Super Crunchers (28 page)

Isabel helps doctors consider major diagnosis:
Stephen M. Borowitz, et al., “Impact of a Web-based Diagnosis Reminder System on Errors of Diagnosis,” presented at AMIA 2006: Biomedical and Health Informatics (Nov. 11, 2006).

CHAPTER 5

Super Crunchers take on experts to predict Supreme Court decisions:
Andrew D. Martin et al., “Competing Approaches to Predicting Supreme Court Decision Making,” 2
Persp. on Pol
., 763 (2004); Theodore W. Ruger et al., “The Supreme Court Forecasting Project: Legal and Political Science Approaches to Predicting Supreme Court Decision-making,” 104
Colum. L. Rev
. 1150 (2004).

Holmes on legal positivism:
Oliver W. Holmes,
The Common Law 1
(1881) (“The prophesies of what the courts will do in fact, and nothing more pretentious, are what I mean by the law.”). See also Oliver Wendell Holmes, Jr., “The Path of the Law,” 10
Harv. L. Rev.
457, 461 (1897) (“The object of our study, then, is prediction, the prediction of the incidence of the public force through the instrumentality of the courts.”).

Langdell on law as a science:
Christopher C. Langdell, “Harvard Celebration Speeches,” 3
L.Q. Rev
. 123, 124 (1887).

Meehl's little book (and other works):
Paul E. Meehl,
Clinical Versus
Statistical Prediction: A Theoretical Analysis and a Review of the Evidence
(1954). See also William M. Grove, “Clinical Versus Statistical Prediction: The Contribution of Paul E. Meehl,” 61
J. Clinical Psychol
. 1233 (2005), http://www.psych. umn.edu/faculty/grove/112clinicalversusstatisticalprediction.pdf; Michael P. Wittman, “A Scale for Measuring Prognosis in Schizophrenic Patients,” 4
Elgin
Papers
20 (1941); Drew Western and Joel Weinberger, “In Praise of Clinical Judgment: Meehl's Forgotten Legacy,” 61
J. Clinical Psychol
. 1257, 1259 (2005), http://www.psychsystems.net/lab/2005_w_weinberger_meeh_JCP.pdf; Paul E. Meehl, in 8
A History of Psychology in Autobiography
337, 354 (G. Lindzey, ed., 1989).

Snijders vs. the buying experts:
Chris Snijders et al., “Electronic Decision Support for Procurement Management: Evidence on Whether Computers Can Make Better Procurement Decisions,” 9
J. Purchasing and Supply Mgmt
191(2003); Douglas Heingartner, “Maybe We Should Leave That Up to the Computer,”
N.Y. Times
, Jul. 18, 2006.

Man vs. machine meta analysis:
William M. Grove and Paul E. Meehl, “Comparative Efficiency of Informal (Subjective, Impressionistic) and Formal (Mechanical, Algorithmic) Prediction Procedures: The Clinical–Statistical Controversy,” 2
Psychol. Pub. Pol'y and L.
293, 298 (1996); William M. Grove, “Clinical Versus Statistical Prediction: The Contribution of Paul E. Meehl,” 61
J. Clinical Psychol
. 1233 (2005), http://www.psych.umn.edu/faculty/grove/112 clinicalversusstatisticalprediction.pdf.

Human bias:
D. Kahneman et al.,
Judgment Under Uncertainty: Heuristics and
Biases
(1982); R. M. Dawes and M. Mulford, “The False Consensus Effect and Overconfidence: Flaws in Judgment, or Flaws in How We Study Judgment?” 65
Organizational Behavior and Human Decision Processes
201 (1996).

A pool is more dangerous than a gun:
Steven Levitt, editorial, “Pools More Dangerous Than Guns,”
Chi. Sun-Times
, Jul. 28, 2001, p. 15.

People guess poorly:
J. Edward Russo and Paul J. H. Schoemaker,
Decision
Traps: Ten Barriers to Brilliant Decision-Making and How to Overcome Them
(1990). See also Scott Plous,
The Psychology of Judgment and Decision Making
(2003); John Ruscio, “The Perils of Post-Hockery: Interpretations of Alleged Phenomena After the Fact,”
Skeptical Inquirer
, Nov.–Dec. 1998.

Costs of the Iraq War:
Interview with Vice President Cheney, CNN broadcast, Jun. 20, 2005;. interview with Glenn Hubbard, CNBC broadcast, October 4, 2002; Reuters, “U.S. Officials Play Down Iraq Reconstruction Needs,”
Entous
, Apr. 11, 2003; Hearing on a Supplemental War Regulation Before the H. Comm. on Appropriations, 108th Cong. (Mar. 27, 2003) (statement of Deputy Defense Sec'y Paul Wolfowitz); Rep. Jan Schakowsky, “Past Comments About How Much Iraq Would Cost,” www.house.gov/schakowsky/iraqquotes_web.htm.

Human judges:
Richard Nisbett and Lee Ross,
Human Inference: Strategies and
Shortcomings of Social Judgment
(1980).

