A conservative legal argument for gun control

I am an advocate for gun control because, as I expounded in my previous post, of my inherent belief in the incompetence of all humans. A major impediment to gun control in the US is the 2nd Amendment of the Constitution, which states “A well regulated Militia, being necessary to the security of a free State, the right of the people to keep and bear Arms, shall not be infringed.” The two key phrases of the 2nd Amendment are “well regulated Militia” and “right … to bear arms” and there has always been constant tension over what they exactly mean. The current Supreme Court, prior to Antonin Scalia’s death, held that the 2nd Amendment means that people can bear arms under any circumstance and this has led to the overturning of many gun control measures in cities like Washington DC and Chicago. However, this has not always been the case. Previous courts have put more weight into the “well regulated” part and allowed for some gun restrictions.

Although the right to bear arms is considered to be the conservative position, I actually think there is an equally compelling conservative argument for gun control. One of the things that conservatives argue for is that government should be less centralized and that individual states should be able to set their own laws, as long as they don’t violate the Constitution. Hence, gun control advocates should use a “States’ Rights” argument that communities should be able to establish their own interpretation for how “well regulated” and “right to bear arms” should be balanced. Instead of trying to fight for uniform federal gun control laws, they should argue that local laws should be allowed to stand, provided that they do not completely outlaw guns. So if Washington DC wants an assault weapons ban, that should be fine. If Chicago wants to limit magazine sizes in hand guns, that should also be okay. People in gun ravaged cities like Baltimore should not have to have gun laws that might be popular in states like Idaho be forced upon them. Depending on who fills the vacant position on the next Supreme Court this line or argument could be moot but I think it is one that gun control advocates should perhaps pursue.

Forming a consistent political view

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.




The hazards of being obese

One of my favourite contrarian positions is that being overweight is not so bad. I don’t truly believe this but I like to use it to point out that although most everyone holds that being obese is not healthy, there is actually very little evidence to support this assertion. However, this recent rather impressive paper in the Lancet finally shows that being overweight or obese is really bad. The paper is a meta-analysis of hundreds of studies with a combined study size of over 10 million! The take home message is that the hazard ratio for dying is significantly greater than one but not too bad for overweight and mildly obese people (BMI < 30) but increases sharply after that. It is over two and rapidly increasing for BMI greater than 35. The hazard ratio gives the relative probability of mortality (or any outcome) per unit time (i.e. mortality rate) in a survival analysis, which in this case was a Cox proportional hazards model. The hazard ratio as a function of BMI is well fit by a quadratic function with a minimum around 22 kg/m^2. The chances of dying increase if you are thinner or fatter than this. The study was careful to not include smokers and anyone with a chronic disease and also did not start the analysis until 5 years after the measurement to avoid capturing people who are thin because they are already ill. They also broke the model down into various regions. Surprisingly, the chances of dying when you are obese is worse if you are in Europe or North America compared to Asia. Particularly surprising is the fact that the hazard ratio rises slowest in South Asia for increasing BMI. South Asians have been found to be more susceptible to insulin resistance and Type II diabetes with increased body fat but it seems that they die from it at lower rates. However, the error bars were also very large because the sample size was smaller so this may not hold up with more data. In any case, I can no longer use the lack of health consequences of obesity to rib my colleagues so I’ll have to find a new axe to grind.

Low carb diet study paper finally out

Kevin Hall’s long awaited paper on what I dubbed “the land sub” experiment, where subjects were sequestered for two months, is finally in print (see here). This was the study funded by Gary Taube’s organization Nusi. The idea was to do a fully controlled study comparing low carb to a standard high carb diet to test the hypothesis that high carbs lead to weight gain through increased insulin. See here for a summary of the hypothesis. The experiment showed very little effect and refutes the carbohydrate-insulin model of weight gain. Kevin was so frustrated with dealing with Nusi that he opted out of any follow up study. Taubes did not support the conclusions of the paper and claimed that the diet used (which Nusi approved) wasn’t high enough in carbs. This is essentially positing that the carb effect is purely nonlinear – it only shows up if you are just eating white bread and rice all day. Even if this were true it would still mean that carbs could not explain the increase in average body weight over the past three decades since there is a wide range of carb consumption over the general population. It is not as if only the super carb lovers were getting obese. There were some weird effects that warrant further study. One is that study participants seemed to burn 500 more Calories outside of a metabolic chamber compared to inside. This was why the participants lost weight on the lead-in stabilizing diet. These missing Calories far swamped any effect of macronutrient composition.

