When I share that you need to prepare for the end of times as we know you may laugh. I’m agnostic so I’m not going to preach any religion or end of humanity due to any religious factor but our own technological advance, I think things will change way more rapidly that you think and I’d like to prepare myself and share how I think you, me and our kids will be part of this new future.
What to do? I can share that three areas have a higher chance of making good preparation for you and your children:
- Get professionally involved in creative endeavors with social interactions, or,
- If you find a way to get paid by anything where your body or mobility is the product, you will be fine for a while.
- Last option is become entrepreneur and specialise in leadership, sales, negotiators, caretaking, nursing, or teaching.
If you don’t do this unemployment will reach 95% by 2075 and what will your kids do? It sounds insane but it will happen and I’d like you to prepare for it by at least reading about the topic and shaping your opinion. In 2013, Vincent C. Müller and Nick Bostrom conducted a survey that asked hundreds of AI experts when the moment of artificial intelligence reach the level of human intelligence and the pessimistic scenario was 2075.You can debate with me on the timeframe between 30 and 60 years but if you respect people like Elon Musk, Bill Gates and Dr. Stephen Hawking and you wonder why 1 billion US dollars were put into a new company OpenAI some weeks again. A company that open sources artificial intelligence advances, you should read on.
You think computers are stupid and think that the self-driving car will take decades to make an impact on your life and you think you can can ignore it by changing laws to forbid these advances you are wrong. Let’s get into your brain just a second. For that I’ll borrow a big chunk of this awesome article by Tim Urban, that you have to read.
Why We Are Bad Predicting the Future?
You can hardly predict the future you say so why try? Well you are right but you can kind of oversee the future of your own work domain for the next 2-3 years, so when asking hundreds of AI experts (I guess not your field of expertise) say as early as 2022 and as late as 2075 we would have a human intelligence, do you trust them?
Just recently we have been able to emulate a 1mm-long flatworm brain, which consists of just 302 total neurons. The human brain contains 100 billion. If that makes it seem like a hopeless project, remember the power of exponential progress—now that we’ve conquered the tiny worm brain, an ant might happen before too long, followed by a mouse, and suddenly this will seem much more plausible and according to the experts we hit human intelligence levels is AI no later than 2075 with probably a artificial superintelligence with a brain 170.000 times more advances only 90 minutes later. Worried yet?
Why is it so hard to believe this. Let me show you a graph from The AI Revolution: The Road to Superintelligence.
This is what I’m sharing… you see the future from this perspective. While the graph below shows you is what is about to happen…
Now why we are stubborn in believing this is not hard to explain, but please read the article by Tim Urban to get a deeper understanding of this.
Your Job Is Going Away Fast
You can take the future predictions of AI experts and ignore them all but you can see for yourself what is happening. U.S. flavor of capitalism will prefer machines of people and outsource everything regardless the consequences to the country or rest of the world. It’s a winner take all version of capitalism that will do to us what happened to the horses and I think an article in Foreign Affairs by Erik Brynjolfsson and Andrew McAfee is the best introduction understanding the context of your future unemployment.
In 1983, the Nobel Prize–winning economist Wassily Leontief brought the debate into sharp relief through a clever comparison of humans and horses. For many decades, horse labor appeared impervious to technological change. Even as the telegraph supplanted the Pony Express and railroads replaced the stagecoach and the Conestoga wagon, the U.S. equine population grew seemingly without end, increasing sixfold between 1840 and 1900 to more than 21 million horses and mules. The animals were vital not only on farms but also in the country’s rapidly growing urban centers, where they carried goods and people on hackney carriages and horse-drawn omnibuses.
But then, with the introduction and spread of the internal combustion engine, the trend rapidly reversed. As engines found their way into automobiles in the city and tractors in the countryside, horses became largely irrelevant. By 1960, the United States counted just three million horses, a decline of nearly 88 percent in just over half a century. If there had been a debate in the early 1900s about the fate of the horse in the face of new industrial technologies, someone might have formulated a “lump of equine labor fallacy,” based on the animal’s resilience up till then. But the fallacy itself would soon be proved false: once the right technology came along, most horses were doomed as labor.
But will there be enough demand, especially over the long term, for those two types of human labor: that which must be done by people and that which can’t yet be done by machines? There is a real possibility that the answer is no—that human labor will, in aggregate, decline in relevance because of technological progress, just as horse labor did earlier. If that happens, it will raise the specter that the world may not be able to maintain the industrial era’s remarkable trajectory of steadily rising employment prospects and wages for a growing population.
