Unfair (74 page)

Even when it was made explicit:
Moore et al., “Wolves in Sheep's Clothing,” 176.

According to the researchers:
Moore et al., “Wolves in Sheep's Clothing,” 175.

Is it any surprise, then:
James J. Gobert, Ellen Kreitzberg, and Charles H. Rose III,
Jury Selection: The Law, Art and Science of Selecting a Jury
(Eagen, MN: West, 2009): § 14:3; Twila Wingrove et al., “The Use of Survey Research in Trial Consulting,” in
Handbook of Trial Consulting
, eds. Richard L. Wiender and Brian H. Bornstein (New York: Springer, 2011): 100–01.

In some ways, research like this:
As another example, one of the fascinating ways that scientific jury analysis is employed is for identifying potentially helpful jurors who the other side might try to remove for an impermissible reason, like the fact that they are African American.
Paterson and Silverstein, “Jury Research—How to Use It.” However, it can also have a dark side: coming up with alternative reasons for preemptively challenging someone that you want to remove based on race or gender. Indeed, an article in the
United States Attorneys' Bulletin
more than a decade ago suggested that U.S. prosecutors already had the capacity to employ questionnaire data and statistical analysis to do exactly that. As the two government attorney authors explained, “for each juror the government was likely to strike, the computer identified and included in the report those areas of the questionnaire that could be used to defend against a potential
Batson
challenge made by the defense.” Paterson and Silverstein, “Jury Research—How to Use It.”

 

A little over one hundred years ago:
G. K. Chesterton, “G. K. Chesterton Empanels a Jury,”
Lampham's Quarterly
, accessed May 20, 2014,
http://​www.laphamsquarterly.org/​voices-in-time​/g-k-chesteron-empanels-a-jury.php?page=all
.

After taking his oath:
Chesterton, “G. K. Chesteron Empanels a Jury.”

From that intimate vantage point:
Chesterton, “G. K. Chesteron Empanels a Jury.”

As he explained, the problem:
Chesterton, “G. K. Chesteron Empanels a Jury.”

For Chesterton, the solution was:
Chesterton, “G. K. Chesteron Empanels a Jury.”

The good news is that:
Calvin K. Lai et al., “Reducing Implicit Racial Preferences: I. A Comparative Investigation of 17 Interventions,”
Journal of Experimental Psychology: General
143, no. 4 (2014): 2; Calvin K. Lai, Kelly M. Hoffman, and Brian A. Nosek, “Reducing Implicit Prejudice,”
Social and Personality Psychology Compass
7 (2013): 315–30. doi: 10.1111/spc3.12023; Rajees Sritharan and Bertram Gawronski, “Changing Implicit and Explicit
Prejudice: Insights from the Associative-Propositional Evaluation Model,”
Social Psychology
41 (2010): 113–23, doi: 10.1027/1864-9335/a000017; Leon Neyfakh, “The Bias Fighters,”
Boston Globe
, September 21, 2014,
http://www.bostonglobe.com/​ideas/​2014/09/20/​the-bias-fighters/​lTZh1WyzG2sG5CmXoh8dRP/​story.html
.

There's now evidence, for example:
People show racial bias both in how quickly they make decisions to shoot or hold their fire and in how accurate those decisions turn out to be (that is, whether they fire at those pointing guns and don't fire at those holding wallets or cell phones). So, when presented with an unarmed black man, experimental participants are more likely to shoot him than if he is white, and they are also more hesitant in responding to armed and dangerous white men. For an overview of the research, see Adam Benforado, “Quick on the Draw: Implicit Bias and the Second Amendment,”
Oregon Law Review
89: 42–44. For a sample of some of the research studies investigating the role of race in shooter decision-making, see Joshua Correll et al., “Across the Thin Blue Line: Police Officers and Racial Bias in the Decision to Shoot,”
Journal of Personality and Social Psychology
92, no. 6 (2007): 1006; Joshua Correll et al., “Event-Related Potentials and the Decision to Shoot: The Role of Threat Perception and Cognitive Control,”
Journal of Experimental Social Psychology
42 (2006): 120; E. Ashby Plant and B. Michelle Peruche, “The Consequences of Race for Police Officers' Responses to Criminal Suspects,”
Psychological Science
16 (2005): 180; Anthony G. Greenwald et al., “Targets of Discrimination: Effects of Race on Responses to Weapons Holders,”
Journal of Experimental Social Psychology
39 (2003): 399; Joshua Correll et al., “The Police Officer's Dilemma: Using Ethnicity to Disambiguate Potentially Threatening Individuals,”
Journal of Personality and Social Psychology
83 (2002): 1314. For discussion of the positive effects of
simulator training, see Benforado, “Quick on the Draw,” 46–48; Correll et al., “Across the Thin Blue Line,” 1007, 1020–21.

The training doesn't remove:
Benforado, “Quick on the Draw,” 48; Correll et al., “Across the Thin Blue Line,” 1020.