Super Crunching without emotions:
Douglas Heingartner, “Maybe We Should Leave That Up to the Computer,”
N.Y. Times
, Jul. 18, 2006.

Can Super Crunchers and experts coexist?:
S. Schwartz et al., “Clinical Expert Systems Versus Linear-Models: Do We Really Have to Choose,” 34
Behavioral Sci
. 305 (1989).

Humans serving machines:
Douglas Heingartner, “Maybe We Should Leave That Up to the Computer,”
N.Y. Times
, Jul. 18, 2006.

Parole predictions:
For an early study assessing the likely outcomes for parolees, see Earnest W. Burgess, “Factors Determining Success or Failure on Parole,” in
The
Workings of the Indeterminate Sentence Law and the Parole System in Illinois
(A. A. Bruce, ed., 1928), pp. 205–249. For biographical information and account of Burgess's place in sociology, use of new methods of measurement, see Howard W. Odum,
American
Sociology: The Story of Sociology in the United States Through 1950
(1951), pp. 168–171, http://www2.asanet.org/governance/burgess.htm.

Clouston and the SVPA:
Virginia General Statutes, § 37.1–70.4 (C); Frank Green, “Where Is This Man?: Should This Child Molester and Cop Killer Have Been Released?”
Richmond Times-Dispatch
, Apr. 16, 2006.

Supremes uphold SVPA:
Kansas v. Hendricks
, 521 U.S. 346 (1997).

Monahan on the first Super Crunching statutory trigger:
Bernard E. Harcourt,
Against Prediction: Profiling, Policing and Punishment in an Actuarial Age
(2007); John Monahan,
Forecasting Harm: The Law and Science of Risk Assessment among Prisoners, Predators, and Patients
, ExpressO Preprint Series (2004), http://law.bepress.com/expresso/eps/410.

Conditioning commitment on legal, but statistically predictive, behavior:
Eugene Volokh on his blog, The Volokh Conspiracy, has questioned whether the sex discrimination would withstand constitutional scrutiny. Eugene Volokh, “Sex Crime and Sex,” The Volokh Conspiracy, Jul. 14, 2005, http://volokh.com/ posts/1121383012.shtml. I do have concerns about whether the RRASOR system is in fact statistically valid. The original dataset upon which it was estimated was “artificially reduced” to 1,000 observations to intentionally reduce the statistical significance of the explanatory variables. R. Karl Hanson,
The Development of a
Brief Actuarial Scale for Sexual Offense Recidivism
(1997). Instead of constructing the crude point system, a more tailored approach would estimate recidivism probabilities based directly on the coefficients of the regression equation. The constructors of RRASOR seemed to be operating in a pre-computer environment where assessments had to be easily calculated by hand.

Introduction of the broken-leg case:
Paul E. Meehl,
Clinical Versus
Statistical Prediction: A Theoretical Analysis and a Review of the Evidence
(1954) (reissued University of Minnesota 1996).

Tom Wolfe:
Tom Wolfe,
The Right Stuff
(1979).

Mistaken discretionary releases:
Frank Green, “Where Is This Man?: Should This Child Molester and Cop Killer Have Been Released?”
Richmond
Times-Dispatch
, Apr. 16, 2006.

Assessing human overrides:
James M. Byrne and April Pattavina, “Assessing the Role of Clinical and Actuarial Risk Assessment in an Evidence-Based Community Corrections System: Issues to Consider,”
Fed. Probation
(Sep. 2006). See also Laurence L. Motiuk et al., “Federal Offender Population Movement: A Study of Minimum-security Placements,” Correctional Service of Canada, (Mar. 2001); Patricia M. Harris, “What Community Supervision Officers Need to Know About Actuarial Risk Assessment and Clinical Judgment,”
Fed.
Probation
(Sep. 2006).

The work that's left for humans:
Drew Western and Joel Weinberger, “In Praise of Clinical Judgment: Meehl's Forgotten Legacy,” 61
J. Clinical Psychol
. 1257, 1259 (2005); Paul E. Meehl, “What Can the Clinician Do Well?” in
Problems in Human Assessment
594 (D. N. Jackson and S. Messick, eds., 1967); PaulE. Meehl, “Causes and Effects of My Disturbing Little Book,” 50
J. Personality
Assessment
370 (1986).

Fink's circumcision hypothesis:
A. J. Fink, Letter, “A Possible Explanation for Heterosexual Male Infection with AIDS,” 315
N. Engl. J. Med
. 1167 (1986).

HIV-transmission hypotheses:
Cameron D. William et al., “Female to Male Transmission of Human Immunodeficiency Virus Type 1: Risk Factors for Seroconversion in Men,” 2
Lancet
403 (1989). See also J. Simonsen et al., “Human Immunodeficiency Virus Infection in Men with Sexually Transmitted Diseases,” 319
N. Engl. J. Med
. 274 (1988); M. Fischl et al., “Seroprevalence and Risks of HIV Infection in Spouses of Persons Infected with HIV,” Book 1, 4th Int'l Conf. on AIDS 274, Stockholm, Sweden (Jun. 12–16, 1988).

