Logan Paul and the Algorithms of Outrage

Leaving aside the issues of “Did Logan Paul actually do anything wrong?” and “Is changing YouTube’s policies actually in Game Theorist’s interests?” Game Theorist makes a good point: while YouTube might want to say, for PR reasons, that it is doing something about big, bad, controversial videos like Logan Paul’s, it also makes money off those same videos. YouTube–like many other parts of the internet–is primarily click driven. (Few of us are paying money for programs on YouTube Red.) YouTube wants views, and controversy drives views.

That doesn’t mean YouTube wants just any content–a reputation for having a bunch of pornography would probably have a damaging effect on channels aimed at small children, as their parents would click elsewhere. But aside from the actual corpse, Logan’s video wasn’t the sort of thing that would drive away small viewers–they’d get bored of the boring non-cartoons talking to the camera long before the suicide even came up.

Logan Paul actually managed to hit a very sweet spot: controversial enough to draw in visitors (tons of them) but not so controversial that he’d drive away other visitors.

In case you’ve forgotten the controversy in a fog of other controversies, LP’s video about accidentally finding a suicide in the Suicide Forest was initially well-received, racking up thousands of likes and views before someone got offended and started up the outrage machine. Once the outrage machine got going, public sentiment turned on a dime and LP was suddenly the subject of a full two or three days of Twitter hate. The hate, of course, got YouTube more views. LP took down the video and posted an apology–which generated more attention. Major media outlets were now covering the story. Even Tablet managed to quickly come up with an article: Want a New Years Resolution? Don’t be Like Logan Paul.

And it worked. I passed up Tablet’s regular article on Trump and Bagels and Culture, but I clicked on that article about Logan Paul because I wanted to know what on earth Tablet had to say about LP, a YouTuber whom, 24 hours prior, I had never heard of.

And the more respectable (or at least highly-trafficked) news outlets picked up the story, the higher Logan’s videos rose on the YouTube charts. And as more people watched more of LP’s other videos, they found more things to be offended at. For example, once he ran through the streets of Japan holding a fish. A FISH, I tell you. He waved this fish at people and was generally very annoying.

I don’t like LP’s style of humor, but I’m not getting worked up over a guy waving a fish around.

So understand this: you are in an outrage machine. The purpose of the outrage machine is to drive traffic, which makes clicks, which result in ad revenue. There are probably whole websites (Huffpo, CNN) that derive a significant percent of their profits from hate-clicks–that is, intentionally posting incendiary garbage not because they believe it or think it is just or true or appeals to their base, but because they can get people to click on it in sheer shock or outrage.

Your emotions–your “emotional labor” as the SJWs call it–is being turned into someone else’s dollars.

And the result is a country that is increasingly polarized. Increasingly outraged. Increasingly exhausted.

Step back for a moment. Take a deep breath. Get some fresh air. Ask yourself, “Does this really matter? Am I actually helping anyone? Will I remember this in a week?”

I’d blame the SJWs for the outrage machine–and really, they are good running it–but I think it started with CNN and “24 hour news.” You have to do something to fill that time. Then came Fox News, which was like CNN, but more controversial in order to lure viewers away from the more established channel. Now we have the interplay of Facebook, Twitter, HuffPo, online newspapers, YouTube, etc–driven largely by automated algorithms designed to maximized clicks–even hate clicks.

The Logan Paul controversy is just one example out of thousands, but let’s take a moment and think about whether it really mattered. Some guy whose job description is “makes videos of his life and posts them on YouTube” was already shooting a video about his camping trip when he happened upon a dead body. He filmed the body, called the police, canceled his camping trip, downed a few cups of sake while talking about how shaken he was, and ended the video with a plea that people seek help and not commit suicide.

In between these events was laughter–I interpret it as nervous laughter in an obviously distressed person. Other people interpret this as mocking. Even if you think LP was mocking the deceased, I think you should be more concerned that Japan has a “Suicide Forest” in the first place.

