The Invisible Gorilla: And Other Ways Our Intuitions Deceive Us (43 page)

1.
Basic facts about the Human Genome Project, which involved researchers in several countries, can be found at the U.S. Department of Energy (DOE) website devoted to the project (
www.ornl.gov/sci/techresources/Human_Genome/home.shtml
). The DOE was involved in biomedical research because of the recognition that radiation from nuclear weapons and other sources could affect human genes. The majority of the project’s funding, however, came from the budget of the National Institutes of Health (NIH).

2.
The story of the gene count betting pool is based on a series of articles in
Science
magazine: E. Pennisi, “And the Gene Number Is …?”
Science
288 (2000): 1146–1147; E. Pennisi, “A Low Number Wins the GeneSweep Pool,”
Science
300 (2003): 1484; and E. Pennisi, “Working the (Gene Count) Numbers: Finally, a Firm Answer?”
Science
316 (2007): 1113. Other sources include an Associated Press article from October 20, 2004 (reprinted at
www.thescienceforum.com/Scientists-slash-estimated-number-of-human-genes-5t.php
), and an article by Cold Spring Harbor Laboratory’s David Stewart, who maintained the official handwritten ledger in which all bets were recorded,
www.cshl.edu//files/02/92/98/f029298/public/HT/ss03-sweep.pdf
(accessed August 27, 2009). The pool’s defunct website has been archived at
web.archive.org/web/20030424100755/www.ensembl.org/Genesweep/
(accessed August 27, 2009).

3.
The prediction was made in a talk given by Herbert Simon on behalf of himself and Allen Newell at the National Meeting of the Operations Research Society of America on November 14, 1957: H. A. Simon and A. Newell, “Heuristic Problem Solving: The Next Advance in Operations Research,”
Operations Research
6 (1958): 1–10. They also predicted that within ten years, computers would be proving important mathematical theorems and composing high-quality original music, and that most theories in psychology would be expressed in the form of computer programs designed to simulate the human mind. None of these things fully came to pass, though some progress was made on each of them.

4.
Nowadays even laptop computers are the equal of the world’s top players. The history of the bets is described by D. Levy and M. Newborn,
How Computers Play Chess
(New York: Computer Science Press, 1991). The match between Kasparov and Deep Blue is recounted in the following works: M. Newborn,
Deep Blue: An Artificial Intelligence Milestone
(New York: Springer, 2003); F-H. Hsu,
Behind Deep Blue: Building the Computer
That Defeated the World Chess Champion
(Princeton, NJ: Princeton University Press, 2002); and D. Goodman and R. Keene,
Man Versus Machine: Kasparov Versus Deep Blue
(Cambridge, MA: H3 Publications, 1997).

5.
P. Ehrlich,
The Population Bomb
(New York: Ballantine, 1968).

6.
Quoted by J. Tierney, “Science Adviser’s Unsustainable Bet (and Mine),” TierneyLab blog, December 23, 2008 (
tierneylab.blogs.nytimes.com/2008/12/23/science-advisors-unsustainable-bet-and-mine/
). Other information on the Ehrlich-Simon wager is drawn from the following sources: J. Tierney, “Betting on the Planet,”
The New York Times
, December 2, 1990; J. Tierney, “Flawed Science Advisor for Obama?” TierneyLab blog, December 19, 2008 (
tierneylab.blogs.nytimes.com/2008/12/19/flawed-science-advice-for-obama/
); and E. Regis, “The Doomslayer,”
Wired
, February 1997.

7.
J. L. Simon, “Resources, Population, Environment: An Oversupply of False Bad News,”
Science
208 (1980): 1431–1437.

8.
We could have gone on and on with examples of scientific overconfidence; for example, even physicists have been found to be overconfident when historical data was examined to see how accurately they had measured well-known physical constants, like the speed of light: M. Henrion and B. Fischhoff, “Assessing Uncertainty in Physical Constants,”
American Journal of Physics
54 (1986): 791–797.

9.
R. Lawson, “The Science of Cycology: Failures to Understand How Everyday Objects Work,”
Memory and Cognition
34 (2006): 1667–1775.

10.
L. G. Rozenblit, “Systematic Bias in Knowledge Assessment: An Illusion of Explanatory Depth,” PhD dissertation, Yale University, 2003.

11.
From an interview Dan conducted with Leon Rozenblit on August 14, 2008.

12.
B. Worthen, “Keeping It Simple Pays Off for Winning Programmer,”
The Wall Street Journal
, May 20, 2008, p. B6 (
online.wsj.com/article/SB121124841362205967.html
).

