The battle over academic freedom

In the wake of George Floyd’s death, almost all of institutional America put out official statements decrying racism and some universities initiated policies governing allowable speech and research. This was followed by the expected dissent from those who worry that academic freedom is being suppressed (see here, here, and here for some examples). Then there is the (in)famous Harper’s Magazine open letter decrying Cancel Culture, which triggered a flurry of counter responses (e.g. see here and here).

While some faculty members in the humanities and (non-life) sciences are up in arms over the thought of a committee of their peers judging what should be allowable research, I do wish to point out that their colleagues over on the Medical campus have had to get approval for human and animal research for decades. Research on human subjects must first pass through an Institutional Review Board (IRB) while animal experiments must clear the Institutional Animal Care and Use Committee (IACUC). These panels ensure that the proposed work is ethical, sound, and justified. Even research that is completely noninvasive, such as analysis of genetic data, must pass scrutiny to ensure the data is not misused and subject identies are strongly protected. Almost all faculty members would agree that this step is important and necessary. History is rife of questionable research that range from careless to criminal. Is it so unreasonable to extend such a concept to the rest of campus?

The depressing lack of American imagination

Democratic presidential candidate Andrew Yang made universal basic income a respectable topic for debate. I think this is a good thing because I’m a major proponent of UBI but my reasons are different. Yang is a technology dystopian who sees a future where robots take all of our jobs and the UBI as a way to alleviate the resulting pain and suffering. I think a UBI (and universal health care) would lead to less resentment of the welfare system and let people take more entrepreneurial risks. I believe human level AI is possible but I do not accept that this necessarily implies an economic apocalypse. To believe such a thing is to believe that the only way society can be structured is that a small number of tech companies owns all the robots and everyone else is at their mercy. That to me is a depressing lack of imagination. The society we live in is a human construct. There is no law of nature that says we must live by any specific set of rules or economic system. There is no law that says tech companies must have monopolies. There is no reason we could not live in a society where each person has her own robot who works for her. There is no law that says we could not live in a society where robots do all the mundane work while we garden and bake bread.

I think we lack imagination in every sector of our life. We do not need to settle for the narrow set of choices we are presented. I for one do not accept that elite colleges must wield so much influence in determining the path of one’s life. There is no reason that the US meritocracy needs to be a zero sum game, where one student being accepted to Harvard means another is not or that going to Harvard should even make so much difference in one’s life. There is no reason that higher education needs to cost so much. There is no reason students need to take loans out to pay exorbitant tuition. That fact that this occurs is because we as a society have chosen such.

I do not accept that irresponsible banks and financial institutions need to be bailed out whenever they fail, which seems to be quite often. We could just let them fail and restart. There is no reason that the access to capital needs to be controlled by a small number of financial firms. It used to be that banks would take in deposits and lend out to homeowners and businesses directly. They would evaluate the risk of each loan. Now they purchase complex financial products that evaluate the risk according to some mathematical model. There is no reason we need to subsidize such activity.

I do not accept that professional sports teams cannot be community owned. There is no law that says sports leagues need to be organized as monopolies with majority owners. There is no reason that communities cannot simply start their own teams and play each other. There is no law that says we need to build stadiums for privately owned teams. We only choose to do so.

The society we live in is the way it is because we have chosen to live this way. Even an autocrat needs a large fraction of the population to enforce his rule. The number of different ways we could organize (or not organize) is infinite. We do not have to be limited to the narrow set of choices we are presented. What we need is more imagination.

The fatal flaw of the American Covid-19 response

The United States has surpassed 2 million official Covid-19 cases and a 115 thousand deaths. After three months of lockdown, the country has had enough and is reopening. Although it has achieved its initial goal of slowing the growth of the pandemic so that hospitals would not be overwhelmed, the battle has not been won. We’re not at the beginning of the end; we may not even be at the end of the beginning. If everyone in the world could go into complete isolation, the pandemic would be over in two weeks. Instead, it is passed from one person to the next in a tragic relay race. As long as a single person is shedding the SARS-CoV-2 virus and comes in contact with another person, the pandemic will continue. The pandemic in the US is not heading for extinction. We are not near herd immunity and R0 is not below one. By the most optimistic yet plausible scenario, 30 million people have already been infected and 200 million will never get it either by having some innate immunity or by avoiding it through sheltering or luck. However, that still leaves over 100 million who are susceptible of which about a million will die if they all catch it.