Let’s look at a similar case: When three year old Alan Kurdi drowned, the photograph of his dead body appeared on websites and newspapers around the world–earning thousands of dollars for the photographers and news agencies. Politicans then used little Alan’s death to push particular political agendas–Hillary Clinton even talked about Alan Kurdi’s death in one of the 2016 election debates. Alan Kurdi’s death was extremely profitable for everyone making money off the photograph, but no one got offended over this.

Why is it acceptable for photographers and media agencies to make money off a three year old boy who drowned because his father was a negligent fuck who didn’t put a life vest on him*, but not acceptable for Logan Paul to make money off a guy who chose to kill himself and then leave his body hanging in public where any random person could find it?

Elian Gonzalez, sobbing, torn at gunpoint from his relatives. BTW, This photo won the 2001 Pulitzer Prize for Breaking News.

Let’s take a more explicitly political case. Remember when Bill Clinton and Janet Reno sent 130 heavily armed INS agents to the home of child refugee Elian Gonzalez’s relatives** so they could kick him out of the US and send him back to Cuba?

Now Imagine Donald Trump sending SWAT teams after sobbing children. How would people react?

The outrage machine functions because people think it is good. It convinces people that it is casting light on terrible problems that need correcting. People are getting offended at things that they wouldn’t have if the outrage machine hadn’t told them to. You think you are serving justice. In reality, you are mad at a man for filming a dead guy and running around Japan with a fish. Jackass did worse, and it was on MTV for two years. Game Theorist wants more consequences for people like Logan Paul, but he doesn’t realize that anyone can get offended at just about anything. His videos have graphic descriptions of small children being murdered (in videogame contexts, like Five Nights at Freddy’s or “What would happen if the babies in Mario Cart were involved in real car crashes at racing speeds?”) I don’t find this “family friendly.” Sometimes I (*gasp*) turn off his videos as a result. Does that mean I want a Twitter mob to come destroy his livelihood? No. It means a Twitter mob could destroy his livelihood.

For that matter, as Game Theorist himself notes, the algorithm itself rewards and amplifies outrage–meaning that people are incentivised to create completely false outrage against innocent people. Punishing one group of people more because the algorithm encourages bad behavior in other people is cruel and does not solve the problem. Changing the algorithm would solve the problem, but the algorithm is what makes YouTube money.

In reality, the outrage machine is pulling the country apart–and I don’t know about you, but I live here. My stuff is here; my loved ones are here.

The outrage machine must stop.

*I remember once riding in an airplane with my father. As the flight crew explained that in the case of a sudden loss of cabin pressure, you should secure your own mask before assisting your neighbors, his response was a very vocal “Hell no, I’m saving my kid first.” Maybe not the best idea, but the sentiment is sound.

**When the boat Elian Gonzalez and his family were riding in capsized, his mother and her boyfriend put him in an inner tube, saving his life even though they drowned.

Do Sufficiently Large Organizations Start Acting Like Malevolent AIs? (pt 2)

(Part 1 is here)

As we were discussing on Monday, as our networks have become more effective, our ability to incorporate new information may have actually gone down. Ironically, as we add more people to a group–beyond a certain limit–it becomes more difficult for individuals with particular expertise to convince everyone else in the group that the group’s majority consensus is wrong.

The difficulties large groups experience trying to coordinate and share information force them to become dominated by procedures–set rules of behavior and operation are necessary for large groups to operate. A group of three people can use ad-hoc consensus and rock-paper-scissors to make decisions; a nation of 320 million requires a complex body of laws and regulations. (I once tried to figure out just how many laws and regulations America has. The answer I found was that no one knows.)

