Entries Tagged "cheating"

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Detecting Cheaters

Our brains are specially designed to deal with cheating in social exchanges. The evolutionary psychology explanation is that we evolved brain heuristics for the social problems that our prehistoric ancestors had to deal with. Once humans became good at cheating, they then had to become good at detecting cheating—otherwise, the social group would fall apart.

Perhaps the most vivid demonstration of this can be seen with variations on what’s known as the Wason selection task, named after the psychologist who first studied it. Back in the 1960s, it was a test of logical reasoning; today, it’s used more as a demonstration of evolutionary psychology. But before we get to the experiment, let’s get into the mathematical background.

Propositional calculus is a system for deducing conclusions from true premises. It uses variables for statements because the logic works regardless of what the statements are. College courses on the subject are taught by either the mathematics or the philosophy department, and they’re not generally considered to be easy classes. Two particular rules of inference are relevant here: modus ponens and modus tollens. Both allow you to reason from a statement of the form, "if P, then Q." (If Socrates was a man, then Socrates was mortal. If you are to eat dessert, then you must first eat your vegetables. If it is raining, then Gwendolyn had Crunchy Wunchies for breakfast. That sort of thing.) Modus ponens goes like this:

If P, then Q. P. Therefore, Q.

In other words, if you assume the conditional rule is true, and if you assume the antecedent of that rule is true, then the consequent is true. So,

If Socrates was a man, then Socrates was mortal. Socrates was a man. Therefore, Socrates was mortal.

Modus tollens is more complicated:

If P, then Q. Not Q. Therefore, not P.

If Socrates was a man, then Socrates was mortal. Socrates was not mortal. Therefore, Socrates was not a man.

This makes sense: if Socrates was not mortal, then he was a demigod or a stone statue or something.

Both are valid forms of logical reasoning. If you know "if P, then Q" and "P," then you know "Q." If you know "if P, then Q" and "not Q," then you know "not P." (The other two similar forms don’t work. If you know "if P, then Q" and "Q," you don’t know anything about "P." And if you know "if P, then Q" and "not P," then you don’t know anything about "Q.")

If I explained this in front of an audience full of normal people, not mathematicians or philosophers, most of them would be lost. Unsurprisingly, they would have trouble either explaining the rules or using them properly. Just ask any grad student who has had to teach a formal logic class; people have trouble with this.

Consider the Wason selection task. Subjects are presented with four cards next to each other on a table. Each card represents a person, with each side listing some statement about that person. The subject is then given a general rule and asked which cards he would have to turn over to ensure that the four people satisfied that rule. For example, the general rule might be, "If a person travels to Boston, then he or she takes a plane." The four cards might correspond to travelers and have a destination on one side and a mode of transport on the other. On the side facing the subject, they read: "went to Boston," "went to New York," "took a plane," and "took a car." Formal logic states that the rule is violated if someone goes to Boston without taking a plane. Translating into propositional calculus, there’s the general rule: if P, then Q. The four cards are "P," "not P," "Q," and "not Q." To verify that "if P, then Q" is a valid rule, you have to verify modus ponens by turning over the "P" card and making sure that the reverse says "Q." To verify modus tollens, you turn over the "not Q" card and make sure that the reverse doesn’t say "P."

Shifting back to the example, you need to turn over the "went to Boston" card to make sure that person took a plane, and you need to turn over the "took a car" card to make sure that person didn’t go to Boston. You don’t—as many people think—need to turn over the "took a plane" card to see if it says "went to Boston" because you don’t care. The person might have been flying to Boston, New York, San Francisco, or London. The rule only says that people going to Boston fly; it doesn’t break the rule if someone flies elsewhere.

If you’re confused, you aren’t alone. When Wason first did this study, fewer than 10 percent of his subjects got it right. Others replicated the study and got similar results. The best result I’ve seen is "fewer than 25 percent." Training in formal logic doesn’t seem to help very much. Neither does ensuring that the example is drawn from events and topics with which the subjects are familiar. People are just bad at the Wason selection task. They also tend to only take college logic classes upon requirement.

