The conventional wisdom in economics is that trade is mutually beneficial to all parties and the freer the trade the better. However, as David Autor and collaborators have empirically shown, the benefits of trade can be unevenly distributed. A simple way to think about this is to consider a simple model of a nation’s income () as a function of socio-economic status (), . Here, can be distributed in anyway but has zero mean. The mean income of the nation is while is a measure of inequality (i.e. proportional to standard deviation). Generally, it was presumed that trade increases . However, as Autor finds, trade can also increase and then it becomes a quantitative game as to whether you personally will do better or worse with trade. Your change in income will be . Thus, if you are above the mean then trade is always beneficial and increasing helps you even more. However, where the mean is with respect to the median is strongly dependent on the tails of the distribution of . So if people with high are very far away from the median, then the mean could also be high with respect to the median. If you are below the mean then gains from are offset by decreases in and if you’re is more negative than then you will do worse in absolute terms. This could explain what has been happening in the US. The nation benefits from trade by having cheaper goods but some sectors like manufacturing and textiles are greatly hurt and the cheaper goods cannot make up for the decrease in income. Those above the mean are benefitting from a mean shift in income due to trade as well as any increases in inequality. Those below the mean are getting smaller gains and in some cases doing worse as a result of trade. Thus, it may not be surprising that there are divergent views on the benefits of trade.
Near the end of the twentieth century, there was a battle between small bookstores and the big chains like Barnes and Noble and Borders, typified in the film You’ve Got Mail. The chains won because they had lower prices, larger stocks, and served as mini-community centers where people liked to hang out. It was sad to see the independent bookstores die but the replacement was actually a nice addition to the neighborhood. The Barnes and Noble business model was to create attractive places to spend time, with play areas for children, a cafe with ample seating, and racks and racks of magazines. The idea was that the more time you spent there the more money you would spend and it worked for at least ten years. Yet, at the height of their dominance, the seeds of their destruction could be plainly seen. Amazon was growing even faster and a new shopping model was invented. People would spend time and browse in B and N and then go home to order the books on Amazon. The advent of the smartphone only quickened the demise because people could order directly from the store. The large and welcoming B and N store was a free sample service for Amazon. Borders is already gone and Barnes and Noble is on its last legs. The one I frequent will be closing this summer.
The loss of B and N will be a blow to many communities. It’s a particular favorite locale for retirees to congregate. I think this is a perfect example of a market failure. There is a clear demand for the product but no viable way to monetize it. However, there already is a model for providing the same service as B and N that has worked for a century and that is called a library. Libraries are still extremely popular and provide essential services to people, and particularly low income people. The Enoch Pratt Free Library in Baltimore has a line every morning before it opens for people scrambling to use the computers and access the internet. While libraries have been rapidly modernizing, with a relaxation of behavior rules and adding cafes, they still have short hours and do not provide the comforting atmosphere of B and N.
I see multiple paths forward. The first is that B and N goes under and maybe someone invents a new private model to replace it. Amazon may create book stores in its place that act more like showrooms for their products rather than profit making entities. The second is that a philanthropist will buy it and endow it as a nonprofit entity for the community much like Carnegie and other robber barons of the nineteenth century did with libraries. The third is that communities will start to take over the spaces and create a new type of library that is subsidized by tax payers and has the same hours and ambience of B and N.
In any introductory economics class, one is introduced to the concept of supply and demand. The price of a product is expressed as a function of the number of products that suppliers would produce and buyers would purchase at that price, respectively. Supply curves have positive slope, meaning that the higher the price the more suppliers will produce and vice versa for demand curves. If a market is perfectly competitive, then the supply curve is determined by the marginal cost of production, which is the incremental cost of production for making one additional unit. Firms will keep producing more goods until the price falls below the marginal cost.
Increases in productivity lead to decreases in marginal cost, and since the advent of the industrial revolution, technology has been increasing productivity. In some cases, like software or recorded music, the marginal cost is already zero. The cost for Microsoft to make one more copy of Office is miniscule. However, if the marginal cost is zero then according to classical microeconomic theory firms would produce goods and give it away for free. Public intellectual Jeremy Rifkin has been writing about a zero marginal cost society for several years now, (e.g. see here and here), and has proposed that ubiquitous zero marginal cost will lead to a communitarian revolution where capitalism is overturned and people will collaborate and share goods along the lines of the open software model, which has produced the likes of Wikipedia, Linux, Python, and Julia.