However, the lack of effectiveness of the response is not the fatal flaw. No, the fatal flaw is that the US Covid-19 response asks one set of citizens to sacrifice for the benefit of another set. The Covid-19 pandemic is a story of three groups of people. The fortunate third can work from home, and the lockdown is mostly just an inconvenience. They still get paychecks while supplies and food can be delivered to their homes. Sure it has been stressful and many of have forgone essential medical care but they can basically ride this out for as long as it takes. The second group who own or work in shuttered businesses have lost their income. The federal rescue package is keeping some of them afloat but that runs out in August. The choice they have is to reopen and risk getting infected or be hungry and homeless. Finally, the third group is working to allow the first group to remain in their homes. They are working on farms, food processing plants, and grocery stores. They are cutting lawns, fixing leaking pipes, and delivering goods. They are working in hospitals and nursing homes and taking care of the sick and the children of those who must work. They are also the ones who are most likely to get infected and spread it to their families or the people they are trying to take care of. They are dying so others may live.

A lockdown can only work in a society if the essential workers are adequately protected and those without incomes are supported. Each worker should have an N100 mask, be trained how to wear it and be tested weekly. People in nursing homes should be wearing hazmat suits. Everyone who loses income should be fully compensated. In a fair society, everyone should share the risks and the pain equally.

Harvard and Asian Americans

The current trial regarding Harvard’s admissions policies seem to clearly indicate that they discriminate against Asian Americans. I had always assumed this to be the case. My take is that the problem is not so much that Harvard is non-transparent and unfair in how it selects students but rather that Harvard and the other top universities have too much influence on the rest of society. Each justice on the US Supreme Court has a degree from either Harvard or Yale. That is positively feudalistic. So here is my solution. All universities have a choice. They can 1) choose students any way they wish but they lose their tax free status or 2) retain tax exempt status but then adhere to strict non-discrimination and affirmative action rules. The top schools already have massive endowments and hurt the locales they are in by buying property and then not pay property taxes. I say let them do what they want but tax them heavily for the right to do so. The government should also not subsidize loans for students that attend such schools.

AI and authoritarianism

Much of the discourse on the future of AI , such as this one, has focused on people being displaced by machines. While this is certainly a worthy concern, these analyses sometimes fall into the trap of linear thinking because the displaced workers are also customers. The revenues of companies like Google and Facebook depend almost entirely on selling advertisements to a consumer base that has disposable income to spend. What happens when this base dwindles to a tiny fraction of the world’s population? The progression forward will also most likely not be monotonic because as people initially start to be replaced by machines, those left with jobs may actually get increased compensation and thus drive more consumerism. The only thing that is certain is that the end point of a world where no one has work is one where capitalism as we know it will no longer exist.

Historian and author Yuval Harari argues that in the pre-industrial world, to have power is to have land (I would add slaves and I strongly recommend visiting the National Museum of African American History and Culture for a sobering look at how America became so powerful). In the industrial world, the power shifted to those who own the machines (although land won’t hurt) while in the post-industrial world, power falls to those with the data. Harari was extrapolating our current world where large corporations can track us continually and use machine learning to monopolize our attention and get us to do what they desire. However, data on people is only useful as long as they have resources you want. If people truly become irrelevant then their data is also irrelevant.

It’s anyone’s guess as to what will happen in the future. I proposed an optimistic scenario here but here is a darker one. Henry Ford supposedly wanted to pay his employees a decent wage because he realized that they were also the customers for his product. In the early twentieth century, the factory workers formed the core of the burgeoning middle class that would drive demand for consumer products made in the very factories where they toiled. It was in the interest of industrialists that the general populace be well educated and healthy because they were the source of their wealth. This link began to fray at the end of the twentieth century with the rise of the service economy, globalisation, and automation. After the second World War, post-secondary education became available to a much larger fraction of the population. These college educated people did not go to work on the factory floor but fed the expanding ranks of middle management and professionals. They became managers and accountants and dentists and lawyers and writers and consultants and doctors and educators and scientists and engineers and administrators. They started new businesses and new industries and helped drive the economy to greater prosperity. They formed an upper middle class that slowly separated from the working class and the rest of the middle class. They also started to become a self-sustaining entity that did not rely so much on the rest of the population. Globalisation and automation made labor plentiful and cheap so there was less of an incentive to have a healthy educated populace. The wealth of the elite no longer depended on the working class and thus their desire to invest in them declined. I agree with the thesis that the abandonment of the working class in Western liberal democracies is the main driver of the recent rise of authoritarianism and isolationism around the world.

However, authoritarian populist regimes, such as those in Venezuela and Hungary, stay in power because the disgruntled class that supports them is a larger fraction of the population than the opposing educated upper middle class that are the winners in a contemporary liberal democracy. In the US, the disgruntled class is still a minority so thus far it seems like authoritarianism will be held at bay by the majority coalition of immigrants, minorities, and costal liberals. However, this coalition could be short lived. Up to now, AI and machine learning has not been taking jobs away from the managerial and professional classes. But as I wrote about before, the people most at risk for losing jobs to machines may not be those doing jobs that are simple for humans to master but those that are difficult. It may take awhile before professionals start to be replaced but once it starts it could go swiftly. Once a machine learning algorithm is trained, it can be deployed everywhere instantly. As the ranks of the upper middle class dwindle, support for a liberal democracy could weaken and a new authoritarian regime could rise.