An organization is initially founded to accomplish some purpose that benefits its founders–generally to make them well-off, but often also to produce some useful good or service. A small organization is lean, efficient, and generally exemplifies the ideals put forth in Adam Smith’s invisible hand:

It is not from the benevolence of the butcher, the brewer, or the baker, that we expect our dinner, but from their regard to their own interest. We address ourselves, not to their humanity but to their self-love, and never talk to them of our necessities but of their advantages. —The Wealth Of Nations, Book I

As an organization ages and grows, its founders retire or move on, it becomes more dependent on policies and regulations and each individual employee finds his own incentives further displaced from the company’s original intentions. Soon a company is no longer devoted to either the well-being of its founders or its customers, but to the company itself. (And that’s kind of a best-case scenario in which the company doesn’t just disintegrate into individual self-interest.)

I am reminded of a story about a computer that had been programmed to play Tetris–actually, it had been programmed not to lose at Tetris. So the computer paused the game. A paused game cannot lose.

What percentage of employees (especially management) have been incentivized to win? And what percentage are being incentivized to not lose?

And no, I don’t mean that in some 80s buzzword-esque way. Most employees have more to lose (ie, their jobs) if something goes wrong as a result of their actions than to gain if something goes right. The stockholders might hope that employees are doing everything they can to maximize profits, but really, most people are trying not to mess up and get fired.

Fear of messing up goes beyond the individual scale. Whole companies are goaded by concerns about risk–“Could we get sued?” Large corporation have entire legal teams devoted to telling them how they could get sued for whatever their doing and to filing lawsuits against their competitors for whatever they’re doing.

This fear of risk carries over, in turn, to government regulations. As John Sanphillipo writes in City Regulatory Hurdles Favor Big Developers, not the Little Guy:

A family in a town I visited bought an old fire station a few years ago with the intention of turning it into a Portuguese bakery and brewpub. They thought they’d have to retrofit the interior of the building to meet health and safety standards for such an establishment.

Turns out the cost of bringing the landscape around the outside of the building up to code was their primary impediment. Mandatory parking requirements, sidewalks, curb cuts, fire lanes, on-site stormwater management, handicapped accessibility, drought-tolerant native plantings…it’s a very long list that totaled $340,000 worth of work. … Guess what? They decided not to open the bakery or brewery. …

Individually it’s impossible to argue against each of the particulars. Do you really want to deprive people in wheelchairs of the basic civil right of public accommodation? Do you really want the place to catch fire and burn? Do you want a barren landscape that’s bereft of vegetation? …

I was in Hamtramck, Michigan a couple of years ago to participate in a seminar about reactivating neighborhoods through incremental small-scale development. …

While the event was underway the fire marshal happened to drive by and noticed there were people—a few dozen actual humans—occupying a commercial building in broad daylight. In a town that has seen decades of depopulation and disinvestment, this was an odd sight. And he was worried. Do people have permission for this kind of activity? Had there been an inspection? Was a permit issued? Is everything insured? He called one of his superiors to see if he should shut things down in the name of public safety.

It’s a good article. You should read the whole thing.

Back in Phillipe Bourgeois’s In Search of Respect: Selling Crack in el Barrio, Phillipe describes one drug dealer’s attempt to use the money he’d made to go into honest business by opening a convenience store. Unfortunately, he couldn’t get the store complaint with NYC disability-access regulations, and so the store never opened and the owner went back to dealing drugs. (What IQ, I wonder, is necessary to comply with all of these laws and regulations in the first place?)

Now, I’m definitely in favor of disabled people being able to buy groceries and use bathrooms. But what benefits a disabled person more: a convenience store that’s not fully wheel-chair accessible, or a crack house?

In My IRB Nightmare, Scott Alexander writes about trying to do a simple study to determine whether the screening test already being used to diagnose people with bipolar disorder is effective at diagnosing them:

When we got patients, I would give them the bipolar screening exam and record the results. Then Dr. W. would conduct a full clinical interview and formally assess them. We’d compare notes and see how often the screening test results matched Dr. W’s expert diagnosis.

Remember, they were already using the screening test on patients and then having them talk to the doctor for a formal assessment. The only thing the study added was that Scott would compare how well the screening results matched the formal assessment. No patients would be injected, subject to new procedures, or even asked different questions. They just wanted to compare two data sets.