I’m not so sanguine. There are two rational strategies for firms to pursue to increase profit. The first is to lower costs and the second is to create monopolies. In completely unregulated markets, like drug trafficking, it seems like suppliers spend much of their time and efforts pursuing monopolies by literally killing their competition. In the absence of the violence option, firms can gain monopolies by buying or merging with competitors and through regulatory capture to create barriers to entry. There are also industries where size and success create virtual monopolies. This is what happens for tech companies where a single behemoth like Microsoft, Google, Facebook, or Amazon, completely dominates a domain. Being large has a huge advantage in finance and banking. Entertainment seems to breed random monopoly status where a single artist will garner most of the attention even though objectively there may not be much difference between the top and the 100th best selling artist. As costs continue to decrease, there will be even more incentive to create monopolies. Instead of a sharing collaborative egalitarian world, a more likely scenario is a world with a small number of entrenched monopolists controlling most of the wealth.
I think one of the main things that has fueled a backlash against the global elites is the (correct) perception that they play by different rules. When they make financial mistakes, they get bailed out with taxpayer dollars with no consequences. Gains are privatized and losses are socialized. Another example is insider trading where people profit from securities transactions using nonpublic information. While there have been several high profile cases in recent years (e.g. here is a Baltimore example), my guess is that insider trading is rampant since it is so easy to do and so hard to detect. The conventional wisdom for combating insider trading is stronger enforcement and penalties. However, my take is that this will just lead to a situation where small time insider traders get squeezed out while the sophisticated ones who have more resources will continue. This is an example where a regulation creates a monopoly or economic rent opportunity.
Aside from the collapse of morality that may come with extreme wealth and power (e.g. listen here), I also think that insider traders rationalize their activities because they don’t think that it hurts anyone even though there is an obvious victim. For example, if someone gets inside information that a highly touted drug has failed to win approval from the FDA then they can short the stock (or buy put options), which is an agreement or opportunity to sell the stock at the current price in the future. When the stock decreases in value after the announcement, they just buy the stock at the lower price, resell at the higher price, and reap the profits. The victim is the counter party to the trade who could be a rich trader but could also be someone’s pension fund or employees of the company.
Now the losing party or a regulatory agency could suspect a case of insider trading but to prove it would require someone confessing or finding an email or phone recording of the information passed. They could also try to set up a sting operation to try to catch serial violators. All of these things are difficult and costly. The alternative may seem ridiculous but I think the best solution may be to make insider trading legal. If it were legal then several things would happen. More people would do it which would drive down the prices for the trades, the information would more likely be leaked to the public since people would not be afraid of sharing it, and people would be more careful in making trades prior to big decisions because the other party may have more information than they do. Companies would be responsible for policing people in their firms that leak information. By making insider information legal, the rent created by regulations would be reduced.
Political scientists will be dissecting the results of the 2016 US presidential election for the next decade but certainly one fact that is likely to be germane to any analysis is that real wages have been stagnant or declining for the past 45 years. I predict that this trend will only worsen no matter who is in power. The stark reality is that most jobs are replaceable by machines. This is not because AI has progressed to the point that machines can act human but because most jobs, especially higher paying jobs, do not depend heavily on being human. While I have seen some consternation about the prospect of 1.5 million truck drivers being replaced by self-driving vehicles in the near future, I have seen much less discourse on the fact that this is also likely to be true for accountants, lawyers, middle managers, medical professionals, and other well compensated professionals. What people seem to miss is that the reason these jobs are well paid is that there are relatively few people who are capable of doing them and that is because they are difficult for humans to master. In other words, they are well paid because they require not acting particulary human. IBM’s Watson, which won the game show Jeopardy and AlphaGo, which beat the world’s best Go player, shows that machines can quite easily better humans at specific tasks. The more specialized the task, the easier it will be for a machine to do it. The cold hard truth is that AI does not have to improve for you to be replaced by a machine. It does not matter whether strong AI, (an artificial intelligence that truly thinks like a human), is ever possible. It only matters that machine learning algorithms can mimic what you do now. The only thing necessary for this to happen was for computers to be fast enough and now they are.
