Posts Tagged ‘leadership’
Test what you know, but avoid congruence bias
A few posts ago I discussed confirmation bias, where individuals interpret everything they experience as reinforcing their existing beliefs. It’s not surprising that humans fall prey to this trap. We have to make sense of our surroundings, so we develop mental models to do so. They’re our models, based on our mental, so it’s no surprise we think highly of them.
No model of the world can capture all of its complexity. We can model industrial processes at a certain level, but we can’t get all the way down to the interactions of individual atoms. Fortunately, we don’t have to to generate accurate depictions of reality. As statistician George E. P. Box noted, “All models are wrong, but some are useful.”
Many humans realize they will move through life more effectively by testing and updating their mental models, but you need to test your model correctly. If you test your mental models and other hypotheses through direct testing, rather than testing possible alternative models, you are experiencing congruence bias. You’re testing your model, which is great, but you’re not entertaining other ways of approaching the problem, which is not so great. In The Structure of Scientific Revolutions, Thomas Kuhn argued that scientists work within a paradigm, which is the dominant framework for creating, testing, and determining hypotheses at a given time. When experimental results aren’t as expected, scientists can either work to shore up the existing paradigm or create a new one.
My wife, Virginia Belt, is a director and formerly taught acting at Willamette University in Salem, Oregon. She emphasizes the need for actors to try different tactics to get what they want. Think of the young child who tries everything he can think of to have you buy him a treat at the grocery store or the cat that really, really (really) wants a piece of sausage from your pizza. You can take the same approach to life. If you find your model isn’t working well any more, such as after a promotion at work, joining a new improv group or entering into a new relationship, try different tactics to see what does work. Ginny always exhorts her students to make positive choices, to focus on what they want rather than what they don’t want. If you call Domino’s and say you don’t want anchovies, you’ll either get no pizza because you haven’t given them enough information or get a pizza that costs $50 because it has every other available topping on it.
As anyone who has ever tried anything new well knows, individuals who break away from the pack meet a lot of resistance. Having the strength to break out of congruence bias at a personal level is tough — having the strength to do it in the face of a tenure board is even tougher. Let’s leave the paradigmatic fights for the professionals and focus on our own world views for a while. We’ll be better off in the end.
When You’re “Due” — The Gambler’s Fallacy
I travel to Las Vegas once or twice a year, both to play poker (where I convince myself I have an advantage) and to dabble in other games (where I definitely don’t). Since 1993, when I started playing while on the East Coast, I’ve seen thousands of players succumb to the insidious gambler’s fallacy.
Let’s say you’re playing roulette and notice, as posted on the so very helpful display by the wheel, that five red numbers have come up in a row. Is black due? What about green (0/00)? The answer is neither. Roulette wheels are well-balanced and the little obstacles spread around the wheel, called canoes in casino parlance, make outcomes random enough to be considered independent trials. If red numbers come up five times in a row, the next number will be red 18/38 of the time, black 18/38 of the time, and green 2/38 of the time. Ironically, it’s our human urge to discover patterns that makes the gambler’s fallacy work. The wheel has no memory, but we do.
The bottom line is that when you play roulette, the proportion of red, black, and green numbers will tend toward the target ratios over millions of spins and the weighted payoffs will ensure the house earns its profit over the long run. But what about games like poker? Poker is a skill game with a healthy dose of luck thrown in, so trials aren’t truly independent. Inferior players beat better players over the short term, but only because of luck. But what happens when equal players face off?
It’s hard to find players of the same skill level at a poker table, but I tested the theory by replicating an experiment described by poker author Lou Krieger. Like Lou, I set up ten identical players in Wilson Software’s Turbo Texas Hold’em simulation mode and let them play hundreds of millions of hands against each other. Six of the ten players were just above or below breaking even, but there were two big winners and two big losers. Remember that each player followed an identical strategy — the only factor controlling their fate was the luck of the draw.