Not taking artificial intelligence (AI) into account there is an interesting study of McKinsey that analyzed the detailed work activities for 750+ occupations in the US just two months ago (November 2015) to estimate the percentage of time that could be automated by adapting currently demonstrated technology at medium human level of understanding our language, they say 45% of all current work can be automated. A second study from the researchers at Oxford University and Deloitte looked at the jobs in the UK and the data was gathered by assessing nine key skills of each job, which included social perceptiveness, negotiation, and persuasion. Those that required more “human-like” skills were deemed to have less of a chance of automation, but in total about 35% of jobs were said to be at risk of computerization in the next 20 years. So even if with US current unemployment of 5.5% we are looking at an unemployment of nearly 50% at 2035 that is not even close to Spain’s unemployment of 25% in 2013. Eventually, we will all be as unemployed as Zimbabwe of 95%.
“In many cases, automation technology can already match, or even exceed, the median level of human performance required. For instance, Narrative Science’s artificial intelligence system, Quill, analyzes raw data and generates natural language, writing reports in seconds that readers would assume were written by a human author. Amazon’s fleet of Kiva robots is equipped with automation technologies that plan, navigate, and coordinate among individual robots to fulfill warehouse orders roughly four times faster than the company’s previous system. IBM’s Watson can suggest available treatments for specific ailments, drawing on the body of medical research for those diseases. Clearly, organizations and governments will need new ways of mitigating the human costs, including job losses and economic inequality, associated with the dislocation that takes place as companies separate activities that can be automated from the individuals who currently perform them.” according to the McKinsey report.
“Results like these indicate that cooks, gardeners, repairmen, carpenters, dentists, and home health aides are not about to be replaced by machines in the short term. All of these professions involve a lot of sensorimotor work, and many of them also require the skills of ideation, large-frame pattern recognition, and complex communication.” according Erik Brynjolfsson and Andrew McAfee (MIT) in their book “The Second Machine Age”.
Find out if your job is at risk in the next 20 years by using either the BBC or McKinsey study interactive infographics(below)
Prepare for the loss jobs by educating constantly might be making your lifetime job security more likely (although you might need to think about a 20 hour workweek in a couple of years), the current education system is not sufficient to prepare your children for the future where industrialized methods of education are the norm. AI will change everything, employment can grow significant in 5 to 20 years and 35% can already be completely automatized in the next years. Companies will work hard to make this happen and there will be most likely an artificial intelligence revolution and will result in Utopia or Dystopia. Prepare well for a decrease of the workweek by one hour each year from now on, so 10-20 hour workweeks will be the norm in 2040. So what do you do to prepare yourself and your children for this path. To understand that we need to loop at the path that artificial intelligence is taking now.
What is AI?
Since it’s not my intention to write an original piece where other already did great work, I borrowed heavily here from Yaabot. That article helps us see the path clears and artificial intelligence can be graded as:
- ANI: (Artificial Narrow Intelligence) Is the level of artificial intellgience we have achieved currently. It is also known as ‘weak AI’. These systems can perform excel only in a particular field (In a specific function). Like Google Now, or Siri, or Cortana – these ‘personal assistants’ excel is assisting you in your daily life, with mails, messages, reminders and the like.
- AGI: (Artificial General Intelligence) This is the next stage wherein computers equal human intelligence; they are able to perform all human skills in thinking, reasoning and other processes of a human mind. This is also called ‘Strong AI’. Like robots, for example, like the NS-5 in Will Smith’s I, Robot.Japan’s National Institute of Informatics is developing an AI program that can pass the country’s college entrance exams. The project, called the Todai Robot Project, began in 2011 with the goals of achieving a high score on the national entrance exams by 2016 and of passing the University of Tokyo entrance exam by 2021.
- ASI: (ArtificialSuper Intelligence) This stage is really creepy. ASI is what we’re going to call computers that turn out to be more intelligent than humans. The level of intelligence these machines will run on is beyond human comprehension. ASI will be able to solve problems considered impossible for us, within seconds.
