Tag Archives: predictions

Argument: humans like causation because they like to feel in control

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Here is an interesting piece that summarizes some research and concludes that humans like to feel in control and therefore like the idea of causality:

This predisposition for causation seems to be innate. In the 1940s, psychologist Albert Michotte theorized that “we see causality, just as directly as we see color,” as if it is omnipresent. To make his case, he devised presentations in which paper shapes moved around and came into contact with each other. When subjects—who could only see the shapes moving against a solid-colored background—were asked to describe what they saw, they concocted quite imaginative causal stories…

Nassim Taleb noted how ridiculous this is in his book The Black Swan. In the hours after former Iraqi dictator Saddam Hussein was captured on December 13, 2003, Bloomberg News blared the headline, “U.S. TREASURIES RISE; HUSSEIN CAPTURE MAY NOT CURB TERRORISM.” Thirty minutes later, bond prices retreated and Bloomberg altered their headline: “U.S. TREASURIES FALL; HUSSEIN CAPTURE BOOSTS ALLURE OF RISKY ASSETS.” A more correct headline might have been: “U.S. TREASURIES FLUCTUATE AS THEY ALWAYS DO; HUSSEIN CAPTURE HAS NOTHING TO DO WITH THEM WHATSOEVER,” but that isn’t what editors want to post, nor what people want to read.

This trend doesn’t merely manifest itself for stocks or large events. Take scientific studies, for example. Many of the most sweeping findings, ones normally reported in large media outlets, originate from associative studies that merely correlate two variables—television watching and death, for example. Yet headlines—whose functions are partly to summarize and primarily to attract attention—are often written as “X causes Y” or “Does X cause Y?” (I have certainly been guilty of writing headlines in the latter style). In turn, the general public usually treats these findings as cause-effect, despite the fact that there may be no proven causal link between the variables. The article itself might even mention the study’s correlative, not causative, nature, and this still won’t change how it is perceived. Co-workers across the world will still congregate around coffee machines the next day, chatting about how watching The Kardashians is killing you, albeit very slowly.Humanity’s need for concrete causation likely stems from our unceasing desire to maintain some iota of control over our lives. That we are simply victims of luck and randomness may be exhilarating to a madcap few, but it is altogether discomforting to most. By seeking straightforward explanations at every turn, we preserve the notion that we can always affect our condition in some meaningful way. Unfortunately, that idea is a facade. Some things don’t have clear answers. Some things are just random. Some things simply can’t be controlled.

I like the reference to Taleb here. His books make just this argument: people want to see patterns when they don’t exist and thus are completely unprepared for changes in the stock market, governments, or the natural world. The trick is to know when you can rely on patterns and when you can’t – and Taleb even has general investment strategies in his most recent book Antifragile that try to minimize loss and try to maximize potential gains.

I wonder if this isn’t lurking behind the discussion of big data: there are scientists and others who seem to suggest that all we need to understand the world is more data and better pattern recognition tools. If only we could get enough, we could figure things out. But, what if the world turns out to be too complex? What if we can’t know everything about the social or natural world? Does this then change our perceptions of human ingenuity and progress?

h/t Instapundit

Will Nate Silver ruin his brand with NCAA predictions?

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Statistical guru Nate Silver, known for his 2012 election predictions, has been branching out into other areas recently on the New York Times site. Check out his 2013 NCAA predictions. Or look at his 2013 Oscar predictions.

While Silver has a background in sports statistics, I wonder if these forays into new areas with the imprimatur of the New York Times will eventually backfire. In many ways, these new areas have less data than presidential elections and thus, Silver has to step further out on a limb. For example, look at these predictions for the 2013 NCAA bracket:

The top pick for 2013, Louisville, only has a 22.7% chance of winning. If Silver goes with this pick of Louisville, and he does, then he by his own figures will be wrong 77.3% of the time. These are not good odds.

I’m not sure Silver can really win much by predicting the NCAA champion or the Oscars because the odds of making a wrong prediction are higher. What happens if he is wrong a number of times in a row? Will people still listen to him in the same way? What happens when the 2016 presidential election comes along? Of course, Silver could continue to develop better models and make more accurate picks but even this takes attention away from his political predictions.

Correlation and not causation: Redskins games predict results of presidential election

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Big events like presidential elections tend to bring out some crazy data patterns. Here is my nomination for the oddest one of this election season: how the Washington Redskins do in their final game before the election predicts the presidential election.

Since 1940 — when the Redskins moved to D.C. — the team’s outcome in its final game before the presidential election has predicted which party would win the White House each time but once.

When the Redskins win their game before the election, the incumbent party wins the presidential vote. If the Redskins lose, the non-incumbent wins.

The only exception was in 2004, when Washington fell to Green Bay, but George W. Bush still went on to win the election over John Kerry.

This is simply a quirk of data: how the Redskins do should have little to no effect on voting in other states. This is exactly what correlation without causation is about; there may be a clear pattern ut it doesn’t necessarily mean the two related facts cause each other. There may be some spurious association here, some variable that predicts both outcomes, but even that is hard to imagine. Yet, the Redskins Rule has garnered a lot of attention in recent days. Why? A few possible reasons:

1. It connects two American obsessions: presidential elections and the NFL. A sidelight: both may involve a lot of betting.

2. So much reporting has been done on the 2012 elections that this adds a more whimsical and mysterious element.

3. Humans like to find patterns, even if these patterns don’t make much sense.

What’s next, an American octopus who can predict presidential elections?

A call to “begin creating synthetic sociology”

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Two academics call for “synthetic sociology”:

Well, it’s time we begin creating synthetic sociology. Along with Nicholas Christakis, I recently laid out the potential for this new field:

We wanted to see if this could be done in humans. Like crabs, humans have specific kinds of behavior that can be predicted, in groups. To harness this, we created a survey on Amazon’s Mechanical Turk, surveying lots of people at once.

We asked a couple hundred people to complete a string of 1’s and 0’s, and asked them to make it “as random as possible.” As it happens, people are fairly bad at generating random numbers—there is a broad human tendency to suppose that strings must alternate more than they do. And what we found in our Mechanical Turk survey was exactly this: Predictably, people would generate a nonrandom number. For example, faced with 0, 0, there was about a 70 percent chance the next number would be 1.

From this single behavioral quirk, it is theoretically possible to construct a way in which a group of humans can act as what is known as a logic gate in computer science. By running such a question through a survey of enough people, and feeding those results to other people, you can turn them into what computer scientists call a “NOR” gate—a tool to take two pieces of binary input and yield consistent answers. And with just a handful of NOR gates, you can make a binary adder, a very simple computing device that can add two numbers together.

What this means is that, given sufficient numbers of people, and their willingness to answer questions about random bits, we can re-deploy humans for a purpose they were not intended, namely to act as a kind of computer—doing anything from adding two bits to running Microsoft Word (albeit really, really slowly).

On one hand, it sounds like we are far from using these methods to have humans finish complicated tasks yet, on the other hand, this continues to build upon research about social networks and how information and other traits can be passed along and built on in a group of people. As these academics suggest, we have come some distance in recent decades in understanding and modeling human behavior and advances are likely to continue to come in the near future.

This also isn’t the first time that I have heard of social scientists using Amazon’s Mechanical Turk for studies. For a relatively small amount of money, researchers can find a willing group of participants for experiments or other tasks.

Debating the reliability of social science research

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A philosopher argues social science research is not that reliable and therefore should have a limited impact on public policy:

Without a strong track record of experiments leading to successful predictions, there is seldom a basis for taking social scientific results as definitive.  Jim Manzi, in his recent book, “Uncontrolled,” offers a careful and informed survey of the problems of research in the social sciences and concludes that “nonexperimental social science is not capable of making useful, reliable and nonobvious predictions for the effects of most proposed policy interventions.”

Even if social science were able to greatly increase their use of randomized controlled experiments, Manzi’s judgment is that “it will not be able to adjudicate most policy debates.” Because of the many interrelated causes at work in social systems, many questions are simply “impervious to experimentation.”   But even when we can get reliable experimental results, the causal complexity restricts us to “extremely conditional, statistical statements,” which severely limit the range of cases to which the results apply.

My conclusion is not that our policy discussions should simply ignore social scientific research.  We should, as Manzi himself proposes, find ways of injecting more experimental data into government decisions.  But above all, we need to develop a much better sense of the severely limited reliability of social scientific results.   Media reports of research should pay far more attention to these limitations, and scientists reporting the results need to emphasize what they don’t show as much as what they do.

Given the limited predictive success and the lack of consensus in social sciences, their conclusions can seldom be primary guides to setting policy.  At best, they can supplement the general knowledge, practical experience, good sense and critical intelligence that we can only hope our political leaders will have.

Several quick thoughts:

1. There seems to be some misunderstanding about the differences between the social and natural sciences. The social sciences don’t have laws in the same sense that the natural sciences do. People don’t operate like planets (to pick up on one of the examples). Social behaviors change over time in response to changing conditions and this makes study more difficult.

2. There is a heavy emphasis in this article on experiments. However, these are more difficult to conduct in the social realm: it is hard to control for all sorts of possible influential factors, have a sizable enough N to make generalizations, and experiments in the “harder sciences” like medicine have some of their own issues (see this critique of medical studies).

3. Saying the social sciences have some or a little predictive ability is different than saying they have none. Having some knowledge of social life is better than none when crafting policy, right?

4. Leaders should have “the general knowledge, practical experience, good sense and critical intelligence” to be able to make good decisions. Are these qualities simply individualistic or could social science help inform and create these abilities?

5. While there are limitations to doing social science research, there are also ways that researchers can increase the reliability and validity of studies. These techniques are not inconsequential; there are big differences between good research methods and bad research methods in what kind of data they produce. There is a need within social science to think about “big science” more often rather than pursuing smaller, limited studies but these studies than can speak to broader questions typically require more data and analysis which in turn requires more resources and time.

Shiller makes more dire prediction: “we might not see a really major [housing] turnaround in our lifetimes”

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I highlighted about a month ago a prediction from economist Robert Shiller that suburban housing values may not recover anytime soon. Shiller made another prediction this past week that is even more dire:

The housing market is likely to remain weak and may take a generation or more to rebound, Yale economics professor Robert Shiller told Reuters Insider on Tuesday.

Shiller, the co-creator of the Standard & Poor’s/Case-Shiller home price index, said a weak labor market, high gas prices and a general sense of unease among consumers was outweighing low mortgage rates and would likely keep a lid on prices for the foreseeable future.

“I worry that we might not see a really major turnaround in our lifetimes,” Shiller said.

Shiller is the most pessimistic prognosticator about the housing market I’ve seen. Is this earning him credibility or scorn?

By the way, is there any academic or impartial observer who keeps track of such predictions? I thought about this during the NFL draft: think how many hours and days were wasted coming up with mock drafts that are based on one-seventh of the draft and often have mistakes. What is the same number of hours and days was devoted to trying to predict the outcome of the US housing market in the coming months and years – would the predictions get any better?

Lots of sociological themes in Time’s “10 ideas that are changing your life”

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I enjoy reading magazines and other media sources that are willing to consider the world of ideas and what new thinking we all need to know about. Thus, Time’s “10 ideas that are changing your life” are not only interesting – there is a lot of sociological material in these ten ideas. Here are a few sociological musings about four of these ideas:

1. “Living Alone is the New Norm.” I’ve highlighted some of the recent reviews of the new research from sociologist Eric Klinenberg (see here and here) that shows that Americans living alone “make up 28% of all U.S. households, which means they are now tied with childless couples as the most prominent residential type, more common than the nuclear family, the multigenerational family and roommate or group home.” Another interesting line: “Living alone helps us pursue sacred modern values – individual freedom, personal control and self-realization.” That is an interesting trio of values to mull over.

3. “The Rise of the Nones.” Sixteen percent of Americans claim to be non-religious but this group is particularly interesting because 4% claim to be agnostic or atheist. Thus, many of the “nones” are spiritual or religious but dissatisfied with organized religion. This group can be examined as part of a larger debate about whether American religion is declining or not. This also presents a challenge for organized religion: how do you get these religious or spiritual “nones” to buy into established houses of worship?

7. “High-Status Stress.” New findings suggest that people in charge or in the higher classes experience more stress: “In fact, research indicates that as you near the top, life stress increases so dramatically that its toxic effects essentially cancel out many positive aspects of succeeding.” It may not be easy to be at the top even if you have the power and ability to do more of what you want. I’m not sure how this would affect the class struggles between the upper and lower classes but it is interesting information nonetheless.

9. “Nature is Over.” Humans have altered the earth in many ways, doing so much so that our conception of nature might need to change: “The reality is that in the Anthropocene, there may simply be no room for nature, at least not nature as we’ve known and celebrated it – something separate from human beings – something pristine. There’s no getting back to the Garden [of Eden], assuming it ever existed.” This reminds me of the romanticism of nature in the mid 1800s that influenced how early American suburbs were created (designing winding streets to preserve pastoral views) and how Central Park was created (meant to preserve a piece of nature in the midst of the big city). More realistically, neither city parks or most suburbs really present much of nature – based on an idea in James Howard Kunstler’s TED talk about suburbs, these are more elaborate “nature band-aids.”

Several of the other ideas have sociological implications as well.

Reading through this list, it reminds me of how much I enjoy reading and talking about new ideas and where society might be going. If I could get all of my students to share this enthusiasm and develop a capacity to seek out and interact with ideas on their own (using the critical thinking skills and other tools they have picked up in college), it would make me happy.

Researchers develop an equation to help predict the next hit song

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A team of researchers says they have developed an equation that helps predict which songs will become hit singles. Here is how the equation works:

We represent each song using a set of 23 different features that characterize the audio. Some are very simple features — such as how fast it is, how long the song is — and some are more complex features, such as how energetic the song is, how loud it is, how danceable and how stable the beat is throughout the song. We also took into account the highest rank that songs ever achieved on the chart.

The computer can combine a song’s features in an equation that can be used to score any given song.

We can then evaluate how accurately the computer scored it by seeing how well the song actually did.

Every single week now we’re updating our equation based on how recent releases have done on the chart. So the equation will continue to evolve, because music tastes will evolve as well.

As the researchers note, this equation is based mainly on the musical content and doesn’t factor in the content of the lyrics or budgeting for the song and music group. The equation seems mainly to be based on whatever musical styles and changes are already popular so I wonder how they account for changes in musical periods.

If this equation works well (and the interview doesn’t really say how accurate this formula is for new songs), this could be a big boon for the culture industries. The movie, music, and book industry all struggle with this: it is very difficult to predict which works will become popular. There are ways in which companies try to hedge their bets either by working with established stars/performers/authors, working with established stories and characters (more sequels, anyone?), and trying to read the cultural zeitgeist (more vampires!). But, in the end, the industries can survive because enough of the works become blockbusters and help subsidize the rest.

At the same time, haven’t people claimed they have cracked this code before? For example, you can quickly find people (like this and this) who claim they have it figured out. And yet, revenues and ticket sales were down in 2011. There is a disconnect here…

Thinking about the future of suburbs in Levittown

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At the end of a retrospective article about Levittown, CNN considers the future of the suburbs:

It’s a hot issue in academia to think about what suburbs may become.

An upcoming exhibit at the New York Museum of Modern Art, called Foreclosed: Rehousing the American Dream, proposes several visions, including one that would integrate nature more sustainably into the suburbs and another that would try to make suburban neighborhoods denser.

Something has to change, said Barry Bergdoll, MoMA’s curator for architecture and design, or we will “roll the suburban carpet across all the open land that is left.”

“It’s just irresponsible to have a model that encourages moving out onto green fields and leaving behind decaying rings of an ever-fattening tree,” he said. “I’m interested in not just letting the path of least resistance exist. It’s cheaper for a developer to build on virgin territory, but it’s not cheaper for people to live on it or get to it.”

This year, another group of designers descended on Levittown to imagine “a future suburbia” in the place where the concept was hatched…

For a day, a designer named Claudia Linders turned Dwyer’s Levitt home into an “Attention Clinic.” Patrons sat in her living room and waited for a chance to receive advice, attention and/or hugs from Dwyer and two actors.

The idea was to make suburbia profitable rather than just a place where people live.

“They kept choosing me (for advice), I guess because I was older and wiser,” Dwyer said, cracking a smile. “Because these actresses, they were beautiful.”

All this attention confused Dwyer, who said she was happy to give out advice to strangers but felt somewhat unqualified to make life decisions for them.

There was a real chance here to share with the public what academics forecast for American suburbs. For my six predictions for American suburbs for 2012, read here. But here is what this article went with:

1. A typical critique that suburbs take up too much open land and by focusing resources on suburbs, other locations are impoverished. These opinions aren’t necessarily wrong (indeed, the densification of the suburbs is a popular topic today) but these ideas have been around for decades.

2. This last bit about the “Attention Clinic” seems more like performance art than a viable option for American suburbs. What exactly is this supposed to illustrate?

This is a puzzling selection of “what the suburbs may become.” While the earlier parts of the article hit some key elements that make Levittown unique including its mass production and its race relations, the last part of the article is a missed opportunity.

Six predictions for American suburbs in 2012

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Since this is the time of year for predictions, here are my six broad predictions for American suburbs in 2012:

1. The suburbs will continue to be the space of choice for Americans even as critics argue they are bland, environmentally untenable, and ultimately unsustainable.

2. At the same time, because of the economic crisis, continuing trends in design, and different tastes among Millennials and retiring baby boomers, suburbs will be pursuing denser projects with more certain long-term outcomes.

3. Many suburbs and other local taxing bodies (school districts, etc.) will struggle to find revenue. The budget deficits at the federal and state levels will continue to trickle down. Many communities will struggle to fund basic services.

4. Minorities, immigrants, and lower-class residents will continue to move to the suburbs and more strongly challenge the image of suburbs as lily-white havens. Some suburbs will struggle to adapt. Wealthier suburbs will continue to look for ways to limit these changes.

5. The issues of funding and revenues will trump concerns like providing social services for new populations, being environmentally-friendly, and providing affordable housing. Some will argue these communities would likely stonewall these concerns regardless.

6. Regarding single-family homes: McMansions will continue to be disparaged, the size of the average new home will drop again, the problems with foreclosures will continue, the President and Congress will continue to express how the single-family home is the foundation of the American Dream, and affordable housing will still be unpopular.

(Note: I’ve written about these trends throughout 2011 and I plan to keep writing about them in 2012. While these predictions are somewhat vague, it is difficult to describe trends across all suburbs as they are a varied lot.)