As human beings trying to extract a living from an indifferent universe, we must realize that the odds are not always in our favor and that we will go through bad streaks we can’t seem to reverse. At these times it pays to strengthen your base by learning new skills or practicing old ones, reinforcing friendships, reaching out to others for help, and offering assistance where you can. Doing these things doesn’t constitute “good karma” or “putting things out into the universe”, both dubious concepts. What you are doing is improving the chances you’ll be ready to take advantage of opportunities that you and your contacts discover.
Perceived safety increases risk-taking
In many senses, life is a series of risk/reward calculations. Choosing which school to attend, buying a house, and choosing a spouse are all risky endeavors. According to the Peltzman effect, also known as risk compensation, people have a tendency to take greater risks when perceived safety increases.
I’m sure this conclusion comes as no surprise to you. Toddlers learning to walk soon start to run, or go down stairs, with the expected results. Teen drivers (particularly teen boys) get comfortable behind the wheel and dart off in a burst of testosterone, occasionally ending up in dire circumstances. This phenomenon was very common the Formula 2 racing series. Formula 2 is a development series for the global F1 competition, which is viewed as the pinnacle of motor racing. The problem is that the Formula 2 series was plagued with multiple accidents resulting from brash moves made by the young drivers. The reason? Analysts, including current F1 drivers, argued that Formula 2 racers were overly aggressive because their cars are so safe. Romain Grosjean, a Formula 2 driver who now competes for the Renault F1 team, was fined several times and sat out for an F1 race after being at fault in repeated incidents following his promotion.
Investors make similar risk/reward calculations. Wall Street investment bankers often take significant risks because their compensation schemes reward short-term success far more than they punish failure. Why would they take such risks? Because it’s part of their overall strategy. In the Wharton School’s corporate finance MOOC I’m taking on Coursera, Professor Franklin Allen argues that one’s sense of risk is inverted when you think of investing in a portfolio of stocks rather than in a single stock. For example, imagine that you buy stock in an oil company that finds oil in 1 out of 20 wells, and each producing well returns $100. You have a hit rate of 5% which, multiplied by the return of a good well, yields an expected value of $5. Now imagine that you have a separate investment in a research company that has a 1 in 50 chance of returning $250, otherwise gaining you nothing. This investment has a similar expected value to the previous example, because 2% (1 in 50) of $250 is $5.
Which of the two investments is less risky? If you look at the expected values, they’re equally risky. However, Professor Allen argues that, when considered as part of a portfolio, the latter investment is less risky because of its higher potential return. The crux of the argument is that a diversified portfolio with numerous independent risks will tend to have a higher return than a collection of pedestrian investments with relatively low risk. The end result is safety in numbers. Just as a fair coin flipped 1,000 times will tend to show heads in about 50% of the trials, investments with independent risks will tend to earn out at their expected rate, assuming you adjudged the risks correctly in the first place. Statistics on investment return since the year 1900 bear out his argument.
Improvisers can and should take risks to make great scenes. We can do it without fear because we know our fellow players will be there to make what we say and do the right thing. Similarly, businesses can take risks as part of a diversified portfolio of ideas. Just as you wouldn’t invest in a single stock such as, I don’t know…Enron, you shouldn’t discourage experimentation and risk. That said, you must understand that risks taken within a scene or business are dependent, not independent. There’s only so much we can do to fix things if you go too far overboard. If you can’t spread out your risk, you must moderate it to be successful.
Clustering and Streaks — Real or Imagined?
The folk wisdom that “bad things come in threes” is still popular in the U.S. Whenever two celebrities die on the same day, for example, even the most hardened critical thinker feels the urge to look for the third.