After absurd quantities of paperwork and an approval process much too long to summarize here, the project got audited:

I kept the audit report as a souvenier. I have it in front of me now. Here’s an example infraction:

The data and safety monitoring plan consists of ‘the Principal Investigator will randomly check data integrity’. This is a prospective study with a vulnerable group (mental illness, likely to have diminished capacity, likely to be low income) and, as such, would warrant a more rigorous monitoring plan than what is stated above. In addition to the above, a more adequate plan for this study would also include review of the protocol at regular intervals, on-going checking of any participant complaints or difficulties with the study, monitoring that the approved data variables are the only ones being collected, regular study team meetings to discuss progress and any deviations or unexpected problems. Team meetings help to assure participant protections, adherence to the protocol. Having an adequate monitoring plan is a federal requirement for the approval of a study. See Regulation 45 CFR 46.111 Criteria For IRB Approval Of Research. IRB Policy: PI Qualifications And Responsibility In Conducting Research. Please revise the protocol via a protocol revision request form. Recommend that periodic meetings with the research team occur and be documented.

… Faced with submitting twenty-seven new pieces of paperwork to correct our twenty-seven infractions, Dr. W and I gave up. We shredded the patient data and the Secret Code Log. We told all the newbies they could give up and go home. … We told the IRB that they had won, fair and square; we surrendered unconditionally.

The point of all that paperwork and supervision is to make sure that no one replicates the Tuskegee Syphilis Experiment nor the Nazi anything. Noble sentiments–but as a result, a study comparing two data sets had to be canceled.

I’ve noticed recently that much of the interesting medical research is happening in the third world/China–places where the regulations aren’t as strong and experiments (of questionable ethics or not) can actually get done.

Like the computer taught not to lose at Tetris, all of these systems are more focused on minimizing risk–even non-existent risk–than on actually succeeding.

In his review of Yudkowsky’s Inadequate Equilibria, Scott writes:

…[Yudkowsky] continues to the case of infant parenteral nutrition. Some babies have malformed digestive systems and need to have nutrient fluid pumped directly into their veins. The nutrient fluid formula used in the US has the wrong kinds of lipids in it, and about a third of babies who get it die of brain or liver damage. We’ve known for decades that the nutrient fluid formula has the wrong kind of lipids. We know the right kind of lipids and they’re incredibly cheap and there is no reason at all that we couldn’t put them in the nutrient fluid formula. We’ve done a bunch of studies showing that when babies get the right nutrient fluid formula, the 33% death rate disappears. But the only FDA-approved nutrient fluid formula is the one with the wrong lipids, so we just keep giving it to babies, and they just keep dying. Grant that the FDA is terrible and ruins everything, but over several decades of knowing about this problem and watching the dead babies pile up, shouldn’t somebody have done something to make this system work better?

The doctors have to use the FDA-approved formula or they could get sued for malpractice. The insurance companies, of course, only cover the FDA-approved formula. The formula makers are already making money selling the current formula and would probably have to go through an expensive, multi-year review system (with experiments far more regulated than Scott’s) to get the new formula approved, and even then they might not actually get approval. In short, on one side are people in official positions of power whose lives could be made worse (or less convenient) if they tried to fix the problem, and on the other side are dead babies who can’t stand up for themselves.

The Chankiri Tree (Killing Tree) where infants were fatally smashed, Choeung Ek, Cambodia.

Communism strikes me as the ultimate expression of this beast: a society fully transformed into a malevolent AI. It’s impossible to determine exactly how many people were murdered by communism, but the Black Book of Communism estimates a death toll between 85 and 100 million people.

Capitalism, for all its faults, is at least somewhat decentralized. If you make a bad business decision, you suffer the consequences and can hopefully learn from your mistakes and make better decisions in the future. But in communist systems, one central planner’s bad decisions can cause suffering for millions of other people, resulting in mass death. Meanwhile, the central planner may suffer for correcting the bad decision. Centralized economies simply lack the feedback loops necessary to fix problems before they start killing people.