“When the computer is able to understand the world around it as well as a human four-year-old. Suddenly, within an hour of hitting that milestone, the system pumps out the grand theory of physics that unifies general relativity and quantum mechanics, something no human has been able to definitively do. 90 minutes after that, the AI has become an ASI, 170,000 times more intelligent than a human.”
When AGI / ASI has been reached “singularity” happened. Singularity assumes many synonyms in accordance with the context. In cosmology for example, a singularity is the centre of a black hole, where the laws of physics break down. Singularity thus refers to anything where normal rules no longer apply. In the case of computer science, or artificial intelligence, a singularity is a point when we would achieve human intelligence (or even better, super intelligence) on computers.
Peter Cochranes helps us understand the path from ANI to ASI in his article in TechRepublic.
It takes decades for the first ANI system to reach low-level general intelligence we just reached worm level, but it finally happens. A computer is able to understand the world around it as well as a human four-year-old. Suddenly, within an hour of hitting that milestone, the system pumps out the grand theory of physics that unifies general relativity and quantum mechanics, something no human has been able to definitively do. 90 minutes after that, the AI has become an ASI, 170,000 times more intelligent than a human.
This finding implies that overall machine intelligence is growing linearly with time. So the obvious question is what happens when a large number of intelligent machines are networked? If they are sufficient, and their numbers grow exponentially, then, and only then, will we see an exponential growth in intelligence.
This growth will probably be furnished by the cloud, with a large population of fixed and mobile computers, but more importantly, mobile phones laden with all forms of sensory capability. That development gives a whole new meaning to mobile intelligence.
So I did not see this coming. Did you? I thought AI was always going to be controlled by people and the rest was science fiction. I was the stick figure in this drawing.
When in reality somewhere in the next 60 years the graph below with the “What the fuck just happened”-stick figure will happen in the next 60 years. What happens afterwards is still open to philisophers and ever harder to predict then the next 60 years. But if you are interested read these two articles to get an idea: this and this.
But is 60 years a correct prediction? It seems so, what is clear that now I’m 40 most likely most of this will pass me by, but my children will be the last generation that had 40 hour workweeks and the last generation where bus-driver was a job. What skills would they need to have and how do you prepare them for what obviously will be a very turbulent time.
Welcome to the next 60 years of your life
What are the signs of a computer-driven economy? First and most obviously, if automation were displacing labor, we’d expect to see a steady decline in the share of the population that’s employed according to this article.
“Machines are not very good at motivating, nurturing, caring and comforting people. Human interactions are something that are important but, so far at least, machines are wholly inadequate for those kind[s] of tasks.” The stunted social skills of machines should mean that salespeople, managers and entrepreneurs have a reasonably bright future, as will nurses, kindergarten teachers and home help aids, he said in the book The Second Machine Age,
Second, we’d expect to see fewer job openings than in the past. Third, as more people compete for fewer jobs, we’d expect to see middle-class incomes flatten in a race to the bottom. Fourth, with consumption stagnant, we’d expect to see corporations stockpile more cash and, fearing weaker sales, invest less in new products and new factories. Fifth, as a result of all this, we’d expect to see labor’s share of national income decline and capital’s share rise.
Less and less labor to get capital will be the consequence and that trend is already starting (see graph below)
Labor, Capital, so how does this affect me?
Credit Suisse has estimated that in 2014, the richest one percent held 48 percent of the world’s total wealth. This means that these smarter narrow version of AI (ANI) like a Tesla or Google car, Amazon’s warehouse or delivery robots or Facebook replacing our phone and internet companies, a simple restaurant ordering computer with some narrow but impressive skills will first take the middle-skill jobs. The money saved will go to the owners of the machines, hedge the currently already weathly people.
“Economist David Autor has suggested here that the first jobs to go will be middle-skill jobs. Despite impressive advances, robots still don’t have the dexterity to perform many common kinds of manual labor that are simple for humans – digging ditches, changing bedpans”, as you already saw in the BBC and McKinsey studies I mentioned earlier. “Nor are they any good at jobs that require a lot of cognitive skill – teaching classes, writing magazine articles. But in the middle you have jobs that are both fairly routine and require no manual dexterity. So that may be where the hollowing out starts: with desk jobs in places like accounting or customer support.”