Is clustering real? Do events happen in streaks, or are they just a product of our pattern-seeking brains? George Carlin made fun of the “bad things happen in threes” adage by stating that bad things actually happen in 27’s, noting that “it just takes longer to see the pattern.” You can always find instances of “bad things” in the world to fill out your sets of three, but what does the research say? There have been a lot of studies on the subject, including Koehler and Conley’s “The “Hot Hand” Myth In Professional Basketball”, published in 2003 in the Journal of Sport and Exercise Psychology. The authors examined the National Basketball Association’s long distance shooting contest and looked for statistical aberrations in the sequences of made and missed shots. As in all but a few other studies, they found no significant deviation from chance. When they took each player’s base shooting accuracy into account, the effect disappeared.
Sports are physical contests and even little variations in physical conditions can affect performance, but what about chess? Chess is a mental game played with perfect information. That is, you know everything there is to know about a position and there’s no hidden information, such as a player’s hole cards in poker. As of this writing, I have played 19,738 games of blitz chess (each player has 3 or 5 minutes to make all moves in a game) at the Internet Chess Club since June 27, 2001. As I watch my online chess rating fluctuate from embarrassing to “not bad for me”, I wonder how much the streaks of wins, losses, and draws reflect my abilities and how much is the “luck” of an opponent making some horrible mistake.
The three-year graph of my rating shows huge swings, but the average is right about where I perceive myself as a player. Perhaps my streaks are due to luck. After all, I don’t seriously study the game and play to take a break from other work. The big changes make a strong visual impression, but there are a lot of small shifts in there, too.
Improvisers can make a fun game out of looking for apparent patterns and justifying reasons for believing streaks exist. The lesson for analysts? Carefully examine whether a sequence of events is due to some underlying cause or is just a sequence of events that might be due to chance. That said, given the strength of our innate need to discover patterns, is there any way to dispel what appears to be the myth of the hot hand? In a 2006 review of the literature, Michael Bar-Elia, Simcha Avugosa, and Markus Raab summarized the situation in this way:
As Amos Tversky, who initiated the hot hand research, used to say (cited by Gilovich in an online chat, September, 2002), ‘‘I’ve been in a thousand arguments over this topic, won them all, but convinced no one’’.
Cognitive Biases are Fun!
George Carlin once pointed out that comedy depends on exaggeration — to make something funny, you must distort one aspect of the situation or description to introduce humor.
If you’re thinking, “I don’t have to exaggerate anything…I make enough mistakes to feed a hundred comics for a year,” you’re probably right. We’re all susceptible to cognitive biases that skew our judgment. If you’ve read any of Dan Ariely’s work (Predictably Irrational, The Upside of Irrationality, and The Honest Truth About Dishonesty) or read the pop psych literature, you know the human mind is a frighteningly powerful yet flawed instrument.
I have good news: you can identify and minimize the impact of cognitive biases. What’s more, performers can use them to create humorous situations on stage. I downloaded a list of cognitive biases and will do my best to explore how they affect the world where business and funny intersect.
I first thought of writing a series of posts after a ComedySportz gig for health care professional employed by the Oregon penal system. One of their handouts (I always grab the handouts) listed about 120 cognitive biases and logical traps affecting the reasoning inmates and others use to assess their circumstances. I’ll leave the connection between prison, work, and comedy to your fertile brains.
First up? Everyone’s favorite trap: confirmation bias.
Book Review: The Gamble, from Princeton University Press
Title: The Gamble
Authors: John Sides and Lynn Vavreck
Publisher: Princeton University Press
Copyright: 2013
ISBN13: 978-0-691-15688-0
Length: 322
Price: $29.95
Rating: 93%
I received access to a preview copy of this book via the NetGalley site.
The popular media covers U.S. presidential campaigns like announcers calling a horse race, highlighting every move, nuance, and setback as if it could determine the winner. Why? Because not doing so would give viewers tacit permission to watch something else, drive down the networks’ ratings, and cost them advertising dollars. One journalist from Mother Jones identified 68 unique events the press labeled “game changers.” Were they, or was it just meaningless hype?