While FDA oversight of medicines is probably important, would it be such a bad thing if a slightly freer market in parenteral nutrition allowed parents to chose between competing brands of formula, each promising not to kill your baby?

Of course, capitalism isn’t perfect, either. SpottedToad recently had an interesting post, 2010s Identity Politics as Hostile AI:

There’s an interesting post mortem on the rise and fall of the clickbait liberalism site Mic.com, that attracted an alleged 65 million unique visitors on the strength of Woketastic personal stories like “5 Powerful Reasons I’m a (Male) Feminist,” …

Every time Mic had a hit, it would distill that success into a formula and then replicate it until it was dead. Successful “frameworks,” or headlines, that went through this process included “Science Proves TK,” “In One Perfect Tweet TK,” “TK Reveals the One Brutal Truth About TK,” and “TK Celebrity Just Said TK Thing About TK Issue. Here’s why that’s important.” At one point, according to an early staffer who has since left, news writers had to follow a formula with bolded sections, which ensured their stories didn’t leave readers with any questions: The intro. The problem. The context. The takeaway.

…But the success of Mic.com was due to algorithms built on top of algorithms. Facebook targets which links are visible to users based on complex and opaque rules, so it wasn’t just the character of the 2010s American population that was receptive to Mic.com’s specific brand of SJW outrage clickbait, but Facebook’s rules for which articles to share with which users and when. These rules, in turn, are calibrated to keep users engaged in Facebook as much as possible and provide the largest and most receptive audience for its advertisers, as befits a modern tech giant in a two-sided market.

Professor Bruce Charlton has a post about Head Girl Syndrome–the Opposite of Creative Genius that is good and short enough that I wish I could quote the whole thing. A piece must suffice:

The ideal Head Girl is an all-rounder: performs extremely well in all school subjects and has a very high Grade Point Average. She is excellent at sports, Captaining all the major teams. She is also pretty, popular, sociable and well-behaved.

The Head Girl will probably be a big success in life, in whatever terms being a big success happens to be framed …

But the Head Girl is not, cannot be, a creative genius. …

The more selective the social system, the more it will tend to privilege the Head Girl and eliminate the creative genius.

Committees, peer review processes, voting – anything which requires interpersonal agreement and consensus – will favour the Head Girl and exclude the creative genius.  …

*

We live in a Head Girl’s world – which is also a world where creative genius is marginalized and disempowered to the point of near-complete invisibility.

The quest for social status is, I suspect, one of the things driving the system. Status-oriented people refuse to accept information that comes from people lower status than themselves, which renders system feedback even more difficult. The internet as a medium of information sharing is beautiful; the internet as a medium of status signalling is horrible.

So what do you think? Do sufficiently large organization start acting like malevolent (or hostile) AIs?

(Back to Part 1)

Do Sufficiently Large Organizations Start Acting Like Malevolent AIs? (pt 1)

(and Society is an Extremely Large Organization)

What do I mean by malevolent AI?

AI typically refers to any kind of intelligence or ability to learn possessed by machines. Malevolent AI occurs when a machine pursues its programmed objectives in a way that humans find horrifying or immoral. For example, a machine programmed to make paperclips might decide that the easiest way to maximize paperclip production is to enslave humans to make paperclips for it. Superintelligent AI is AI that has figured out how to make itself smarter and thus keeps getting smarter and smarter. (Should we develop malevolent superintelligent AI, then we’ll really have something to worry about.)

Note: people who actually study AI probably have better definitions than I do.

While we like to think of ourselves (humans) as unique, thinking individuals, it’s clear that many of our ideas come from other people. Chances are good you didn’t think up washing your hands or brushing your teeth by yourself, but learned about them from your parents. Society puts quite a bit of effort, collectively speaking, into teaching children all of the things people have learned over the centuries–from heliocentrism to the fact that bleeding patients generally makes diseases worse, not better.