This isn’t just another "math is hard" story. There’s a point to this. The one variation of this task that people are surprisingly good at getting right is when the rule has to do with cheating and privilege. For example, change the four cards to children in a family—"gets dessert," "doesn’t get dessert," "ate vegetables," and "didn’t eat vegetables"—and change the rule to "If a child gets dessert, he or she ate his or her vegetables." Many people—65 to 80 percent—get it right immediately. They turn over the "ate dessert" card, making sure the child ate his vegetables, and they turn over the "didn’t eat vegetables" card, making sure the child didn’t get dessert. Another way of saying this is that they turn over the "benefit received" card to make sure the cost was paid. And they turn over the "cost not paid" card to make sure no benefit was received. They look for cheaters.

The difference is startling. Subjects don’t need formal logic training. They don’t need math or philosophy. When asked to explain their reasoning, they say things like the answer "popped out at them."

Researchers, particularly evolutionary psychologists Leda Cosmides and John Tooby, have run this experiment with a variety of wordings and settings and on a variety of subjects: adults in the US, UK, Germany, Italy, France, and Hong Kong; Ecuadorian schoolchildren; and Shiriar tribesmen in Ecuador. The results are the same: people are bad at the Wason selection task, except when the wording involves cheating.

In the world of propositional calculus, there’s absolutely no difference between a rule about traveling to Boston by plane and a rule about eating vegetables to get dessert. But in our brains, there’s an enormous difference: the first is a arbitrary rule about the world, and the second is a rule of social exchange. It’s of the form "If you take Benefit B, you must first satisfy Requirement R."

Our brains are optimized to detect cheaters in a social exchange. We’re good at it. Even as children, we intuitively notice when someone gets a benefit he didn’t pay the cost for. Those of us who grew up with a sibling have experienced how the one child not only knew that the other cheated, but felt compelled to announce it to the rest of the family. As adults, we might have learned that life isn’t fair, but we still know who among our friends cheats in social exchanges. We know who doesn’t pay his or her fair share of a group meal. At an airport, we might not notice the rule "If a plane is flying internationally, then it boards 15 minutes earlier than domestic flights." But we’ll certainly notice who breaks the "If you board first, then you must be a first-class passenger" rule.

This essay was originally published in IEEE Security & Privacy, and is an excerpt from the draft of my new book.

EDITED TO ADDD (4/14): Another explanation of the Wason Selection Task, with a possible correlation with psychopathy.

Posted on April 7, 2011 at 1:10 PMView Comments

Hacking Scratch Lottery Tickets

Design failure means you can pick winning tickets before scratching the coatings off. Most interesting is that there’s statistical evidence that this sort of attack has been occurring in the wild: not necessarily this particular attack, but some way to separate winners from losers without voiding the tickets.

Since this article was published in Wired, another technique of hacking scratch lottery tickets has surfaced: store clerks capitalizing on losing streaks. If you assume any given package of lottery tickets has a similar number of winners, wait until you sell most of the way through the packet without seeing those winners and then buy the rest.

Posted on February 10, 2011 at 6:42 AMView Comments

Football Match Fixing

Detecting fixed football (soccer) games.

There is a certain buzz of expectation, because Oscar, one of the fraud analysts, has spotted a game he is sure has been fixed.

“We’ve been watching this for a couple of weeks now,” he says.

“The odds have gone to a very suspicious level. We believe that this game will finish in an away victory. Usually an away team would have around a 30% chance of winning, but at the current odds this team is about 85% likely to win.”

[…]

Often news of the fix will leak so that gamblers jump on the bandwagon. The game we are watching falls, it seems, into the second category.

Oscar monitors the betting at half-time. He is especially interested in money being laid not on the result itself, but on the number of goals that are going to be scored.

“The most likely score lines are 2-1 or 3-1,” he announces.

This is interesting:

Oscar is also interested in the activity of a club manager – but his modus operandi is somewhat different. He does not throw games. He wins them.

[…]

“The reason he’s so important is because he has relationships with all his previous clubs. He has managed at least three or four of the teams he is now buying wins against. He has also managed a lot of players from the opposition, who are being told to lose these matches.”

I always think of fixing a game as meaning losing it on purpose, not winning it by paying the other team to lose.

Posted on December 3, 2010 at 12:41 PMView Comments

Term Paper Writing for Hire

This recent essay (commentary here) reminded me of this older essay, both by people who write student term papers for hire.

There are several services that do automatic plagiarism detection—basically, comparing phrases from the paper with general writings on the Internet and even caches of previously written papers—but detecting this kind of custom plagiarism work is much harder.

