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Archive for February, 2011

How to make better friendly wagers

Using the technique described in this blog post, my girlfriend was able to stick to more than a half dozen simultaneous self improvement behaviors in one month. These were all behaviors she had tried to cultivate without success before. How was she able to suddenly beat beat inertia and achieve what she wanted? Simple: she and I made a wager.

As someone who enjoys being competitive, I often find myself wanting to make bets with people. Not substantive $500 bets or anything, but little friendly wagers. My favorite kind of wagers are those that require people to put effort into affecting the results. For instance, betting someone you can or can’t gain 5 pounds of muscle in 2 weeks, or eat 35 cupcakes in one sitting, or run from your house to the gym in less than 5 minutes with fewer than 7 days of training. And for the purposes of this short blog, I want to focus on this kind of willpower wager. When you make willpower wagers correctly, they can be a powerful force for self improvement, entertainment, and relationship building. My surprising realization is that it’s actually fairly simple to change betting behavior from a divisive zero sum game into a mutually beneficial lifestyle behavior. In three simple steps here’s how to do it:

1) Pick a challenge.

Choose something you have been avoiding, but know you ought to do. It must be something that you wouldn’t do otherwise but know you should. It is very important that you choose a truly difficult challenge [1], as you will see in the next step. For example, hand-writing and mailing 3 letters a week to friends, or going to the gym for 30 minutes a day, or cutting a particular food from your diet for a month. Although health-related goals spring immediately to mind, there are massive categories of other difficult self improvement challenges. If you are a web designer, learning how to use that new programming language in 10 days might be something you propose. If you are a writer, pushing out an additional 3 chapters in your novel in 10 days would be an enormous challenge. Once you’ve put together a list of several challenges you’ve been avoiding, you need to quantify them. You can’t just say you will exercise more, you need to specify that you will do 30 minutes of intense cardio 4 times weekly. You can’t just say that you will drink less Sprite, you have to say you won’t drink any for 3 weeks. After you’ve come up with some measurable goals, you are ready to go to the next step.

2) Make your friend call “bullshit.”

Now here’s the trick: you must now present your challenge to a close friend. If you have chosen a challenge audacious enough, your close friend should respond with something akin to “bullshit, you can’t do that.” If he nods and says something like “good luck,” you either need to find a more critical friend, or more likely, you haven’t come up with a big enough challenge. As soon as you get the incredulous response, you’re good to go.

Now, ask him to make a wager with you, then repeat step 1 but with his interests. For instance, he might be staying up too late consistently and he need an enforced curfew. He may have been putting off getting thesis approval for their Ph.D, or any number of other personal challenges. If you succeed at your challenge, he must ante up and complete his. If you fail, you must cede something of importance to you that he wants, just like any normal bet.

Changing that single winning situation being good for the winner only, to being good for both parties fundamentally changes how the bet feels when concluded. Instead of being frustrated when one person gains at another person’s expense, the wager has the potential to benefit both parties while still maintaining the dynamics of a competitive bet. If you succeed, you have accomplished personal goals and now have a socially binding reason to force your friend to do the same. If you lose, your friend gets something he wants and you can try again.

Example: I am a candy addict. I know it’s bad for me and so does my girlfriend. So, when my girlfriend came up with a challenge for herself, I offered to go without candy for a month if she accomplished the challenge [2]. In another challenge I wagered that if I failed to succeed, I had to admit failure to those closest to me  and my betting partner [3].

3) Make it last.

Once both you and your friend have agreed on the exact specifications of the challenge and the cost of failing, you’re golden. I have found that challenges that last several weeks tend to be the optimal period. The time allows for both parties to talk a little smack, get competitive, and tell others about the wager. This last point is unexpectedly important. Challenges like this are great conversation pieces, and it creates even more social binding which encourages fulfillment.

An Example

So here’s an example of how this actually works: back in December, a friend of mine claimed that he could maintain 19 strict self-improvement rules for 30 days. Rules included heavy diet modification, physical exercise, a curfew, set amounts of work on personal projects, etc. I of course called bullshit and wagered that he couldn’t do it. We agreed that if he succeeded, I had to have a cupcake eating competition with him. Nick likes eating competitions, and I have long wanted to try one, but didn’t have the motivation to try on my own. If Nick failed, however, he had to buy me $40 worth of sugary treats from a nearby candy warehouse [4]. This was a great wager because Nick seriously disapproved of my candy habit and abetting it was loathsome to him. On the flip side, I wanted to see how many cupcakes I could eat, but wasn’t willing to try it without external motivation. He ended up winning and you can read more about the cupcake-eating here.