Approach
In The Gamble: Choice and Chance in the 2012 Presidential Election, authors John Sides and Lynn Vavreck analyze the race’s twists and turns in measured tones, emphasizing the role “the fundamentals” (especially the economy) play in presidential elections. Sides is associate professor of political science at George Washington University and the coauthor of Campaigns and Elections. He cofounded and contributes to The Monkey Cage, a politics blog. Vavreck is associate professor of political science and communications at UCLA. As academics, they had to strike a balance between writing for a general audience versus writing for an academic audience.
Books without sufficient analytical rigor might not be considered during tenure evaluations, so the authors took a bit of a risk by writing mainly for laymen. I thought they struck a clever and useful balance by dividing the book into two sections: commentary text, where the authors summarize their findings in the main body of the book; and appendixes that present their data and analyses in more depth. The main text contains plenty of facts and figures, but the appendices extend the analysis by including summary statistics (such as standard deviation and standard error) and other measures of interest to professional academics.
Analysis
So, did the various campaign gaffes, missteps, blunders, and revelations make a difference? Sides and Vavreck conclude that, in the long run, they did not. The American electorate is more or less evenly divided between Democrats and Republicans with only a small percentage of persuadable voters for each election. Seemingly substantial missteps such as Mitt Romney’s statement about the (alleged) 47% of Americans who pay no income tax and Barack Obama’s (real) horrific performance in the first debate caused a momentary blip in the polls, but the candidates’ results settled back to the predicted norm within a few days.
The Republican primary season provides an even starker example of how Mitt Romney kept his forward momentum as challengers such as Rick Perry, Herman Cain, and Rick Santorum were “discovered” by the media but ran off the road due to policy mismatches with the electorate, poor debate performance, or personal issues the press uncovered. The fundamentals of Romney’s campaign didn’t guarantee him the nomination, but the odds were ever in his favor.
So too with Obama, who could rely on an (albeit slowly) improving economy to lift his campaign. Sides and Vavreck point out that even a general sense that things are getting better makes the incumbent very hard to overcome. Just as most Vegas odds makers give NFL teams a three-point edge for home field advantage, improving economic times provide a lift to sitting presidents.
Of course, campaigns and independent organizations do their best to overcome these limitations through voter outreach (aka the vaunted Obama “ground game”) and advertising. The authors’ analysis confirms previous work that ads shift opinions for a short time after viewing, but the effect fades quickly. The Romney campaign tried to leverage that fact by buying a lot of advertising in the days just before the election, but the Obama campaign had done a good job of maintaining their candidate’s presence and prevented the Romney campaign from succeeding.
The Gamble also addresses what the Obama win implies for American politics. Did his win, which was by a reasonably substantial margin, constitute a mandate and indicate a liberal trend in the polity? Recent votes in favor of legalizing gay marriage and marijuana seem to argue in favor of that interpretation, but Sides and Vavreck found that the electorate tends to equilibrate by moving in opposition to the winning candidate’s views. In other words, a liberal candidate’s win results in a more conservative electorate and vice-versa.
Conclusion
When it comes to U.S. presidential elections, the percentage of the electorate that will vote for their preferred party’s candidate regardless of attempted persuasion is so large as to render most campaigning moot. The campaign machines are so well-tuned, the authors argue, they cancel each other out over the long run. The fundamental elements, especially the economy, are far more relevant. I find that aspect of The Gamble comforting.
Before I close, I’d like to give a quick shout-out to the cover designer. I didn’t see the designer’s name in my preview copy of the book, but the cover image uses the point of the “A” in “Gamble” as the fulcrum of a dynamic balance between red and blue, which is a terrific touch. It makes a good book that much better.
Curtis Frye is the editor of Technology and Society Book Reviews. He is the author of more than 30 books, including Improspectives, his look at applying the principles of improv comedy to business and life. His list includes more than 20 books for Microsoft Press and O’Reilly Media; he has also created over a dozen online training courses for lynda.com. In addition to his writing, Curt is a keynote speaker and entertainer. You can find more information about him at www.curtisfrye.com.
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