Ironically, a transition to a consumer authoritarianism would be smoothed and possibly quickened by a stronger welfare state. A possible jobless economy would be one where the state provides a universal basic income that is funded by taxation on existing corporations, which would then compete for those very same dollars. Basically, the future incarnations of Apple, Netflix, Facebook, Amazon, and Google would give money to an idle population and then try to win it back. Although, this is not a world I would choose to live in, it would be preferable to a socialistic model where the state would decide on what goods and services to provide. It would actually be in the interest of the corporations and their elite owners to lobby for high taxes and to not form monopolies and allow for competition to provide better goods and services. The tax rate would not matter much because in a steady state loop, any wealth inequality is stable regardless of the flux. It is definitely in their interest to keep the idle population happy.

The robot human equilibrium

There has been some push back in the media against the notion that we will “soon” be replaced by robots, e.g. see here. But absence of evidence is not evidence of absence. Just because there seem to be very few machine induced job losses today doesn’t mean it won’t happen tomorrow or in ten years. In fact, when it does happen it probably will happen suddenly as have many recent technological changes. The obvious examples are the internet and smartphones but there are many others. We forget that the transition from vinyl records to CDs was extremely fast; then iPods and YouTube killed CDs. Video rentals became ubiquitous from nothing in just a few years and died just as fast when Netflix came along, which was then completely replaced a few years later by streaming video. It took Amazon a little longer to become dominant but the retail model that had existed for centuries has been completely upended in a decade. The same could happen with AI and robots. Unless you believe that human thought is not computable, then in principle there is nothing a human can do that a machine can’t. It could take time to set up the necessary social institutions and infrastructure for an AI takeover but once it is established the transition could be abrupt.

Even so that doesn’t mean all or even most humans will be replaced. The irony of AI, known as Moravec’s Paradox (e.g. here), is that things that are hard for humans to do, like play chess or read X-rays, are easy for machines to do and vice versa. Although drivers and warehouse workers are destined to be the first to be replaced, the next set of jobs will likely be highly paid professionals like stock brokers, accountants, doctors, and lawyers. But as the ranks of the employed start to shrink, the economy will also shrink and wages will go down (even if the displaced do eventually move on to other jobs it will take time). At some point, particularly for jobs that are easy for humans but harder for machines, humans could be cheaper than machines.  So while we can train a machine to be a house cleaner, it may be more cost effective to simply hire a person to change sheets and dust shelves. The premium on a university education will drop. The ability to sit still for long periods of time and acquire arcane specialized knowledge will simply not be that useful anymore. Centers for higher learning will become retreats for the small set of scholarly minded people who simply enjoy it.

As the economy shrinks, land prices in some areas should drop too and thus people could still eke out a living. Some or perhaps many people will opt or be pushed out of the mainstream economy altogether and retire to quasi-pre-industrial lives. I wrote about this in quasi-utopian terms in my AlphaGo post but a dystopian version is equally probable. In the dystopia, the gap between the rich and poor could make today look like an egalitarian paradise. However, unlike the usual dystopian nightmare like the Hunger Games where the rich exploit the poor, the rich will simply ignore the poor. But it is not clear what the elite will do with all that wealth. Will they wall themselves off from the rest of society and then what, engage in endless genetic enhancements or immerse themselves in a virtual reality world? I think I’d rather raise pigs and make candles out of lard.





The US election and the future

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.

What liberal boomers don’t get

Writer Lionel Shriver recently penned an opinion piece in the New York Times lamenting that the millennial penchant for political correctness is stifling free speech and imposing cultural conformity the way the conservatives did in the 60’s and 70’s. The opinion piece was her response to the uproar over her speech at the 2016 Brisbane Writer’s Festival instigated by a young woman named Yassmin Abdel-Magied, who walked out in the middle and then wrote a commentary about why she did so in the Guardian. You can read Shriver’s piece here, Abdel-Magied’s here, and a blog post about the talk here. The question of cultural appropriation, identity politics, and political correctness is a major theme in the current US presidential election. While there has always been conservative resentment towards political correctness there has been a recent strong liberal backlash.

The liberal resentment has been spurred mainly by two recent incidents at two elite US colleges. The first was when Yale’s Intercultural Affairs Council recommended that students not wear Hallowe’en costumes that might offend other students. Lecturer and associate master of one of Yale’s residential colleges, Erica Christakis, wrote an email questioning the need to regulate student’s clothing choices and that students should be allowed to be a little offensive. This triggered a massive reaction from the student body strongly criticizing Christakis. The second incident occurred at Bowdoin College in which there was a “tequila” themed party at a College Residence, where students wore sombreros and acted out Mexican sterotypes. Two members of the student government attended the party and this led to a movement by students to have the two impeached. Both of these incidents led to pretty uniform condemnation of the students by the main stream media. For example, see this article in the Atlantic.