Conclusion

The result of making willpower wagers with friends is that you actually do the things you always wish you would, get to compete a little in the process, and share an experience with someone close to you. If you succeed at your challenge, your friend may feel a little miffed, but he is also likely to feel impressed that you wrote those 3 chapters in your novel or learned how to code a tiny webapp in an unknown language in 10 days. You’ll find that as long as you stick to the steps, you can chew your way through New Year’s resolutions in no time and have fun doing it.

[1] In my experience, the more challenging the bet, the better. If you told someone that you were going to exercise twice a week for 15 minutes, they probably would believe you capable of the feat. If you said that you were going to practice for 15 minutes in the morning and 15 minutes in the evening every day, that would seem far less feasible. The harder the challenge, the more likely you are to rise to it, get competitive, and actually get other people to wager with you.

[2] I lost that one and have been candy-free for 30 days. I’m hoping I can maintain the streak!

[3] As with all parts of the wager, you have to specify the terms exactly. In this case, I had to tell my girlfriend, mother, father, brother, and best friend.

[4] This happened before the wager in which I lost my candy privileges.

How I Almost Failed a Facebook Turing Test

A week ago I finished a blog post and discovered that WordPress had a new Facebook promotion feature. I decided to bite the bullet and Facebook-promote myself. After all, most of my friends use Facebook, even if I don’t.

It had been a while since I had logged into Facebook. In fact, I couldn’t remember the last time I had. Facebook seemed equally nonplussed. I was so derelict that Facebook informed me the lock to my account had rusted shut or some such nonsense. Since I guess I’m in the .01% of Facebook users who don’t post status updates at the bus stop, at work, and during their own wedding, I was assumed to be a malicious hacker who was guilty until proven innocent. I was asked to walk through a five-step authentication process that put online banking applications to shame (it was more rigorous than my CapitalOne online credit card approval):

For those of us who started using Facebook back when some less scrupulous college students referred to it as “Stalkbook,” falsifying information made a lot of sense. I had made it a habit to change personal information several times a year. This proved to be a problem when it came to proving I was the account holder. The irony of Facebook protecting me from the false data I had made to protect me from Facebook was not lost on me.

The only real chance I had of getting back into Facebook and proving myself worthy to buy Farmville credits was a verification method that required me to identify pictures of my friends. It was supposed to work something like a police lineup. I had to pick the right name out of a short list, but if I didn’t identify enough faces correctly Facebook would banish me to MySpace. It was like a game show, except instead of cash you win the ability to ignore spam on your personal feed.

I quickly realized that there were two things that made this a bad way to verify my identity.

First, I’m not really friends with most of my Facebook friends. Sure, several hundred people on Facebook have clicked a button that says we’re friends, but I couldn’t pick many of them out of a crowd. And I’d be screwed if the people I did know did something drastic, like cut their hair since 2005.

Second, Facebook photos seem to have all been taken with pre-smartphones in bad lighting. Was that my best friend from high school grinding on that drunk girl or is my best friend the out-of-focus shoulder in the foreground?

Ah yes, I remember him well.

I'd know that shape anywhere!

Let's play the which-hair-do-you-recognize game.

Knowing that if I ever wanted to poke another stranger I would have to complete this challenge, I set forth.

I got lucky with the first set of pictures. Immediately a half-decent photo of the lower half of a college friend’s face stuck out. I managed to  identify the friendly mouth.

The second set involved identifying the back of a high school friend’s head. This shot appeared to have been taken in a bar. There was other hair in the photo which might have confused me, but I used a motion-blurred prom photo along with a contorted web cam picture to verify the hair’s owner. Yes!

The third photo featured an acquaintance I think I met in Cinema 101 seven years ago. Was that the guy that said that thing and wore that shirt all the time? I couldn’t be sure. Perhaps I never will know since I got that one wrong.

Finally, the algorithm gave me a breather with a perfectly acceptable face shot of a close college friend. The picture showed more than 60% of her face. Bingo!

I was told by a stern-looking confirmation page that I had scored “acceptably” and was fit to have digital friends again.

After all this tribulation I got to my profile to find 200 pokes, 25 zombie bites, 23 carbon copy invitations to events happening 2000 miles from my home, a smattering of cookie-cutter happy birthday messages from people I didn’t know made on the wrong date, and a renewed understanding of why I hate Facebook.

IMDB Score Bias: It’s Temporal

I’m a nerd, economist, and a movie snob. Sometimes it makes me hard to deal with.

My brother has a natural fear of picking movies with me. During our holiday visits home we invariably try to watch a movie and it ends in eyes being rolled in my direction. My family has taken to calling any movie I pick as a “depressing indie drama.”