What this implies is that the jobs of the future will be limited to those that require being human or where interacting with a human is preferred. This will include 1) jobs that most people can do and thus will not be well paid like store sales people, restaurant servers, bar tenders, cafe baristas, and low skill health workers, 2) jobs that require social skills that might be better paid such as social workers, personal assistants, and mental health professionals, 3) jobs that require special talents like artisans, artists, and some STEM professionals, and 4) capitalists that own firms that employ mostly robots. I strongly believe that only a small fraction of the population will make it to categories 3) and 4). Most people will be in 1) or not have a job at all. I have argued before that one way out is for society to choose to make low productivity work viable. In any case, the anger we saw this year is only going to grow because existing political institutions are in denial about the future. The 20th century is over. We are not getting it back. The future is either the 17th or 18th century with running water, air conditioning and health care or the 13th century with none of these.
In view of the current US presidential election, I think it would be a useful exercise to see if I could form a rational political view that is consistent with what I actually know and believe from my training as a scientist. From my knowledge of dynamical systems and physics, I believe in the inherent unpredictability of complex nonlinear systems. Uncertainty is a fundamental property of the universe at all scales. From neuroscience, I know that people are susceptible to errors, do not always make optimal choices, and are inconsistent. People are motivated by whatever triggers dopamine to be released. From genetics, I know that many traits are highly heritable and that includes height, BMI, IQ and the Big Five personality traits. There is lots of human variance. People are motivated by different things, have various aptitudes, and have various levels of honesty and trustworthiness. However, from evolution theory, I know that genetic variance is also essential for any species to survive. Variety is not just the spice of life, it is also the meat. From ecology, I know that the world is a linked ecosystem. Everything is connected. From computer science, I know that there are classes of problems that are easy to solve, classes that are hard to solve, and classes that are impossible to solve and no amount of computing power can change that. From physics and geology, I fully accept that greenhouse gases will affect the energy balance on earth and that the climate is changing. However, given the uncertainty of dynamical systems, while I do believe that current climate models are pretty good, there does exist the possibility that they are missing something. I believe that the physical laws that govern our lives are computable and this includes consciousness. I believe everything is fallible and that includes people, markets and government.
So how would that translate into a political view? Well, it would be a mishmash of what might be considered socialist, liberal, conservative, and libertarian ideas. Since I think randomness and luck is a large part of life, including who your parents are, I do not subscribe to the theory of just desserts. I don’t think those with more “talents” deserve all the wealth they can acquire. However, I also do realize that we are motivated by dopamine and part of what triggers dopamine is reaping the rewards of our efforts so we must leave incentives in place. We should not try to make society completely equal but redistributive taxation is necessary and justified.
Since I think people are basically incompetent and don’t always make good choices, people sometimes need to be protected from themselves. We need some nanny state regulations such as building codes, water and air quality standards, transportation safety, and toy safety. I don’t believe that all drugs should be legalized because some drugs can permanently damage brains, especially those of children. Amphetamines and opioids should definitely be illegal. Marijuana is probably okay but not for children. Pension plans should be defined benefit (rather than defined contribution) schemes. Privatizing social security would be a disaster. However, we should not over regulate. I would deregulate a lot of land use especially density requirements. We should eliminate all regulations that enforce monopolies including some professional requirements that deliberately restrict supply. We should not try to pick winners in any industry.
I believe that people will try to game the system so we should design welfare and tax systems that minimize the possibility of cheating. The current disability benefits program needs to be fixed. I do not believe in means testing for social programs as it gives room to cheat. Cheating not only depletes the system but also engenders resentment in others who do not cheat. Part of the anger of the working class is that they see people around them gaming the system. The way out is to replace the entire welfare system with a single universal basic income. People have argued that it makes no sense for Bill Gates and Warren Buffet to get a basic income. In actuality, they would end up paying most of it back in taxes. In biology, this is called a futile cycle but it has utility since it is easier to just give everyone the same benefits and tax according to one rule then having exceptions for everything as we have now. We may not be able to afford a basic income now but we eventually will.