Continuing empiricism on the circumcision-AIDS connection:
D. T. Halperin et al., “Male Circumcision and HIV Infection: 10 Years and Counting,” 354
Lancet
1813 (1999); Donald G. McNeil Jr., “Circumcision's Anti-AIDS Effect Found Greater Than First Thought,”
N.Y. Times
, Feb. 23, 2007.

Weight loss investments:
I personally have signed a contract putting thousands of my dollars at risk if I don't take off twenty pounds this year and keep it off. Dean Karlan and I are trying to put together a randomized study of weight-loss bonds. Send me an email at [email protected] if you're interested in participating.

Hammond on clinical resistance:
Kenneth R. Hammond,
Human
Judgment and Social Policy
137–38 (1996).

CHAPTER 6

Google Books creates a virtual library:
Jeffrey Toobin, “Google's Moon Shot,”
New Yorker
, Feb. 5, 2007.

Discriminatory negotiation practices:
These results came from my initial study: Ian Ayres, “Fair Driving: Gender and Race Discrimination in Retail Car Negotiations,” 104
Harv. L. Rev.
817 (1991). An analysis of five more recent studies can be found in my book
Pervasive Prejudice?: Non-Traditional Evidence of
Race and Gender Discrimination
(2001).

Discriminatory auto-lending mark-ups:
Ian Ayres, “Market Power and Inequality: A Competitive Conduct Standard for Assessing When Disparate Impacts Are Justified,”
Cal. L. Rev.
(2007).

ChoicePoint sells data:
Gary Rivlin, “Keeping Your Enemies Close,”
N.Y. Times
, Nov. 12, 2006; ChoicePoint 2005 Annual Report, http://library. corporate-ir.net/library/95/952/95293/items/189639/2005annual.pdf.

Biggest company you never heard of:
“Persuaders,” PBS
Frontline
, http://www.pbs.org/wgbh/pages/frontline/shows/persuaders/etc/script.htm; see also Richard Behar, “Never Heard of Acxiom? Chances Are It's Heard of You,”
Fortune
, Feb. 23, 2004.

134: 850 terabytes of storage:
Rick Whiting, “Tower of Power,”
InformationWeek
, Feb. 11, 2002.

Data silos:
Kim Nash, “Merging Data Silos,”
Computerworld
, April 15, 2002; Gary Rivlin, “Keeping Your Enemies Close,”
N.Y. Times
, Nov. 12, 2006; Eric K. Neumann, “Freeing Data, Keeping Structure,”
Bio-IT World
, Jun. 14, 2006.

Data “mashups”:
Rachel Rosmarin, “Maps. Mash-ups. Money.” Forbes.com, Jun. 16, 2006, http://www.forbes.com/technology/2006/06/14/google-yahoomicrosoft_cx_rr_0615maps.htm.

Car theft database:
This data is available from the Federal Bureau of Investigation's National Crime Information Center (NCIC), http://www. fas.org/irp/agency/doj/fbi/is/ncic.htm.

Erroneous felon disenfranchisement:
The United States Civil Rights Commission,
The 2000 Presidential Elections
(www.usccr.gov/pubs/vote2000/ report/ch5.htm).

Kryder's Law:
“Kryder's Law” is the title of an article by Chip Walter in the Aug. 2005 issue of
Scientific American
.

Computer storage capacity costs decrease over time:
“Historical Notes about the Cost of Hard Drive Storage Space,” www.littletechshoppe.com/ ns1625/winchest.htm; Jim Handy, “Flash Memory vs. Hard Disk Drives—Which Will Win?” Jun. 6, 2005, http://www.storagesearch.com/semicoart1.htm.

Twelve terabytes for Yahoo:
Kevin J. Delaney, “Lab Test: Hoping to Overtake Its Rivals, Yahoo Stocks Up on Academics,”
Wall St. J
., Aug. 25, 2006, p. Al.

Background on neural networks:
P. L. Brockett et al., “A Neural Network Method for Obtaining an Early Warning of Insurer Insolvency,” 61
J.
Risk and Insurance
402 (1994); Jack V. Tu, “Advantages and Disadvantages of Using Artificial Neural Networks versus Logistic Regression for Predicting Medical Outcomes,” 50
J. Clin. Epidemiol.
1309 (1996); W. G. Baxt, “Analysis of the Clinical Variables Driving Decision in an Artificial Neural Network Trained to Identify the Presence of Myocardial Infarction,” 21
Ann. Emerg. Med.
1439(1992); K. A. Spackman, “Combining Logistic Regression and Neural Networks to Create Predictive Models,” in
Proceedings of the Sixteenth Annual Symposium on
Computer Applications in Medical Care
(1992), pp. 456–59; J. L. Griffith et al., “Statistical Regression Techniques for the Construction, Interpretation and Testing of Computer Neural Networks,” 12
Med. Decis. Making
343 (1992).