Just as we cannot understand the behavior of ants or bees simply by examining the anatomy of a single ant or single bee, but must look at the collective life of the entire colony/hive, so we cannot understand human behavior by merely examining a single human, but must look at the collective nature of human societies. “Man is a political animal,” whereby Aristotle did not mean that we are inherently inclined to fight over transgender bathrooms, but instinctively social:

Hence it is evident that the state is a creation of nature, and that man is by nature a political animal. And he who by nature and not by mere accident is without a state, is either above humanity, or below it; he is the ‘Tribeless, lawless, hearthless one,’ whom Homer denounces—the outcast who is a lover of war; he may be compared to a bird which flies alone.

Now the reason why man is more of a political animal than bees or any other gregarious animals is evident. Nature, as we often say, makes nothing in vain, and man is the only animal whom she has endowed with the gift of speech. And whereas mere sound is but an indication of pleasure or pain, and is therefore found in other animals (for their nature attains to the perception of pleasure and pain and the intimation of them to one another, and no further), the power of speech is intended to set forth the expedient and inexpedient, and likewise the just and the unjust. And it is a characteristic of man that he alone has any sense of good and evil, of just and unjust, and the association of living beings who have this sense makes a family and a state. –Aristotle, Politics

With very rare exceptions, humans–all humans, in all parts of the world–live in groups. Tribes. Families. Cities. Nations. Our nearest primate relatives, chimps and bonobos, also live in groups. Primates are social, and their behavior can only be understood in the context of their groups.

Groups of humans are able to operate in ways that individual humans cannot, drawing on the collective memories, skills, and knowledge of their members to create effects much greater than what could be achieved by each person acting alone. For example, one lone hunter might be able to kill a deer–or if he is extremely skilled, hardworking, and lucky, a dozen deer–but ten hunters working together can drive an entire herd of deer over a cliff, killing hundreds or even thousands. (You may balk at the idea, but many traditional hunting societies were dependent on only a few major hunts of migrating animals to provide the majority of their food for the entire year–meaning that those few hunts had to involve very high numbers of kills or else the entire tribe would starve while waiting for the animals to return.)

Chimps have never, to my knowledge, driven megafauna to extinction–but humans have a habit of doing so wherever they go. Humans are great at what we do, even if we aren’t always great at extrapolating long-term trends.

But the beneficial effects of human cooperation don’t necessarily continue to increase as groups grow larger–China’s 1.3 billion people don’t appear to have better lives than Iceland’s 332,000 people. Indeed, there probably is some optimal size–depending on activity and available communications technology–beyond which the group struggles to coordinate effectively and begins to degenerate.

CBS advises us to make groups of 7:

As it turns out, seven is a great number for not only forming an effective fictional fighting force, but also for task groups that use spreadsheets instead of swords to do their work.

That’s according to the new book Decide & Deliver: 5 Steps to Breakthrough Performance in Your Organization (Harvard Business Press).

Once you’ve got 7 people in a group, each additional member reduces decision effectiveness by 10%, say the authors, Marcia W. Blenko, Michael C. Mankins, and Paul Rogers.

Unsurprisingly, a group of 17 or more rarely makes a decision other than when to take a lunch break.

Princeton blog reports:

The trope that the likelihood of an accurate group decision increases with the abundance of brains involved might not hold up when a collective faces a variety of factors — as often happens in life and nature. Instead, Princeton University researchers report that smaller groups actually tend to make more accurate decisions, while larger assemblies may become excessively focused on only certain pieces of information. …

collective decision-making has rarely been tested under complex, “realistic” circumstances where information comes from multiple sources, the Princeton researchers report in the journal Proceedings of the Royal Society B. In these scenarios, crowd wisdom peaks early then becomes less accurate as more individuals become involved, explained senior author Iain Couzin, a professor of ecology and evolutionary biology. …

The researchers found that the communal ability to pool both pieces of information into a correct, or accurate, decision was highest in a band of five to 20. After that, the accurate decision increasingly eluded the expanding group.