13.
Information on the Big Dig drawn primarily from the project’s official website (masspike.com/bigdig/index.html).

14.
Information on the Brooklyn Bridge and Sydney Opera House is from B. Flyvbjerg, “Design by Deception: The Politics of Megaproject Approval,”
Harvard Design Magazine
, Spring/Summer 2005, pp. 50–59. Information on the Sagrada Familia is from R. Zerbst,
Gaudi: The Complete Buildings
(Hong Kong: Taschen, 2005) and from Wikipedia (
en.wikipedia.org/wiki/Sagrada_Família
). The entire history of public architecture can be seen as one of cost overruns and delays. Bent Flyvbjerg, an expert on urban planning at the University of Aalborg in Denmark, has coauthored a study of three hundred such projects in twenty countries. He argues persuasively that all parties involved have learned to deliberately lowball the estimates, because if legislators and their constituents appreciated the true costs and uncertainties involved in these projects, they would never support them. In other words, those who do understand the complex systems—or at least understand the limits of their own knowledge—are exploiting the very lack of that understanding among the general public. See B. Flyvbjerg, N. Bruzelius, and W. Rothengatter,
Megaprojects and Risk: An Anatomy of Ambition
(Cambridge: Cambridge University Press, 2003).

15.
The first quote is from Robert Burns, the second is from Helmuth Graf von Moltke, and the third is from Douglas Hofstadter.

16.
This quip is usually attributed to Yogi Berra, whose sayings often had this sort of twisted logic, but a version of it was apparently said earlier by the physicist Neils Bohr.

17.
This study is described on p. 142 of P. B. Carroll and C. Mui,
Billion Dollar Lessons: What You Can Learn from the Most Inexcusable Business Failures of the Last 25 Years
(New York: Portfolio, 2008).

18.
The classic volume on the positive nature of most self-deception is S. E. Taylor,
Positive Illusions: Creative Self-Deception and the Healthy Mind
(New York: Basic Books, 1989). The idea that depressed people are less subject to everyday illusions is speculative; there is a controversial line of research suggesting that depressed people have a more realistic understanding of how much they can control events (e.g., L. B. Alloy and L. Y. Abramson, “Judgment of Contingency in Depressed and Nondepressed Students: Sadder but Wiser?”
Journal of Experimental Psychology: General
108 [1979]: 441–485).

19.
The idea of the “outside view” is described in detail in D. Lovallo and D. Kahneman, “Delusions of Success: How Optimism Undermines Executive Decisions,”
Harvard Business Review
(July 2003): 56–63. The tendency to underestimate the time to complete a task is often called the “planning fallacy,” and the formal name for the technique of comparing a project to similar ones to estimate completion time is called “reference class forecasting.” This method has been endorsed by the American Planning Association. See B. Flyvbjerg, “From Nobel Prize to Project Management: Getting Risks Right,”
Project Management Journal
(August 2006): 5–15. Another way to use the disinterested knowledge of other people to help in forecasting project durations (and other future events) is to set up a prediction market, a sort of artificial financial futures market in which individuals invest or gamble money on making the most accurate prediction. The aggregation of multiple, independent predictions, each from someone motivated by financial gain and not personally involved in carrying out the plan, can yield much more accurate forecasts than those made by even expert individuals. For discussion, see C. R. Sunstein,
Infotopia: How Many Minds Produce Knowledge
(Oxford: Oxford University Press, 2006); and R. W. Hahn and P. C. Tetlock,
Information Markets: A New Way of Making Decisions
(Washington, DC: AEI Press, 2006).

20.
Techniques like these were studied experimentally in R. Buehler, D. Griffin, and M. Ross, “Exploring the ‘Planning Fallacy’: Why People Underestimate Their Task Completion Times,”
Journal of Personality and Social Psychology
67 (1994): 366–381.

21.
Information on Brian Hunter and Amaranth Advisors comes from: A. Davis, “Blue Flameout: How Giant Bets on Natural Gas Sank Brash Hedge-Fund Trader,”
The Wall Street Journal
, September 19, 2006, p. A1 (online.wsj.com/article/SB115861715980366723.html); and H. Till, “The Amaranth Collapse: What Happened and What Have We Learned Thus Far?” EDHEC Business School, Lille, France, 2007. The comparison between Amaranth and other debacles is based on “List of Trading Losses” in Wikipedia, en.wikipedia.org/wiki/List_of_trading_losses (accessed March 27, 2009).