The liberal backlash is based on the premise that the millennial generation (those born between 1980 and 2000) have been so coddled (by their baby boomer parents, born between 1945 and 1965, I should add) that they refuse to be exposed to any offensive speech or image. (Personal disclosure: I am technically a boomer, born in 1962, although by the time I came of age the culture wars of the 60’s had past. I’m a year younger than Douglas Coupland, who wrote the book Generation X, which was partially an anthem for neglected tail-end boomers who missed out on all the fun and excitement of the cohort a decade older. The cruel irony is that the term Generation X was later appropriated to mostly mean those born in the 70’s making us once again, an afterthought.)

My initial reaction to those incidents was to agree with the backlash but the contrast between Ms. Abdel-Magied’s thoughtful heartfelt comment and Ms. Shriver’s exasperated impatient one made me realize that I have underestimated the millennials and that they do have a point. Many liberal boomers believe that while full racial equality may not yet exist, much of the heavy lifting towards that end was done by the Civil Rights Movement of the 60’s, which they supported. What these boomers miss is that the main reason that full racial equality has not been reached is because of cultural biases and attitudes that many of them may even possess. The millennial approach may be a little heavy handed but they at least recognize the true problem and are trying to do something about it.

The plain truth is that just being black does carry an extra risk of being killed in an encounter with law enforcement. Whites and blacks still live in segregated neighborhoods. Even in the so-called liberal enclave of academia, minorities are underrepresented in high level administrative positions. There are just a handful of East Asian women full professors in Ophthalmology in all US medical schools. Hollywood executives do believe that movies cannot be successful with Asian lead actors and thus they still cast white actors for Asian roles. Asians are disadvantaged in the admissions process at elite American schools. Racial stereotypes do exist and pervade even the most self-professed liberal minds and this is a problem. This is not just a battle over free speech as liberal boomers have cast it. This is about what we need to do to make society more just and fair. Shriver thought it was ridiculous that people would be upset over wearing sombreros but it does indicate that there are those that automatically associate a Mexican drink with a Mexican stereotype. Some of these students will be future leaders and I don’t think it is too much to ask that they be aware of the inherent racial biases they may harbour.

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.




What Uber doesn’t get

You may have heard that ride hailing services Uber and Lyft have pulled out of Austin, TX because they refuse to be regulated. You can read about the details here. The city wanted to fingerprint drivers, as they do for taxis, but Uber and Lyft forced a referendum on the city to make them exempt or else they would leave. The city voted against them. I personally use Uber and really like it but what I like about Uber has nothing to do with Uber per se or regulation. What I like is 1) no money needs to be exchanged especially the tip and 2) the price is essentially fixed so it is in the driver’s interest to get me to my destination as fast as possible. I have been taken on joy rides far too many times by taxi drivers trying to maximize the fare and I never know how much to tip. However, these are things that regulated taxis could implement and should implement. I do think it is extremely unfair that Uber can waltz into a city like New York and compete against highly regulated taxis, who have paid as much as a million dollars for the right to operate. Uber and Lyft should collaborate with existing taxi companies rather than trying to put them out of business. There was a reason to regulate taxis (e.g. safety, traffic control, fraud protection), and that should apply whether I hail a cab on the street or I use a smartphone app.

The nature of evil

In our current angst over terrorism and extremism, I think it is important to understand the motivation of the agents behind the evil acts if we are ever to remedy the situation. The observable element of evil (actus reus) is the harm done to innocent individuals. However, in order to prevent evil acts, we must understand the motivation behind the evil (mens rea). The Radiolab podcast “The Bad Show” gives an excellent survey of the possible varieties of evil. I will categorize evil into three types, each with increasing global impact. The first is the compulsion or desire within an individual to harm another. This is what motivates serial killers like the one described in the show. Generally, such evilness will be isolated and the impact will be limited albeit grisly. The second is related to what philosopher Hannah Arendt called “The Banality of Evil.” This is an evil where the goal of the agent is not to inflict harm per se as in the first case but in the process of pursuing some other goal, there is no attempt to avoid possible harm to others. This type of sociopathic evil is much more dangerous and widespread as is most recently seen in Volkswagen’s fraudulent attempt to pass emission standards. Although there are sociopathic individuals that really have no concern for others, I think many perpetrators in this category are swayed by cultural norms or pressures to conform. The third type of evil is when the perpetrator believes the act is not evil at all but a means to a just and noble end. This is the most pernicious form of evil because when it is done by “your side” it is not considered evil. For example, the dropping of atomic bombs on Japan was considered to be a necessary sacrifice of a few hundred thousand lives to end WWII and save many more lives.