Yann LeCun, Facebook’s director of AI research, isn’t as worried, saying that society has adapted to change in the past in a Bloomberg article on AI. “It’s another stage in the progress of technology,” LeCun said. “It’s not going to be easy, but we’ll have to deal with it.” But when the top 1% of the world’s richest tell the 99% remaining humans… don’t worry we know it will not be easy but we will deal with it, should we believe every word? I think the next 60 years will be hard for everyone that does not own an ANI technology in a highly capitalist country (read this essay) so that most likely does not impact LeCun directly but maybe your kids will have a really hard time with their minimum basic income (funded by AI-tax) that is barely enough to live off.
Changing Your Career: Gardeners, Dancers and Entrepreneurs are Safe
45% of current US work can already be automated, 2 trillion in wages, from low-skilled work but CEO’s are not safe. If natural-language processing AI increases to medium level of human skills another 13% of work can be automated. Output are outwaying 7-10x the cost of automation according to McKinsey so every job will be affected and changed.
“Digital technologies are in many ways complements, not substitutes for, creativity,” said Brynjolfsson that gives a hint of where you might want to focus your childrens education on. He says: “If somebody comes up with a new song, a video, or piece of software there’s no better time in history to be a creative person who wants to reach not just hundreds or thousands, but millions and billions of potential customers. That’s great news for a lot of people who are becoming millionaires or even billionaires by using their creativity to create new products and services that can be digitised,” he added in the book The Second Machine Age.
The British economist John Maynard Keynes coined the term “technological unemployment” back in the 1930s when he predicted that the displacement of workers by machines would usher in an era of shorter workweeks and increased leisure. And in the 1990s, economists Sherwin Rosen and Robert Frank saw that globalization and technology could conspire to create “superstar” or “winner take all” labor markets. Until now, the consensus among economists was that these developments would have only a minor or temporary impact on the economy. Now they are not so sure since hourly rate is not predictor of jobs going away according to McKinsey it makes sense to explore their interactive graphic again and read the upcoming 2016 full report.
The last job is the operator does the quality control for machine according to NPR Planet Money where David Kestenbaum and Jacob Goldstein gave a relative positive future in their funny podcast. but if you want to prepare really for the upcoming impact of ANI here some ideas from the book The Second Machine Age and the BBC.
- Creative endeavors: These include creative writing, entrepreneurship, and scientific discovery. These can be highly paid and rewarding jobs. There is no better time to be an entrepreneur with an insight than today, because you can use technology to leverage your invention.
- Social interactions: Robots do not have the kinds of emotional intelligence that humans have. Motivated people who are sensitive to the needs of others make great managers, leaders, salespeople, negotiators, caretakers, nurses, and teachers. Consider, for example, the idea of a robot giving a halftime pep talk to a high school football team. That would not be inspiring. Recent research makes clear that social skills are increasingly in demand.
- Physical dexterity and mobility: If you have ever seen a robot try to pick up a pencil you see how clumsy and slow they are, compared to a human child. Humans have millennia of experience hiking mountains, swimming lakes, and dancing—practice that gives them extraordinary agility and physical dexterity. Jobs which involve physical dexterity, like dancing, are under less threat from intelligent machines than those which involve the processing of information.
Jobs that depend on these three kinds of skills and experiences, such as gardening and housekeeping, are jobs that robots are not good at. Some of these jobs are not always highly paid, but it is unlikely that a robot will soon take them over. However, our friends in robotics are working hard at getting better all the time, so this last category is the one most likely to change.
Results like these indicate that cooks, gardeners, repairmen, carpenters, dentists, and home health aides are not about to be replaced by machines in the short term. All of these professions involve a lot of sensorimotor work, and many of them also require the skills of ideation, large-frame pattern recognition, and complex communication.
Why Becoming an Entrepreneur Makes Sense
We cannot predict exactly what happens when AI reaches the super intelligent level of ASI but we can see that the path to AI is walked only by the ones that work with AI-technology, they make the progress and enjoy the fruits of their progress in money. So if you are interested in having a significant easier life the next 60 years, owning the AI’s of the world makes sense. It’s unlikely that this money will get you anything once the AI becomes super intelligent since obviously there is little use of money anymore at that stage where there will not be an owner of a digital superintelligence 170,000 times more intelligent than Einstein.
Entrepreneurs as a whole are not growing (see graph below)
But there are some characteristics that entrepreneurs have that even if they don’t own some AI’s will help them. Here two things that entrepreneurs (non-employees) do better then most:
- Self-education. With the constant change that is awaiting us you need to constantly be updated on the new changing enviroment to predict where new AI’s are taking over parts of work the next years (source BBC).
