in extremely abrasive regolith and the day lasts 14 Earth days and the night last as long while the temperatures swing wildly. So if you go as a tourist, your lunar trip would make a trip to Antarctica feel like a five star luxury tropical getaway in comparison. So make sure you read the small print when you book your next lunar adventure. There is a reason why lunatic means what it means. And while we are at it, let’s be clear that Mars would only be marginally easier because it has a modicum of atmosphere and gravity closer to Earth’s but you’ll be eight months to two years away from the next resupply ship. So make sure you bring all your Mars bars. But all in all, this could be not an ending but an amazing beginning of our expansion in the solar system and beyond.
Less than a status quo: Or not. An equally plausible alternative is that the smell of hope evaporates yet again. Musk gets hit by a bus, ULA goes bankrupt and Bezos gets an early onset of dementia and forgets to fund his magnificent rockets. These things happen. And to make things worse, NASA, ESA, JAXA and the Roskosmos decide to discontinue their collaboration on the International Space Station, find no commercial buyers and plunge that giant tin can into the Pacific ocean. The Chinese with their methodical, stead-fast approach to developing space-faring technology would then be our only hope. If you want to visit the Moon or retire on Mars, start learning Mandarin now.
“Black alien”: Last but not least, there is always that mother-of-all black swans ending — the first contact with an intelligent extra-terrestrial civilization. Whether they drop by our place, or we spy them with our little telescopic eye at their place, it would be a mega plot twist in the space settlement story. With no intel about the Other Guys, it’s impossible to predict whether it would be good or bad for us. The only thing we can say for certain: it won’t be boring.
YOUR LIFE STORY
If we overlay the above five story shapes of the 21st century (which are, let’s be clear, only a subset of everything that is going on), the range of outcomes varies wildly, from our self-destruction to the conquest of the universe. It’s the ultimate cliff-hanger where we and our offspring are doing the hanging.
So what does this mean for the story arcs of our own lives?
It’s probably safe to guess that most of your stories started at the end of last century. On average, our lives have been steadily improving: internet, smartphones, affordable flying, Ubers and Airbnb’s, wars are down, “job-for-life” is gone, marriage for life and nuclear families are gone. You can now afford to be depressed about it all — which is its own form of good fortune that could serve an evolutionary purpose. There are of course dark clouds on the horizon (no moment in human history is ever cloud free!): climate change and environmental destruction, terrorism, and, depending on your political views, Brexit and Trump.
So how would all the developing stories we have discussed so far affect the most important choices we make in life — purpose, work, spouses, habitats? If we start from the end: you won’t be retiring any time soon, if at all. You have 50–60 years of active life, with most of it still ahead of you. So what you are going to do with all this time? You probably have enough time for three or four different careers, gaps for raising family, traveling the world or two (Moon and Mars might soon be on the list of destinations). Most of the career choices you have today are tricky. Most of what you do today will probably be grabbed by AIs. So you’ll either need to become a grand master of the Unique and the Unpredictable, or you will be very bored. Maintaining “life course flexibility” will be important. Relationships could morph into time limited, renewable marriages. You may face some fun choices about self-augmentation.
Save for major victories in the fight against aging, all of us die at the end of this story. But it need not be a tragic story:
(1) You can of course bob around, and have a meh-life. Most people do. And no one has ever heard them complain after they pass on.
(2) You can pull a Don Quixote: rage against the dying of the light, take on giants with terrible odds of prevailing and with a very real risk that your giants turn out to be just windmills. It makes for a fun story though!
(3) You can focus on making a dent in the universe, doing something monumentally good. The process is exhilarating, like eating glass or falling into a black hole. But if you have a shot at bending the arc of human history towards greater collective good and beauty, then it might be worth it. In the words of Dr Ford from TV series Westworld: