Review: The Science of Fear

Today, I read The Science of Fear (2008) by Daniel Gardner. It’s a remarkably well-done book for what it is – namely, a journalist’s (informed) overview of some of the psychological components of fear, and a large number of example as to how people exploit that tendency to fear.

It’s a nice book because he relies on rather well-accepted psychological research, while going into great depth on examples. It helps people to understand that these principles actually mean something.

On the other hand, for those people who were looking for a explanation about how fear works inside the brain – such as myself – it’s a bit lacking. And the reliance on solid psychological principles means I didn’t learn any new psychology. Regardless, I enjoyed the read because it was well-written and interesting.

In lieu of a review, allow me to review some of his points. In the course of the book, Mr. Gardner outlined three ways the brain screws up, leading people to irrational fears.

1. The Availability Heuristic

The availability heuristic is a pretty good rule. It’s a general cognitive bias – pretty robust across all humans – and works out to people predicting the probability of events in proportion to how many instances of it they can recall (are available).

If you do something a lot – work on computers, go hunting, etc – then over time you establish a battery of experiences. If someone asked you how probable something was, you could reach back into your experience and get a feel for how many times you’ve seen it – and give a pretty good example.

The big advantage is that it’s computationally very fast. If you need to make a split-second decision, you want it to be fast.

It’s also extensible: that is, people don’t differentiate between their own experiences (memories) and other people’s (stories). This works out really well if you talk to people who do the same thing as you do – say, a bunch of hunters sitting around a fire swapping stories. That way, you can tap into the knowledge of your entire community (if you haven’t yet experienced it, you don’t know how common it is – hearing stories of experiences can both ameliorate your ignorance and give you ideas of what to do to deal with it).

But therein lies the rub. The media specialize in providing stories – really compelling anecdotes – about things that happen. The brain doesn’t differentiate based on sources, so the availability heuristic can be screwed in the incorrect direction. People vastly overestimate the risk of terrorism, kidnappings, and murder; but vastly underestimate the risk of car accidents, drowning, diabetes, etc.

2. Confirmation Bias

Confirmation bias is an old favorite of psychologists, simply because it explains so much.

It’s pretty simple, actually. Once you believe something, your brain tends to look for other instances of it – confirming instances. It does not, however, look for falsifying instances for your belief. Sometimes, your brain will even change it’s recollection of the facts to conform to your current belief (one example is the “rose-colored glasses” effect; you believe the past was better, so you unconsciously modify your memories of the past to make it match your belief).

But it also means once you believe something about, say, terrorism, you’ll focus on the positive (that is, supporting) instances – and ignore the others. No terrorist attacks does not affect your belief about the danger of terrorism even though a terrorist attack down – which is illogical. It’s a binary outcome, therefore one outcome value  should be just a good a predictor as the other. The brain doesn’t think so.

A rather insidious effect of confirmation bias concerns the use of statistics. If you believe someone, and you come across a statistic (or a story) you disagree with, you’re going to scrutinize it very closely. If, however, you come across a statistic which supports your belief – then, hey, no need to question the source or the methodology, it’s obviously correct. People apply different levels of evaluation to information that conforms with their existing beliefs to information that violates their existing beliefs.

3. The Urge to Conform

Conformity has been studied a great deal, and the results are pretty consistent. When people are in a group and a task is difficult, you see more conformity. That is, lower confidence in the result for any one individual means that people are more willing to accept a group consensus. Funnily enough, though, each individual’s belief in the accuracy and reliability of the group consensus goes way up – even though the confidence of any individual’s conclusion is low.

Mr. Gardner makes the important point that conformity actually serves a good purpose. If you’re on the African plains, and everyone around you begins to get worried about a tiger in the grass – well, even if you can’t see the tiger yourself, there’s a pretty good reason to take precautions. More formally, it allows all members of a group to take advantage of the knowledge from all members of the group, and not rely on their own knowledge all the time.

The problem is that once a belief has taken hold in the general population, it’s bloody hard to get rid of. The combination of conformity – people fall into line – and the confirmation bias means that as a group, people don’t deal with falsifying evidence well at all. Mr. Gardner goes through a hilarious number of examples showing that (i) people say they believe something because of the evidence, (ii) you prove the evidence is wrong, (iii) people still believe it despite accepting that the evidence is wrong.

A Passing Note

In addition to those three psychological features, Mr. Gardner notes a few other issues. Here’s one I found striking.

It has to do with pointing out how badly people deal with numbers. People have no innate ability to deal with numerical data; though they do have a pretty good ability to deal with proportions. Unfortunately, this isn’t a good thing.

Mr. Gardner gives a great example. Take two groups of people: in both, tell them they are reviewing how much money to devote to improving airport safety. Tell the first group that implementing the precautions will save 150 lives; tell the second that it will save 98% of 150 lives. Consistently, people rate saving 98% of 150 lives higher than 150 lives (that is, the second group would devote more money to the project then the first group, even though they were saving objectively fewer people).

And don’t get started on how bad people are with probability – it doesn’t bear thinking about.

A Brief Conclusion

The Science of Fear rests on some good psychology, and goes into a large number of examples as to how human reason fails us when it comes to knowing what to fear.

The real effect of the book is to persuade people to be less afraid; it reduces fear. Mr. Gardner systematically goes through most hot-button political issues, and shows how the data doesn’t back up the fear-mongering. Not only is he persuasive, but he writes in such a fashion that you’ll pick up an innate skepticism of the media (if you didn’t already have it) and a deeper skepticism for anecdotes (if you have no statistical background).

It’s certainly worth the time just for that.

Google is Omnipotent

The halo effect has graduated from inflating stock prices to making companies godlike. Thus, they can do anything – mere mortals can just speculate. The truth, however, is frequently mundane.

Taylor Buley, writing on the Velocity blog at Forbes, has the provocative title of “Google Isn’t Just Reading Your Links, It’s Now Running Your Code.” Mr. Buley goes onto explain that “for years it’s been unclear whether or not the Googlebot actually understood what it was looking at or whether it was merely doing "’dumb’ searches for well-understood data structured like hyperlinks.” In other word, Google has built a Javascript interpreter!

The source for this headline comes directly from Google:

On Friday, a Google spokesperson confirmed to Forbes that Google does indeed go beyond mere "parsing" of JavaScript. "Google can parse and understand some JavaScript," said the spokesperson.

So it’s confirmed, then.

Mr. Buler spends most of his article explaining that building a Javascript parser is really fucking hard. In fact, a quote from one of his experts isolates the key problem – how long the code will run – and says that “The halting problem is undecidable," There is no algorithm that can solve it. Well, OK, I suppose, but couldn’t you process a lot and cut it off at an arbitrary point? Sure you’d miss some stuff, but surely you’d get enough?

Actually, that’s what another expert says:

"It’s hard to analyze a program using another program," the person says. "Executing [JavaScript code] is pretty much that’s the only way they can do it."

Mr. Buler believes this is a great accomplishment, and quite unknown.

He’s right on one count.

In a previous post, I cited a paper “Data Management Projects at Google” and talked about Edward Chang. Well, the paper is actually about three projects, and one of those is “Indexing the Deep Web,” spearheaded by Jayan Madhavan. In that 2008 paper, Dr. Madhavan had this to say about Javascript:

While our surfacing approach has generated considerable
traffic, there remains a large number of forms that continue
to present a significant challenge to automatic analysis. For
example, many forms invoke Javascript events in onselect
and onsubmit tags that enable the execution of arbitrary
Javascript code, a stumbling block to automatic analysis.
Further, many forms involve inter-related inputs and accessing
the sites involve correctly (and automatically) identifying
their underlying dependencies. Addressing these and
other such challenges efficiently on the scale of millions is
part of our continuing effort to make the contents of the
Deep Web more accessible to search engine users

It would seem they solved this problem! (This is a big accomplishment). When did they solve it? Recently?

Well, sort of. In a 2009 paper called “Harnessing the Deep Web: Past, Present, and Future.” In it, they say this:

We note that the canonical example of correlated inputs,
namely, a pair of inputs that specify the make and model of
cars (where the make restricts the possible models) is typically
handled in a form by Javascript. Hence, by adding a
Javascript emulator to the analysis of forms, one can identify
such correlations easily.

So let’s back up.

What is Google going? They’re accessing structured data hidden behind form submissions. Now, we say the information is “hidden” behind form submissions because you have to submit the form to get the data. One approach – the ”dumb” approach – is to generate all possible result URLs and then crawl all of them.

But. Those clever folks at Google noticed this might be a problem:

For example, the search form on cars.com has 5 inputs and a Cartesian product will yield over 200 million URLs, even though cars.com has only 650,000 cars on sale.

The challenge, then, is making fewer URLs. Thus, they intelligently developed an algorithm with this property:

We have found that the number of URLs our algorithms generate is proportional to the size of the underlying database, rather than the number of possible queries.

How do they do this? Well, one big challenge is (as noted above) the inputs in one field can depend on the inputs in another field. Google has taken to constructing databases of “interrelated data” (like manufacturer and car model) so they can automatically detect the data the form wants and limit their indexing accordingly.

But to detect when some fields on a form are interrelated, you… need to have more than the HTML. In fact, almost all input-dependent forms rely on Javascript to change the values around after a selection.

Well, the clever researchers at Google knew they needed to determine which fields in a form were interrelated. They also figured that they only needed to determine this once, because once they knew which fields were related, they could automatically generate their URLs using their generation algorithms.

As you can imagine, if you only need to do it once (for each form), then it becomes practical to emulate. You emulate one form, and get 650,000 URLs to index with solid data. It’s cheap – so cheap, it’s almost worth getting a human to do it. (Except no Googler would think of that!).

But – and here’s the thing – to emulate the behavior of a form driven by Javascript you have to have the Javascript files. You need to download them, and then execute them.

In other words, the second expert Mr. Buley consulted is spot-on. Google is executing the Javascript code to find out something very specific (which fields on a form are interrelated, and presumably anything done in an onsubmit event that would alter the indexing URL).

This is not news. It’s publically available information – very easily, though Google Scholar, and even easier if you’re following Google’s main researchers – and there is no reason to resort to speculation to answer the question. They’ve been accessing the Deep Web – the web hidden behind forms – for years; Javascript is an obvious stumbling block; Google researchers have papers published on it (frequently presented at conferences!).

It is galling to see a reporter say that something is “unclear” when it is very difficult to make something clearer. In 2008, Jayant Madhavan wrote on the Google Webmaster Central blog talks about crawling through forms to get to the Deep Web – this stuff isn’t restricted to academic papers easily accessible through Google Scholar and surfaced in regular Google results. No, it’s even in the blogosphere.

I think I’ve gone a bit too far, so I’ll stop now.

General McChrystal: Exposed

David Brooks has a column today on the debacle created by the Rolling Stones report on General Stanley McChrystal. Ignoring the politics (why did the Rolling Stones reporter adopt that specific narrative, which he knew would result in political controversy?), there are a couple of points Mr. Brooks raises which I think are worth addressing.

The Psychology of Groups

First, he points out that it’s natural for people in small groups to complain about people on other groups as a way to relieve stress and build a sense of community. He is quite right about this; contemporary research in social psychology has demonstrated, time and again, that people (i) believe that their group is better, and (ii) have less awareness of people in other groups as people.

Possibly the best book on the subject, The Psychology of Stereotyping by David Schneider, goes into this in depth (I highly recommend the book). To summarize,

the “Tajfel effect” occurs when people have ingroup bias for no reason. The most obvious example in the real world is the attachment people develop to sports team from the cities they live in. Why do people associate so strongly with a certain team just because they live nearby? The most striking psychological example is the “minimal group” situation. If you take a set of people and divide them into two groups in a completely arbitrary fashion – say, flipping a coin – then even if you tell them ahead of time how the groups were divided, people show ingroup bias. That is, if you survey people they believe that their group is on average smarter, more attractive, etc. (This effect is robust, i.e. it holds true if you measure it in a different way – say, eliminating surveys).

The second effect is that people in the group will try to maximize ingroup differentiation (and minimize outgroup differentiation – e.g. “Those Muslims are all the same”). It’s a way, in essence, of “dehumanizing” people who are different from you. Why? Well, the easy answer is that everyone has limited cognitive power. You take shortcuts and, in general, while it’s very important to know how people in your own groups are different from each other, it’s essentially irrelevant to know the same information for people you don’t identify with. All you really need to know are attributes (or stereotypes) like “snakes tend to be dangerous” or “maggots are bad.” Applied to people, it can be “jocks tend to be dumb” or “politicians tend to lie.” Limited interactions mean you don’t need to know any more…. you just need to know enough to deal with them if you encounter them.

Thus, it’s not surprising that Genera McChrystal’s group exhibited (as Rolling Stones reported) “arrogance” about their own capabilities and denigrated people who (i) they didn’t deal with much, and (ii) whom they had nothing in common with. If you have something in common with someone, then you are by definition part of some group – and even if it’s a weak tie, the same ingroup/outgroup bias comes into play (just weaker, obviously).

In fact, it’s important to note that the fact that General McChrystal’s team exhibited such behavior. It demonstrates that he had a unified group. The Rolling Stones report really shows a healthy team. Why? Because the General was taking people from ostensibly different groups (computer geeks from MIT, special ops, soldiers, etc) and fusing them into a unified team. It’s very important to note that they complained about other people outside of the group. It would be very easy, in contrast, for the special ops guys to whinge about the computer geeks, or soldiers, etc. They didn’t: they complained about people outside the group.

That is, in fact, an indication of General McChrystal’s “greatness,” and is something – as Rolling Stones noted – which has given him such a reputation: the ability to pull people from multiple different backgrounds and construct a highly functional team.

The Cult of Personality

The second point David Brooks makes is encapsulated by this paragraph:

Then, after Vietnam, an ethos of exposure swept the culture. The assumption among many journalists was that the establishment may seem upstanding, but there is a secret corruption deep down. It became the task of journalism to expose the underbelly of public life, to hunt for impurity, assuming that the dark hidden lives of public officials were more important than the official performances.

I can’t really disagree with him: reading politics or watching the news is no longer about policies is about the personal lives of the politicians. “Would we like this guy if we met him in a bar?” or “Do we want to imitate this guy?” when, really, such concerns are patently irrelevant to the quality of the job they do.

Popular success is not determined on results; it is determined by personality.

Politicians have become celebrities. They establish a personal brand, and suck people into believe that they are a certain “type of person.”

It’s an interesting extension of the representative democracy model. We elect politicians who make political judgments for us – that is, they represent our collective interests, ideally. With the cult of personality, we elect people who seem like “our kind of people” and trust them to make the kind of decisions we’d like them to make. Thus, instead of judging a politician on how well they represented our interests, we judge them on whether or not we still feel like we have something in common with them.

Politicians as a proxy for people; personality as a proxy for ideology.

Of course, the sad thing is that personality is a terribly proxy for either ideology or effectiveness.

It’s also a classic lesson in Peter Drucker’s wisdom that “You can’t manage what you don’t measure” and “what’s measured improved.”

And as politicians learn how important their personality “brand” is, they become obsessed on maintaining that brand. But they found – particularly with the rise of TV – that managing their personality brand has very little to do with passing legislation. On the other hand, it has a great deal to do with (i) sound-bytes, and (ii) relationships with other politicians, and (iii) endorsements by famous people (and other politicians).

As such, the “personality brand” of politicians improves. But everything extraneous to that – e.g. actually reading the laws they’re voting on – deteriorates, because it has no impact on what’s being measured.

In fact, personality has become so important that people think the results (which personality is acting as a proxy for) is irrelevant.

Such is the fate of General McChrystal. He is – according to many on both sides of the political divide – highly capable, has proven success in multiple arenas, and is showing success in Afghanistan. Yet his personality has been judged lacking, due to the highly filtered view of it (and his team) provided by the Rolling Stones reporter.

Mr. Brooks is correct when he calls the “exposure ethos” damaging. But he misdiagnosis the problem – it’s not exposure, per say, it’s exposure of the wrong things. Actions are something we should care about – such as Nixon’s ethical abuses. Not “kvetching” as Mr. Brooks calls it; healthy team dynamics (that should be kept within the team).