I think it is important to understand that the current wave of terrorism and unrest in the Middle East is motivated by the third type. Young people are joining ISIS not because they particularly enjoy inflicting harm on others or they don’t care how their actions affect others, but because they are rallying to a cause they believe to be right and important. Many if not most suicide bombers come from middle class families and many are women. They are not merely motivated by a promise of a better afterlife or by a dire economic situation as I once believed. They are doing this because they believe in the cause and the feeling that they are part of something bigger than themselves. The same unwavering belief and hubris that led people to Australia fifty thousand years ago is probably what motivates ISIS today. They are not nihilists as many in the west believe. They have an entirely different value system and they view the west as being as evil as the west sees them. Until we fully acknowledge this we will not be able to end it.

Why science is hard to believe

Here is an excerpt from a well written opinion piece by Washington Post columnist Joel Achenbach:

Washington Post: We live in an age when all manner of scientific knowledge — from the safety of fluoride and vaccines to the reality of climate change — faces organized and often furious opposition. Empowered by their own sources of information and their own interpretations of research, doubters have declared war on the consensus of experts. There are so many of these controversies these days, you’d think a diabolical agency had put something in the water to make people argumentative.

Science doubt has become a pop-culture meme. In the recent movie “Interstellar,” set in a futuristic, downtrodden America where NASA has been forced into hiding, school textbooks say the Apollo moon landings were faked.

I recommend reading the whole piece.

The demise of the American cappuccino

When I was a post doc at BU in the nineties, I used to go to a cafe on Commonwealth Ave just down the street from my office on Cummington Street. I don’t remember the name of the place but I do remember getting a cappuccino that looked something like this:cappuccinoNow, I usually get something that looks like this:   dry cappuccino Instead of a light delicate layer of milk with a touch of foam floating on rich espresso, I get a lump of dry foam sitting on super acidic burnt quasi-espresso. How did this unfortunate circumstance occur? I’m not sure but I think it was because of Starbucks. Scaling up massively means you get what the average customer wants, or Starbucks thinks they want. This then sets a standard and other cafes have to follow suit because of consumer expectations. Also, making a real cappuccino takes training and a lot of practice and there is no way Starbucks could train enough baristas. Now, I’m not an anti-Starbucks person by any means. I think it is nice that there is always a fairly nice space with free wifi on every corner but I do miss getting a real cappuccino. I believe there is a real business opportunity out there for cafes to start offering better espresso drinks.

What’s wrong with neuroscience

Here is a cute parable in Frontiers in Neuroscience from cognitive scientist Joshua Brown at Indiana Univeristy.  It mirrors a lot of what I’ve been saying for the past few years:


The tale of the neuroscientists and the computer:  Why mechanistic theory matters

A little over a decade ago, a biologist asked the question “Can a biologist fix a radio?” (Lazebnik, 2002). That question framed an amusing yet profound discussion of which methods are most appropriate to understand the inner workings of a system, such as a radio. For the engineer, the answer is straightforward: you trace out the transistors, resistors, capacitors etc., and then draw an electrical circuit diagram. At that point you have understood how the radio works and have sufficient information to reproduce its function. For the biologist, as Lazebnik suggests, the answer is more complicated. You first get a hundred radios, snip out one transistor in each, and observe what happens. Perhaps the radio will make a peculiar buzzing noise that is statistically significant across the population of radios, which indicates that the transistor is necessary to make the sound normal. Or perhaps we should snip out a resistor, and then homogenize it to find out the relative composition of silicon, carbon, etc. We might find that certain compositions correlate with louder volumes, for example, or that if we modify the composition, the radio volume decreases. In the end, we might draw a kind of neat box-and-arrow diagram, in which the antenna feeds to the circuit board, and the circuit board feeds to the speaker, and the microphone feeds to the recording circuit, and so on, based on these empirical studies. The only problem is that this does not actually show how the radio works, at least not in any way that would allow us to reproduce the function of the radio given the diagram. As Lazebnik argues, even though we could multiply experiments to add pieces of the diagram, we still won’t really understand how the radio works. To paraphrase Feynmann, if we cannot recreate it, then perhaps we have not understood it (Eliasmith and Trujillo, 2014; Hawking, 2001).