I don’t think of this as being difficult, I think of it as getting the most out of my time. Having seen thousands of quality movies, I have trouble committing two hours to a movie of dubious quality. In an effort to avoid wasting time on bad and mediocre flicks, I am on quest to better predict how much I will enjoy a given movie. I’ve rated more than 700 movies on Netflix, I visit IMDB about 25 times week, I’ve tried Flixster, Rotten Tomatoes, and the blogs of well-known critics. The goal is to accurately correlate my movie-watching happiness with the ratings provided by these sources. So far the results are disappointing. No one source accurately predicts my preferences. Even inter-comparing and creating composite indexes frequently leads to contradictory predictions. To date, the best predictor I’ve found is a film’s IMDB rating, but this number is far from perfect.

IMDB ratings are worst when movies are newly released. For a film like Citizen Kane, the IMDB score is accurate, and no wonder: enough people have seen it to decide how good it is. In fact, Orson Welles’ masterpiece has 145,319 ratings on IMDB, a score of 8.6/10, and is listed by the American Film Institute as the best movie ever made.[1] Citizen Kane is pretty similar to other critically acclaimed films on IMDB. Among the top ten films, the average number of IMDB votes is 152,073 and the median score is 8.45. With so many ratings these my guess is that these movies are more accurately rated than a movie with 1% as many reviews that was released last week.

Take Inception for example. When it was released it had a rating of 9.3 on IMDB and thousands of reviews. But how could this be? Was Inception actually a better movie than Citizen Kane, Casablanca, The Godfather, Gone with the Wind, Lawrence of Arabia, The Wizard of Oz, The Graduate, On the Waterfront, Schindler’s List, and Singin’ in the Rain?  Having seen all of these films, I had a hard time believing it.

So, I hypothesized that IMDB ratings were biased upwards for young movies. When new movies come out, the first people to see them are early adopters and critics. As an example, someone disinterested in a new film may see it eventually [2], but they are unlikely to see it the first day it comes to their local theater. My contention was that seeking out such pre-releases, in combination with marketing and release hype, would select and reinforce overly-positive movie reviews.

To test this theory, I spent three months sampling a randomly-selected group of 21 new releases. I started sampling on November 9th by finding IMDB’s list of upcoming movies and recording the first data point for all of them[3]. I then checked the ratings once weekly to see if my prediction about prerelease hype held up to a little empirical rigor. My sample was surprisingly diverse. Among the movies I sampled there were big budget Hollywood films like Tron: Legacy as well as indie films like Rare Exports[4]. Because some of the films were slated to release later in the month of December and some had pre-screeners who rated the movies before a popular release, I didn’t have an equal number of data points for each film. Almost every film did reach score equilibrium; the score remained stable for at least three sampling periods (three weeks). Here is a time series for the films. I’ve omitted the titles since it would clutter the graph too much:

Looking at the graph is a bit confusing, and there isn’t a clear trend. So I turned to the numbers. With a little statistical crunching I found that the average movement in rating was -.2125, significant at 95% confidence. In other words, new movies do have inflated IMDB ratings, on average those ratings are .2 points above where they will eventually settle.

The greatest volatility in rating was in the first two sample periods, which is to be expected. The Tempest and Casino Jack were the biggest losers (shedding 1.6 points in the 3 month period). There were several films that appear to have been correctly assessed from the get-go and had no rating change after 12 weeks: I Love You Philip Morris, The Tourist, The Fighter, Little Fockers, and a French film by the name of The Illusionist. The rest suffered small declines in score that are consistent with my theory. There obviously is no way for me to prove that my theory is actually at work, but the evidence doesn’t disprove it, which is great news!

The takeaway here is that if you are asked to watch a new release, assume that the IMDB rating is overly-optimistic by about a fifth of a point, then go anyway and have a good time. If you can avoid it, don’t be a movie snob like me!

[1] Even a film snob like me must admit that it is ridiculous to make such a claim but it sure sounds definitive.

[2] I suspect the biggest reason that disinterested people see films is social pressure.

[3] The equivalent page for this week would be here.

[4] I tracked all of the following films: Black Swan, I Love Your Phillip Morris, Rare Exports, The Warrior’s Way, The Tourist, The Tempest, The Chronicles of Narnia: Voyage of the Dawn Treader, The Company Men, The Fighter, Tron: Legacy, Yogi Bear, How do you Know, All Good Things, Rabbit Hole, Casino Jack, Little Fockers, True Grit, Somewhere, The Illusionist, Gulliver’s Travels, and Country Strong.