AlphaGo and the Future of Work

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, \sim 250^{150} moves, in contrast to chess with a paltry \sim 35^{80} 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 are 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.

  1. Silver, D. et al. Mastering the game of Go with deep neural networks and tree search. Nature 529, 484–489 (2016).

The simulation argument made quantitative

Elon Musk, of Space X, Tesla, and Solar City fame, recently mentioned that he thought the the odds of us not living in a simulation were a billion to one. His reasoning was based on extrapolating the rate of improvement in video games. He suggests that soon it will be impossible to distinguish simulations from reality and in ten thousand years there could easily be billions of simulations running. Thus there are a billion more simulated universes than real ones.

This simulation argument was first quantitatively formulated by philosopher Nick Bostrom. He even has an entire website devoted to the topic (see here). In his original paper, he proposed a Drake-like equation for the fraction of all “humans” living in a simulation:

f_{sim} = \frac{f_p f_I N_I}{f_p f_I N_I + 1}

where f_p is the fraction of human level civilizations that attain the capability to simulate a human populated civilization, f_I is the fraction of these civilizations interested in running civilization simulations, and N_I is the average number of simulations running in these interested civilizations. He then argues that if N_I is large, then either f_{sim}\approx 1 or f_p f_I \approx 0. Musk believes that it is highly likely that N_I is large and f_p f_I is not small so, ergo, we must be in a simulation. Bostrom says his gut feeling is that f_{sim} is around 20%. Steve Hsu mocks the idea (I think). Here, I will show that we have absolutely no way to estimate our probability of being in a simulation.

The reason is that Bostrom’s equation obscures the possibility of two possible divergent quantities. This is more clearly seen by rewriting his equation as

f_{sim} = \frac{y}{x+y} = \frac{y/x}{y/x+1}

where x is the number of non-sim civilizations and y is the number of sim civilizations. (Re-labeling x and y as people or universes does not change the argument). Bostrom and Musk’s observation is that once a civilization attains simulation capability then the number of sims can grow exponentially (people in sims can run sims and so forth) and thus y can overwhelm x and ergo, you’re in a simulation. However, this is only true in a world where x is not growing or growing slowly. If x is also growing exponentially then we can’t say anything at all about the ratio of y to x.

I can give a simple example.  Consider the following dynamics

\frac{dx}{dt} = ax

\frac{dy}{dt} = bx + cy

y is being created by x but both are both growing exponentially. The interesting property of exponentials is that a solution to these equations for a > c is

x = \exp(at)

y = \frac{b}{a-c}\exp(at)

where I have chosen convenient initial conditions that don’t affect the results. Even though y is growing exponentially on top of an exponential process, the growth rates of x and y are the same. The probability of being in a simulation is then

f_{sim} = \frac{b}{a+b-c}

and we have no way of knowing what this is. The analogy is that you have a goose laying eggs and each daughter lays eggs, which also lay eggs. It would seem like there would be more eggs from the collective progeny than the original mother. However, if the rate of egg laying by the original mother goose is increasing exponentially then the number of mother eggs can grow as fast as the number of daughter, granddaughter, great…, eggs. This is just another example of how thinking quantitatively can give interesting (and sometimes counterintuitive) results. Until we have a better idea about the physics underlying our universe, we can say nothing about our odds of being in a simulation.

Addendum: One of the predictions of this simple model is that there should be lots of pre-sim universes. I have always found it interesting that the age of the universe is only about three times that of the earth. Given that the expansion rate of the universe is actually increasing, the lifetime of the universe is likely to be much longer than the current age. So, why is it that we are alive at such an early stage of our universe? Well, one reason may be that the rate of universe creation is very high and so the probability of being in a young universe is higher than being in an old one.

Addendum 2: I only gave a specific solution to the differential equation. The full solution has the form Y_1\exp(at) + Y_2 \exp(ct).  However, as long as a >c, the first term will dominate.

Addendum 3: I realized that I didn’t make it clear that the civilizations don’t need to be in the same universe. Multiverses with different parameters are predicted by string theory.  Thus, even if there is less than one civilization per universe, universes could be created at an exponentially increasing rate.