Lazebnik’s argument should not be construed to disparage biological research in general. There are abundant examples of how molecular biology has led to breakthroughs, including many if not all of the pharmaceuticals currently on the market. Likewise, research in psychology has provided countless insights that have led to useful interventions, for instance in cognitive behavioral therapy (Rothbaum et al., 2000). These are valuable ends in and of themselves. Still, are we missing greater breakthroughs by not asking the right questions that would illuminate the larger picture? Within the fields of systems, cognitive, and behavioral neuroscience in particular, I fear we are in danger of losing the meaning of the Question “how does it work”? As the saying goes, if you have a hammer, everything starts to look like a nail. Having been trained in engineering as well as neuroscience and psychology, I find all of the methods of these disciplines useful. Still, many researchers are especially well-trained in psychology, and so the research questions focus predominantly on understanding which brain regions carry out which psychological or cognitive functions, following the established paradigms of psychological research. This has resulted in the question being often reframed as “what brain regions are active during what psychological processes”, or the more sophisticated “what networks are active”, instead of “what mechanisms are necessary to reproduce the essential cognitive functions and activity patterns in the system.” To illustrate the significance of this difference, consider a computer. How does it work?

**The Tale**

Once upon a time, a group of neuroscientists happened upon a computer (Carandini, 2012). Not knowing how it worked, they each decided to find out how it sensed a variety of inputs and generated the sophisticated output seen on its display. The EEG researcher quickly went to work, putting an EEG cap on the motherboard and measuring voltages at various points all over it, including on the outer case for a reference point. She found that when the hard disk was accessed, the disk controller showed higher voltages on average, and especially more power in the higher frequency bands. When there was a lot of computation, a lot of activity was seen around the CPU. Furthermore, the CPU showed increased activity in a way that is time-locked to computational demands. “See here,” the researcher declared, “we now have a fairly temporally precise picture of which regions are active, and with what frequency spectra.” But has she really understood how the computer works?

Next, the enterprising physicist and cognitive neuroscientist came along. “We don’t have enough spatial resolution to see inside the computer,” they said. So they developed a new imaging technique by which activity can be measured, called the Metabolic Radiation Imaging (MRI) camera, which now measures the heat (infrared) given off by each part of the computer in the course of its operations. At first, they found simply that lots of math operations lead to heat given off by certain parts of the CPU, and that memory storage involved the RAM, and that file operations engaged the hard disk. A flurry of papers followed, showing that the CPU and other areas are activated by a variety of applications such as word-processing, speech recognition, game play, display updating, storing new memories, retrieving from memory, etc.

Eventually, the MRI researchers gained a crucial insight, namely that none of these components can be understood properly in isolation; they must understand the network. Now the field shifts, and they begin to look at interactions among regions. Before long, a series of high profile papers emerge showing that file access does not just involve the disks. It involves a network of regions including the CPU, the RAM, the disk controller, and the disk. They know this because when they experimentally increase the file access, all of these regions show correlated increases in activity. Next, they find that the CPU is a kind of hub region, because its activity at various times correlates with activity in other regions, such as the display adapter, the disk controller, the RAM, and the USB ports, depending on what task they require the computer to perform.

Next, one of the MRI researchers has the further insight to study the computer while it is idle. He finds that there is a network involving the CPU, the memory, and the hard disk, as (unbeknownst to them) the idle computer occasionally swaps virtual memory on and off of the disk and monitors its internal temperature. This resting network is slightly different across different computers in a way that correlates with their processor speed, memory capacity, etc., and thus it is possible to predict various capacities and properties of a given computer by measuring its activity pattern when idle. Another flurry of publications results. In this way, the neuroscientists continue to refine their understanding of the network interactions among parts of the computer. They can in fact use these developments to diagnose computer problems. After studying 25 normal computers and comparing them against 25 computers with broken disk controllers, they find that the connectivity between the CPU and the disk controller is reduced in those with broken disk controllers. This allows them to use MRI to diagnose other computers with broken disk controllers. They conclude that the disk controller plays a key role in mediating disk access, and this is confirmed with a statistical mediation analysis. Someone even develops the technique of Directional Trunk Imaging (DTI) to characterize the structure of the ribbon cables (fiber tract) from the disk controller to the hard disk, and the results match the functional correlations between the hard disk and disk controller. But for all this, have they really understood how the computer works?

The neurophysiologist spoke up. “Listen here”, he said. “You have found the larger patterns, but you don’t know what the individual circuits are doing.” He then probes individual circuit points within the computer, measuring the time course of the voltage. After meticulously advancing a very fine electrode in 10 micron increments through the hard material (dura mater) covering the CPU, he finds a voltage. The particular region shows brief “bursts” of positive voltage when the CPU is carrying out math operations. As this is the math co-processor unit (unbeknownst to the neurophysiologist), the particular circuit path is only active when a certain bit of a floating point representation is active. With careful observation, the neurophysiologist identifies this “cell” as responding stochastically when certain numbers are presented for computation. The cell therefore has a relatively broad but weak receptive field for certain numbers. Similar investigations of nearby regions of the CPU yield similar results, while antidromic stimulation reveals inputs from related number-representing regions. In the end, the neurophysiologist concludes that the cells in this particular CPU region have receptive fields that respond to different kinds of numbers, so this must be a number representation area.