Given our lack of certainty and incompetence, I would be extremely hesitant about any military interventions on foreign soil. We are as likely to make things worse as we are to make the better. I think free trade is in net a good thing because it does lead to higher efficiency and helps people in lower income countries. However, it will absolutely hurt some segment of the population in the higher income country. Since income is correlated with demand for your skills, in a globalized world those with skills below the global median will be losers. If a lot of people will do your job for less then you will lose your job or get paid less. For the time being, there should be some wage support for low wage people but eventually this should transition to the basic income.
Since I believe the brain is computable, this means that any job a human can do, a robot will eventually do as well or better. No job is safe. I do not know when the mass displacement of work will take place but I am sure it will come. As I wrote in my AlphaGo piece, not everyone can be a “knowledge” worker, media star, or CEO. People will find things to do but they won’t all be able to earn a living off of it in our current economic model. Hence, in the robot world, everyone would get a basic income and guaranteed health care and then be free to do whatever they want to supplement that income including doing nothing. I romantically picture a simulated 18th century world with people indulging in low productivity work but it could be anything. This will be financed by taxing the people who are still making money.
As for taxes, I think we need to go a system that de-emphasizes income taxes, which can be gamed and disincentivizes work, to one that taxes the use of shared resources (i.e. economic rents). This includes land rights, mineral rights, water rights, air rights, solar rights, wind rights, monopoly rights, eco system rights, banking rights, genetic rights, etc. These are resources that belong to everyone. We could use a land value tax model. When people want to use a resource, like land to build a house, they would pay the intrinsic value of that resource. They would keep any value they added. This would incentivize efficient utility of the resource while not telling anyone how to use it.
We could use an auction system to value these resources and rights. Hence, we need not regulate wall street firms per se but we would tax them according to the land they use and what sort of monopoly influence they exploit. We wouldn’t need to force them to obey capital requirements, we would tax them for the right to leverage debt. We wouldn’t need Glass-Steagall or Too Big to Fail laws for banks. We’ll just tax them for the right to do these things. We would also not need a separate carbon tax. We’ll tax the right to extract fossil fuels at a level equal to the resource value and the full future cost to the environment. The climate change debate would then shift to be about the discount rate. Deniers would argue for a large rate and alarmists for a small one. Sports leagues and teams would be taxed for their monopolies. The current practice of preventing cities from owning teams would be taxed.
The patent system needs serious reform. Software patents should be completely eliminated. Instead of giving someone arbitrary monopoly rights for a patent, patent holders should be taxed at some level that increases with time. This would force holders to commercialize, sell or relinquish the patent when they could no longer bear the tax burden and this would eliminate patent trolling.
We must accept that there is no free will per se so that crime and punishment must be reinterpreted. We should only evaluate whether offenders are dangerous to society and the seriousness of the crime. Motive should no longer be important. Only dangerous offenders would be institutionalized or incarcerated. Non-dangerous ones should repay the cost of the crime plus a penalty. We should also do a Manhattan project for nonlethal weapons so the police can carry them.
Finally, under the belief that nothing is certain, laws and regulations should be regularly reviewed including the US Constitution and the Bill of Rights. In fact, I propose that the 28th Amendment be that all laws and regulations must be reaffirmed or they will expire in some set amount of time.
In March of this year, Google DeepMind’s computer program AlphaGo defeated world Go champion Lee Sedol. This was hailed as a great triumph of artificial intelligence and signaled to many the beginning of the new age when machines take over. I believe this is true but the real lesson of AlphaGo’s win is not how great machine learning algorithms are but how suboptimal human Go players are. Experts believed that machines would not be able to defeat humans at Go for a long time because the number of possible games is astronomically large, moves, in contrast to chess with a paltry moves. Additionally, unlike chess, it is not clear what is a good position and who is winning during intermediate stages of a game. Thus, any direct enumeration and evaluation of possible next moves as chess computers do, like IBM’s Deep Blue that defeated Gary Kasparov, seemed to be impossible. It was thought that humans had some sort of inimitable intuition to play Go that machines were decades away from emulating. It turns out that this was wrong. It took remarkably little training for AlphaGo to defeat a human. All the algorithms used were fairly standard – supervised and reinforcement backpropagation learning in multi-layer neural networks1. DeepMind just put them together in a clever way and had the (in retrospect appropriate) audacity to try.