- Embracing risk. Taking risks is safer than not taking risks in this new scenario. Training a person to deal with changes on a daily base allows them to innovate internally. Some innovation only happen when things go bad and entrepreneurs experience this more than employees and so will be trained better to prepare for the future.
What happens to the rest of us?
That’s the beauty of the future we don’t know what happens and since we think in linear terms we hardly see it coming. Most likely this post and other people will be ignored and no matter what, companies will find it more profitable to automate then to keep people in their companies. More people will lose jobs, the first 10% (most likely transportation industry) will be ignored and we will just walk past them on the street and consider them another homeless. But slowly it will touch us. We will work less and less and a 10 or 20-hour workweek with part-time compensation does not seem unreal in 2025.unreal in 2025.
The cost creation of material goods will drop with each cycle of automation and increasing unemployment. This will continue due to greed and the nature of the capitalistic core of businesses until we hit the “Uh-oh” moment where the political and economic realities become too pressing to ignore. With massive amounts of production, an ever decreasing labor force, and automation becoming more efficient we reach one reality, goods have dropped in pricing, humans are not needed anymore until politicians realize that isn’t the solution since even at rock bottom consumer prices there is almost nobody that can buy anything without salaries and thus governments will step in.
What happens then could be anything from equally distributed as the Economist’s Ryan Avent puts it, “redistribution, and a lot of it.” or the “essentially” universal basic income (that seemed to be a success in Dauphin, Manitoba Canada) to detention camps that were mentioned in the Manna essay where we are fed, clothed, and prevented from interacting with the upper class. So current science fiction movies are not really all that unrealistic in this scenerio. We can also avoid some of this making the AI’s and robots part of a more distributed economy since other version of capitalisme than the famous US version do exist (see video below)
Preparing for 95% Unemployment
Brynjolfsson on of the authors of the book The Second Machine Age, says in this article of Nick Heath
“Society shouldn’t expect that people will simply adapt to the employment opportunities afforded to them by new technologies. To adjust to the labour upheaval that followed the industrial revolution required a long-term overhaul of education systems, he said, an approach that may need to be repeated. “We have to reinvent education and reskilling, and people are going to have to take it upon themselves to more aggressively learn these skills. Because the technology is changing more rapidly, it’s going to be a case of lifelong learning and continuously reskilling.” Better education, doesn’t mean continuing to teach the same subjects in the same way, and certainly not focusing primarily on the three Rs — reading, writing, and arithmetic — which still are the cornerstones of the classroom in many parts of the world. “AI software tends to be very deep and very narrow.”
“The three Rs were once the skills that workers needed to contribute to the most advanced economy of the time. The educational system of Victorian England was designed quite well for its time and place. But that time and place are no longer ours,” according to the book. To remain valuable knowledge workers in this latest machine age, Brynjolfsson and McAfee say people will need to focus on learning skills that are tricky for computers, such as ideation (the creation of new ideas), large-frame pattern recognition, and complex communication.
You will hear people say, “Nine out of every 10 businesses fail, so why bother becoming an entrepreneur?” Here is another way to look at that — the chance of success is 10 percent. You start nine businesses that fail and then the tenth one succeeds and you make a million bucks — those are damn good odds. Compare that to a lottery, where, for example, 9,999,999 out of every 10,000,000 tickets fail. And tens of millions of people play the lottery even though the odds are that bad. Starting a business is not as easy as buying a lottery ticket, sure, but keep in mind that, “Anything you practice gets easier.”
Let me repeat that, because it is very important: “Anything you practice gets easier.” The more you practice something, the easier it gets. Take video games. How many of you play video games? Come on — Everyone plays video games. Admit it. So let’s take Halo. The first time you played Halo, how well did you play? Be honest. You sucked. The first time you play a video game you suck. That’s true of just about anything you try the first time. First time you rode a bike you sucked. You fell off. First time you ice skated you sucked. And so on.
So the new education should focus on these three areas:
- Creative endeavors
- Social interactions
- Physical dexterity and mobility
You can prepare well by first of all click all links in this article and read the related articles so to make sure I’m not insane. Second is to decide if you want to be an entrepreneur and specialize in leadership, sales, negotiators, caretaking, nursing, or teaching.