Finally the neuropsychologist comes along. She argues (quite reasonably) that despite all of these findings of network interactions and voltage signals, we cannot infer that a given region is necessary without lesion studies. The neuropsychologist then gathers a hundred computers that have had hammer blows to various parts of the motherboard, extension cards, and disks. After testing their abilities extensively, she carefully selects just the few that have a specific problem with the video output. She finds that among computers that don’t display video properly, there is an overlapping area of damage to the video card. This means of course that the video card is necessary for proper video monitor functioning. Other similar discoveries follow regarding the hard disks and the USB ports, and now we have a map of which regions are necessary for various functions. But for all of this, have the neuroscientists really understood how the computer works?

**The Moral**

As the above tale illustrates, despite all of our current sophisticated methods, we in neuroscience are still in a kind of early stage of scientific endeavor; we continue to discover many effects but lack a proportionally strong standard model for understanding how they all derive from mechanistic principles. There are nonetheless many individual mathematical and computational neural models. The Hodgkin-Huxley equations (Hodgkin and Huxley, 1952), Integrate-and-fire model (Izhikevich, 2003), Genesis (Bower and Beeman, 1994), SPAUN (Eliasmith et al., 2012), and Blue Brain project (Markram, 2006) are only a few examples of the models, modeling toolkits, and frameworks available, besides many others more focused on particular phenomena. Still, there are many different kinds of neuroscience models, and even many different frameworks for modeling. This means that there is no one theoretical lingua franca against which to evaluate empirical results, or to generate new predictions. Instead, there is a patchwork of models that treat some phenomena, and large gaps where there are no models relevant to existing phenomena. The moral of the story is not that the brain is a computer. The moral of the story is twofold: first, that we sorely need a foundational mechanistic, computational framework to understand how the elements of the brain work together to form functional units and ultimately generate the complex cognitive behaviors we study. Second, it is not enough for models to exist—their premises and implications must be understood by those on the front lines of empirical research.

**The Path Forward**

A more unified model shared by the community is not out of reach for neuroscience. Such exists in physics (e.g. the standard model), engineering (e.g. circuit theory), and chemistry. To move forward, we need to consider placing a similar level of value on theoretical neuroscience as for example the field of physics places on theoretical physics. We need to train neuroscientists and psychologists early in their careers in not just statistics, but also in mathematical and computational modeling, as well as dynamical systems theory and even engineering. Computational theories exist (Marr, 1982), and empirical neuroscience is advancing, but we need to develop the relationships between them. This is not to say that all neuroscientists should spend their time building computational models. Rather, every neuroscientist should at least possess literacy in modeling as no less important than, for example, anatomy. Our graduate programs generally need improvement on this front. For faculty, if one is in a soft money position or on the tenure clock and cannot afford the time to learn or develop theories, then why not collaborate with someone who can? If we really care about the question of how the brain works, we must not delude ourselves into thinking that simply collecting more empirical results will automatically tell us how the brain works any more than measuring the heat coming from computer parts will tell us how the computer works. Instead, our experiments should address the questions of what mechanisms might account for an effect, and how to test and falsify specific mechanistic hypotheses (Platt, 1964).

The Ebola response

The real failure of the Ebola response is not that a physician went bowling after returning from West Africa but that there are not more doctors over there containing the epidemic where it is needed. Infected patients do not shed virus particles until they become symptomatic and it is emitted in bodily fluids. The New York physician monitored his temperature daily and reported immediately to a designated Ebola hospital the moment he detected high fever. We should not be scape goating physicians who are trying to make a real difference in containing this outbreak and really protecting the rest of the world. This current outbreak was identified in the spring of 2014 but there was no international response until late summer. We know how to contain Ebola – identify patients and isolate them and this is what we should be doing instead of making  emotional and unhelpful policy decisions.

Unintended consequences

Here is a true story. A young man is trained to hit people as hard as possible and to react immediately to any provocation with unhindered aggression. He signs a 5 year contract for 35 million dollars to do this 16 times a year or more if he and his colleagues are very successful at doing it. One day he gets upset with his fiancée and strikes her in the head so hard that she is knocked unconscious in a public place. This creates a minor stir so the employer mandates that he must apologize and is prohibited from smashing into people for 2 of the 16 times he is scheduled to do so. The fiancée-now-spouse also refuses to press charges because she doesn’t want to jeopardize the 27 million over the next 3 years owed to the man. However, a video showing the incident is made public creating a huge uproar so the employer abruptly fires the man and condemns him since he now is no longer financially useful to the employer. The public now feels vindicated that such a despicable man is no longer employed and that domestic violence now is given the attention it deserves. However, the spouse is very unhappy because her comfortable lifestyle has just been pulled from right under her. Now, other spouses who live with violent but rich men will be even more silent about abuse because they fear losing their livelihoods too. If we really cared about victims of domestic violence, we would force the employer to set up a fund to ensure that spouses that come forward are compensated financially. We would also force them to support institutions that help the many more victims of domestic abuse who are not married to rich and famous people. This young man is probably an upstanding citizen most of the time. Now he is unemployed and potentially even angrier. He should not be thrown out onto the street but given a chance to redeem himself. The employers and the system who trained and groomed these young men need to look at themselves.