Couzin found that in small groups, people with specialized knowledge could effectively communicate that to the rest of the group, whereas in larger groups, they simply couldn’t convey their knowledge to enough people and group decision-making became dominated by the things everyone knew.

If you could travel back in time and propose the idea of democracy to the inhabitants of 13th century England, they’d respond with incredulity: how could peasants in far-flung corners of the kingdom find out who was running for office? Who would count the votes? How many months would it take to tally up the results, determine who won, and get the news back to the outlying provinces? If you have a printing press, news–and speeches–can quickly and accurately spread across large distances and to large numbers of people, but prior to the press, large-scale democracy simply wasn’t practical.

Likewise, the communism of 1917 probably couldn’t have been enacted in 1776, simply because society at that time didn’t have the technology yet to gather all of the necessary data on crop production, factory output, etc. (As it was, neither did Russia of 1917, but they were closer.)

Today, the amount of information we can gather and share on a daily basis is astounding. I have at my fingertips the world’s greatest collection of human knowledge, an overwhelming torrent of data.

All of our these information networks have linked society together into an increasingly efficient meta-brain–unfortunately, it’s not a very smart meta-brain. Like the participants in Couzin’s experiments, we are limited to what “everyone knows,” stymied in our efforts to impart more specialized knowledge. (I don’t know about you, but I find being shouted down by a legion of angry people who know less about a subject than I do one of the particularly annoying features of the internet.)

For example, there’s been a lot of debate lately about immigration, but how much do any of us really know about immigrants or immigrant communities? How much of this debate is informed by actual knowledge of the people involved, and how much is just people trying to extend vague moral principles to cover novel situations? I recently had a conversation with a progressive acquaintance who justified mass-immigration on the grounds that she has friendly conversations with the cabbies in her city. Heavens protect us–I hope to get along with people as friends and neighbors, not just when I am paying them!

One gets the impression in conversation with Progressives that they regard Christian Conservatives as a real threat, because that group that can throw its weight around in elections or generally enforce cultural norms that liberals don’t like, but are completely oblivious to the immigrants’ beliefs. Most of our immigrants hail from countries that are rather more conservative than the US and definitely more conservative than our liberals.

Any sufficiently intelligent democracy ought to be able to think critically about the political opinions of the new voters it is awarding citizenship to, but we struggle with this. My Progressive acquaintance seems think that we can import an immense, conservative, third-world underclass and it will stay servile indefinitely, not vote its own interests or have any effects on social norms. (Or its interests will be, coincidentally, hers.)

This is largely an information problem–most Americans are familiar with our particular brand of Christian conservatives, but are unfamiliar with Mexican or Islamic ones.

How many Americans have intimate, detailed knowledge of any Islamic society? Very few of us who are not Muslim ourselves speak Arabic, and few Muslim countries are major tourist destinations. Aside from the immigrants themselves, soldiers, oil company employees, and a handful of others have spent time in Islamic countries, but that’s about it–and no one is making any particular effort to listen to their opinions. (It’s a bit sobering to realize that I know more about Islamic culture than 90% of Americans and I still don’t really know anything.)

So instead of making immigration policy based on actual knowledge of the groups involved, people try to extend the moral rules–heuristics–they already have. So people who believe that “religious tolerance is good,” because this rule has generally been useful in preventing conflict between American religious groups, think this rule should include Muslim immigrants. People who believe, “I like being around Christians,” also want to apply their rule. (And some people believe, “Groups are more oppressive when they’re the majority, so I want to re-structure society so we don’t have a majority,” and use that rule to welcome new immigrants.)

And we are really bad at testing whether or not our rules are continuing to be useful in these new situations.

 

Ironically, as our networks have become more effective, our ability to incorporate new information may have actually gone down.

The difficulties large groups experience trying to coordinate and share information force them to become dominated by procedures–set rules of behavior and operation are necessary for large groups to operate. A group of three people can use ad-hoc consensus and rock-paper-scissors to make decisions; a nation of 320 million requires a complex body of laws and regulations.

But it’s getting late, so let’s continue this discussion in the next post.