I can think of three ways to deal with this:

  1. Require all writing to be done in person, and proctored. Obviously this won’t work for larger pieces of writing like theses.
  2. Semantic analysis in an attempt to fingerprint writing styles. It’s by no means perfect, but it is possible to detect if a piece of writing looks nothing like a student’s normal writing style.
  3. In-person quizzes on the writing. If a professor sits down with the student and asks detailed questions about the writing, he can pretty quickly determine if the student understand what he claims to have written.

The real issue is proof. Most colleges and universities are unwilling to pursue this without solid proof—the lawsuit risk is just too great—and in these cases the only real proof is self-incrimination.

Fundamentally, this is a problem of misplaced economic incentives. As long as the academic credential is worth more to a student than the knowledge gained in getting that credential, there will be an incentive to cheat.

Related note: anyone remember my personal experience with plagiarism from 2005?

Posted on November 16, 2010 at 6:36 AMView Comments

Detecting Cheating at Colleges

The measures used to prevent cheating during tests remind me of casino security measures:

No gum is allowed during an exam: chewing could disguise a student’s speaking into a hands-free cellphone to an accomplice outside.

The 228 computers that students use are recessed into desk tops so that anyone trying to photograph the screen—using, say, a pen with a hidden camera, in order to help a friend who will take the test later—is easy to spot.

Scratch paper is allowed—but it is stamped with the date and must be turned in later.

When a proctor sees something suspicious, he records the student’s real-time work at the computer and directs an overhead camera to zoom in, and both sets of images are burned onto a CD for evidence.

Lots of information on detecting cheating in homework and written papers.

Posted on July 9, 2010 at 6:34 AMView Comments

Cheating on Tests, by the Teachers

If you give people enough incentive to cheat, people will cheat:

Of all the forms of academic cheating, none may be as startling as educators tampering with children’s standardized tests. But investigations in Georgia, Indiana, Massachusetts, Nevada, Virginia and elsewhere this year have pointed to cheating by educators. Experts say the phenomenon is increasing as the stakes over standardized testing ratchet higher—including, most recently, taking student progress on tests into consideration in teachers’ performance reviews.

Posted on June 21, 2010 at 12:01 PMView Comments

Wrasse Punish Cheaters

Interesting:

The bluestreak cleaner wrasse (Labroides dimidiatus) operates an underwater health spa for larger fish. It advertises its services with bright colours and distinctive dances. When customers arrive, the cleaner eats parasites and dead tissue lurking in any hard-to-reach places. Males and females will sometimes operate a joint business, working together to clean their clients. The clients, in return, dutifully pay the cleaners by not eating them.

That’s the basic idea, but cleaners sometimes violate their contracts. Rather than picking off parasites, they’ll take a bite of the mucus that lines their clients’ skin. That’s an offensive act—it’s like a masseuse having an inappropriate grope between strokes. The affronted client will often leave. That’s particularly bad news if the cleaners are working as a pair because the other fish, who didn’t do anything wrong, still loses out on future parasite meals.

Males don’t take this sort of behaviour lightly. Nichola Raihani from the Zoological Society of London has found that males will punish their female partners by chasing them aggressively, if their mucus-snatching antics cause a client to storm out.

[…]

At first glance, the male cleaner wrasse behaves oddly for an animal, in punishing an offender on behalf of a third party, even though he hasn’t been wronged himself. That’s common practice in human societies but much rarer in the animal world. But Raihani’s experiments clearly show that the males are actually doing themselves a favour by punishing females on behalf of a third party. Their act of apparent altruism means they get more food in the long run.

Posted on January 20, 2010 at 1:26 PMView Comments

Computer Card Counter Detects Human Card Counters

All it takes is a computer that can track every card:

The anti-card-counter system uses cameras to watch players and keep track of the actual “count” of the cards, the same way a player would. It also measures how much each player is betting on each hand, and it syncs up the two data points to look for patterns in the action. If a player is betting big when the count is indeed favorable, and keeping his chips to himself when it’s not, he’s fingered by the computer… and, in the real world, he’d probably receive a visit from a burly dude in a bad suit, too.

The system reportedly works even if the gambler intentionally attempts to mislead it with high bets at unfavorable times.

Of course it does; it’s just a signal-to-noise problem.

I have long been impressed with the casino industry’s ability to, in the case of blackjack, convince the gambling public that using strategy equals cheating.

Posted on October 20, 2009 at 6:16 AMView Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.