The take home message of AlphaGo’s success is that humans are very, very far away from being optimal at playing Go. Uncharitably, we simply stink at Go. However, this probably also means that we stink at almost everything we do. Machines are going to take over our jobs not because they are sublimely awesome but because we are stupendously inept. It is like the old joke about two hikers encountering a bear and one starts to put on running shoes. The other hiker says: “Why are you doing that? You can’t outrun a bear.” to which she replies, “I only need to outrun you!” In fact, the more difficult a job seems to be for humans to perform, the easier it will be for a machine to do better. This was noticed a long time ago in AI research and called Moravec’s Paradox. Tasks that require a lot of high level abstract thinking like chess or predicting what movie you will like are easy for computers to do while seemingly trivial tasks that a child can do like folding laundry or getting a cookie out of a jar on an unreachable shelf is really hard. Thus high paying professions in medicine, accounting, finance, and law could be replaced by machines sooner than lower paying ones in lawn care and house cleaning.
There are those who are not worried about a future of mass unemployment because they believe people will just shift to other professions. They point out that a century ago a majority of Americans worked in agriculture and now the sector comprises of less than 2 percent of the population. The jobs that were lost to technology were replaced by ones that didn’t exist before. I think this might be true but in the future not everyone will be a software engineer or a media star or a CEO of her own company of robot employees. The increase in productivity provided by machines ensures this. When the marginal cost of production goes to zero (i.e. cost to make one more item), as it is for software or recorded media now, the whole supply-demand curve is upended. There is infinite supply for any amount of demand so the only way to make money is to increase demand.
The rate-limiting step for demand is the attention span of humans. In a single day, a person can at most attend to a few hundred independent tasks such as thinking, reading, writing, walking, cooking, eating, driving, exercising, or consuming entertainment. I can stream any movie I want now and I only watch at most twenty a year, and almost all of them on long haul flights. My 3 year old can watch the same Wild Kratts episode (great children’s show about animals) ten times in a row without getting bored. Even though everyone could be a video or music star on YouTube, superstars such as Beyoncé and Adele are viewed much more than anyone else. Even with infinite choice, we tend to do what our peers do. Thus, for a population of ten billion people, I doubt there can be more than a few million that can make a decent living as a media star with our current economic model. The same goes for writers. This will also generalize to manufactured goods. Toasters and coffee makers essentially cost nothing compared to three decades ago, and I will only buy one every few years if that. Robots will only make things cheaper and I doubt there will be a billion brands of TV’s or toasters. Most likely, a few companies will dominate the market as they do now. Even, if we could optimistically assume that a tenth of the population could be engaged in producing goods and services necessary for keeping the world functioning that still leaves the rest with little to do.
Even much of what scientists do could eventually be replaced by machines. Biology labs could consist of a principle investigator and robot technicians. Although it seems like science is endless, the amount of new science required for sustaining the modern world could diminish. We could eventually have an understanding of biology sufficient to treat most diseases and injuries and develop truly sustainable energy technologies. In this case, machines could be tasked to keep the modern world up and running with little need of input from us. Science would mostly be devoted to abstract and esoteric concerns.
Thus, I believe the future for humankind is in low productivity occupations – basically a return to pre-industrial endeavors like small plot farming, blacksmithing, carpentry, painting, dancing, and pottery making, with an economic system in place to adequately live off of this labor. Machines can provide us with the necessities of life while we engage in a simulated 18th century world but without the poverty, diseases, and mass famines that made life so harsh back then. We can make candles or bread and sell them to our neighbors for a living wage. We can walk or get in self-driving cars to see live performances of music, drama and dance by local artists. There will be philosophers and poets with their small followings as they have now. However, even when machines can do everything humans can do, there will still be a capacity to sustain as many mathematicians as there are people because mathematics is infinite. As long as P is not NP, theorem proving can never be automated and there will always be unsolved math problems. That is not to say that machines won’t be able to do mathematics. They will. It’s just that they won’t ever be able to do all of it. Thus, the future of work could also be mathematics.
- Silver, D. et al. Mastering the game of Go with deep neural networks and tree search. Nature 529, 484–489 (2016).