22.
Information on various investment strategies comes from the following sources: “Dow Theory” in Wikipedia,
en.wikipedia.org/wiki/Dow_theory
(accessed March 25, 2009); discussion of the Nifty Fifty in Chapter 8, “The Amazing Two-Tier Market,” in D. N. Dreman,
Psychology and the Stock Market: Investment Strategy Beyond Random Walk
(New York: Amacom, 1977). “Dogs of the Dow” is a nickname for a strategy proposed by Michael O’Higgins in his book
Beating the Dow: A High-Return, Low-Risk Method for
Investing in the Dow Jones Industrial Stocks with as Little as $5000
(New York: HarperCollins, 1991). The “Foolish Four” strategy, a derivative of one of O’Higgins’s ideas, is described by Robert Sheard in
The Unemotional Investor: Simple Systems for Beating the Market
(New York: Simon & Schuster, 1998). Both of the latter two books were bestsellers.

23.
It is arguably wrong to view a house as an investment. A typical asset bought for investment purposes is not usable while you own it; there’s nothing you can physically
do
with your Google stock or your municipal bonds or your money-market funds. (You can’t even frame your pretty stock certificates anymore, unless you make a special request for them from your broker.) The right way to think of a house is as a hybrid of a consumable product that must be repaired and upgraded over time, like a car or a computer, and an underlying investment (which is based partly on the value of the land where it stands).

People make mistakes when thinking about housing prices for a variety of reasons, one of which is failing to make this distinction. For example, many homeowners mistakenly believe that improving their homes will increase the home’s value by a greater amount than the cost of the improvement; in fact, every one of twenty-nine common home improvements yields an average increase in resale value less than 100 percent of its cost (see “Remodeling 2007 Cost Versus Value Report” [
www.remodeling.hw.net/costvsvalue/index.html
]; and D. Crook,
The Wall Street Journal Complete Homeowner’s Guidebook
[New York: Three Rivers Press, 2008]). Remodeling a home office costs $27,193 on average, but increases the home’s value by only $15,498, or 57 percent of the original expenditure, not counting any interest paid if the remodeling was financed. Even remodeling a kitchen, one of the classic value centers of a house, returns only 74 percent of the money spent. Look at it this way: If your house would sell for $500,000 today, but you decide to “invest” $40,000 in a new kitchen before you put the house on the market, you should expect to get about $530,000 for it. Putting the same money in the bank would be a much better investment: You wouldn’t earn much in interest, but at least you wouldn’t lose the $10,000!

When told these facts, people often become incredulous and even angry—precisely because they contradict a foundational piece of “knowledge” homeowners have about their “investments.” We will return to this subject later in this chapter when we discuss the necessary conditions for financial bubbles and panics. There are, of course, other reasons to remodel a house besides any expected “investment” gain: A recent study showed that additional full or half bathrooms in a house were more strongly associated with owner satisfaction than any other feature measured, including additional bedrooms, air conditioning, and a garage. See R. N. James III, “Investing in Housing Characteristics That Count: A Cross-Sectional and Longitudinal Analysis of Bathrooms, Bathroom Additions, and Residential Satisfaction,”
Housing and Society
35 (2008): 67–82.

24.
M. Piazzesi and M. Schneider, “Momentum Traders in the Housing Market: Survey Evidence and a Search Model,” Stanford University manuscript, 2009,
www.stanford.edu/~piazzesi/momentum%20in%20housing%20search.pdf
(accessed August 17, 2009).

25.
Alberto Ramirez’s mortgage story is from C. Lloyd, “Minorities Are the Emerging Face of the Subprime Crisis,” SF Gate, April 13, 2007 (
www.sfgate.com/cgi-bin/article.cgi?f=/g/a/2007/04/13/carollloyd.DTL
). Ninja loans, and other bad home-finance ideas, are mentioned in S. Pearlstein, “‘No Money Down’ Falls Flat,”
The Washington Post
, March 14, 2007, p. D1 (
www.washingtonpost.com/wp-dyn/content/article/2007/03/13/AR2007031301733_pf.html
). Ed Glaeser’s quote comes from E. Glaeser, “In
Housing, Even Hindsight Isn’t 20–20,”
The New York Times
Economix blog, July 7, 2009 (economix.blogs.nytimes.com/2009/07/07/in-housing-even-hindsight-isnt-20–20/?hp).