Saving large animals

One  story in the news lately is the dramatic increase in the poaching of African elephants (e.g. New York Times). Elephant numbers have plunged dramatically in the past few years and their outlook is not good. This is basically true of most large animals like whales, pandas, rhinos, bluefin tuna, whooping cranes, manatees, sturgeon, etc. However, one large animal has done extremely well while the others have languished. In the US it had a population of zero 500 years ago and now it’s probably around 100 million.That animal as you have probably guessed is the cow. While wild animals are being hunted to extinction or dying due to habitat loss and climate change, domestic animals are thriving. We have no shortage of cows, pigs, horses, dogs, and cats.

Given that current conservation efforts are struggling to save the animals we love, we may need to try a new strategy. A complete ban on ivory has not stopped the ivory trade just as a ban on illicit drugs has not stopped drug use. Prohibition does not seem to be a sure way to curb demand. It may just be that starting some type of elephant farming may be the only way to save the elephants. It could raise revenue to help protect wild elephants and could drop the price in ivory sufficiently to make poaching less profitable. It could also backfire and increase the demand for ivory.

Another counter intuitive strategy may be to sanction limited hunting of some animals. The introduction of wolves into Yellowstone park has been a resounding ecological success but it has also angered some people like ranchers and deer hunters. The backlash against the wolf has already begun. One ironic way to save wolves could be to legalize the hunting of them. This would give hunters an incentive to save and conserve wolves. Given that the set of hunters and ranchers often have a significant intersection, this could dampen the backlash. There is a big difference in attitudes towards conservation when people hunt to live versus hunting for sport. When it’s a job, we tend to hunt to extinction like  buffalo, cod, elephants, and bluefin tuna. However, when it’s for sport, people want to ensure the species thrives. While I realize that this is controversial and many people have a great disdain for hunting, I would suggest that hunting is no less humane and perhaps more than factory abattoirs.

Complete solutions to life’s little problems

One of the nice consequence of the finiteness of human existence is that there can exist complete solutions to some of our problems.  For example, I used to leave the gasoline (petrol for non-Americans) cap of my car on top of the gas pump every once in a while.  This has now been completely solved by the ludicrously simple solution of tethering the cap to the car.  I could still drive off with the gas cap dangling but I wouldn’t lose it.  The same goes for locking myself out of my car.  The advent of remote control locks has also eliminated this problem.  Because human reaction time is finite, there is also an absolute threshold for internet bandwidth above which the web browser will seem instantaneous for loading pages and simple computations.  Given our finite lifespan, there is also a threshold for the amount of disk space required to store every document, video, and photo we will ever want.  The converse is that are also more books in existence than we can possibly read in a life time although there will always be just a finite number of books by specific authors that we may enjoy.  I think one strategy for life is to make finite as many things as possible because then there is a chance for a complete solution.

The flipside of medicare efficiency

The selection of Paul Ryan as the Republican vice presidential candidate for the upcoming US federal election has brought health care reform back into the spotlight.  While the debate has been highly acrimonious, the one point that everyone seems to agree on is that the rate of increase in health care and in particular medicare spending is unsustainable.  Health care is currently one sixth of the economy and it will take up an increasing share if the growth is not reduced.  I think that a really expensive health care system may actually be a good thing.  What people tend to forget is that there are two sides of a cost.   When we pay for healthcare, that money goes to someone.  Making something more efficient, means producing the same amount of stuff with fewer people.

The official unemployment rate is currently about 8% but the actual fraction number of people who don’t work or wish they had more work is much higher.  Efficiency eliminates jobs.  People like Tom Friedman of the New York Times thinks (e.g. see here) that this will just free us up to do “creative” jobs.  However, what if you are a person that doesn’t want or is unable to do a “creative” job?  My guess is that as we become more efficient, more and more people will be left with nothing to do.  The solution is either to have a massive welfare system or we become less efficient.

However, not all inefficiencies are equal. We wouldn’t want monopolies where all the money flows to a small number of individuals.  What we need is a highly stochastic form of inefficiency that involves lots of people. Healthcare may be just what we need. It’s something that is highly decentralized and affects everyone.  It can’t be easily outsourced. I’ve argued before that having 80% of the economy be devoted to healthcare doesn’t seem that outlandish.  After all, how many flat screen TVs do you need?