To do that, scientists have been:
Calvin K. Lai et al., “Reducing Implicit Racial Preferences: I. A Comparative Investigation of 17 Interventions,”
Journal of Experimental Psychology: General
143, no. 4 (2014): 1–21; Leon Neyfakh, “The Bias Fighters,”
Boston Globe
, September 21, 2014,
http://www.bostonglobe.com/​ideas/​2014/09/20/​the-bias-fighters/​lTZh1WyzG2sG5CmXoh8dRP/story.html
.

One successful approach is to:
Lai et al., “Reducing Implicit Racial Preferences,” 7, 15–16; Neyfakh, “The Bias Fighters.” Of course, stereotypes can also be reinforced: in one experiment, people exposed to newspaper stories about black criminals subsequently showed greater racial bias in their shooting behavior. Joshua Correll et al., “The Influence of Stereotypes on Decisions to Shoot,”
European Journal of Social Psychology
37 (2007): 1102, 1107.

Another involves presenting a vivid story:
Lai et al., “Reducing Implicit Racial Preferences,” 7, 15–16; Neyfakh, “The Bias Fighters.”

Now that we know some:
Lai et al., “Reducing Implicit Racial Preferences,” 17–18; Neyfakh, “The Bias Fighters.”

Visit the Martin guitar factory:
“Martin Guitar Factory Tour Part 3 (of 6),” YouTube video, 13:57, posted by “Musician's Friend,” April 14, 2010,
http://www.youtube.​com/​watch?v=e4K1ec2n_M8
.

The lacquer on the exterior:
“Martin Guitar Factory Tour.”

With its pressure-sensitive wheel:
“Martin Guitar Factory Tour.”

As Dick Boak, a longtime employee, explains:
“Martin Guitar Factory Tour”; Dick Boak, “Welcome,” 2008, accessed May 20, 2014,
http://www.​dickboak.com/​dickboak_website​/Home.html
.

We need to be similarly flexible:
Whether the focus has been on building instruments, diagnosing illnesses, or racing cars, naysayers have inevitably emerged to suggest that human intuitions, decision-making, and execution are just fine (even optimal), and that the latest research that suggests that they are not is just a fad or a conspiracy or worse. When sabermetrics—the statistical study of baseball—was first introduced, there were numerous skeptics who believed that the best way to tell a good player was by watching him swing a bat and throw a ball, and, even today, there are many who remain wary of replacing or supplementing the intuitions of scouts with mathematical calculations of dynamics that you can't pick up from just watching games. Phil Birnbaum, “A Guide to Sabermetric Research,” Society for American Baseball Research, accessed May 20, 2014,
http://sabr​.org/​sabermetrics
. It is unpleasant to imagine that a computer might be better at selecting a team than a human being. And it is equally disquieting to think that a machine might do a better job polishing a fine Martin guitar—objects made with human hands, we imagine, are necessarily superior. Yet, in each case, the backlash has been largely overcome by the results.

Little would be lost:
If eliminating the right to remove jurors without cause proved politically untenable, we might consider replacing it with a more vigorous disqualification for cause. In any case, people should not lose their ability to participate in a vital part of our civic process because of the clothes they are wearing, the color of their fingernail polish, or their posture, let alone the color of their skin or their gender.

Although, as we've seen, videos are not:
Of course, as discussed previously, we must be cautious about how we employ video footage, conscious that it can create its own biases.

The closer we come to a world:
One long-term project may be to develop technology that can create rough images or models of people's faces from DNA left at a crime scene. That possibility has been raised by recent research focused on using interpersonal differences in certain genes believed to be implicated in facial development to produce predictive 3D models of what a person looks like. Sara Reardon, “Mugshots Built from DNA Data,”
Nature
, March 20, 2014,
http://www.nature.com/​news/​mugshots-built-from-dna-data​-1.14899
. The challenge is that there is no one gene that determines the shape of your nose and environmental influences can have a big impact on your ultimate visage. But researchers are not daunted and other projects are underway focused on using DNA to predict height and eye color, among other personal features.

A few cities, for example:
Only about one out of five incidents of gunfire is reported to the police. David S. Fallis, “ShotSpotter Detection System Documents 39,000 Shooting Incidents in the District,”
Washington Post
, November 2, 1013,
http://www.washingtonpost.com/​investigations/​shotspotter-detection-system​-documents-39000-shooting​-incidents-in-the-district/2013/11/02/055f8e9c-2ab1-11e3​-8ade-a1f23cda135e_story.html
; Yann Ranaivo, “Wilmington to Lease $415,000 Gunshot Sensor Network,”
News Journal
, February 19, 2014,
http://www.delawareonline.com/​story/news​/crime/2014/02​/19/wilmington-to-lease​-415000-gunshot​-sensor-network/5625179/
.

Likewise, knowing that detectives often:
Michael Wilson, “Crime Scene Investigation: 360 Degrees,”
New York Times
, November 18, 2011,
http://lens.blogs.nytimes.com/​2011/11/18/crime​-scene-investigation-​360-degrees/?_​r=0
.

Months after a man is found:
“A New Perspective on Crime Scenes: The Man on the Bed,”
New York Times
, November 18, 2011,
http://www.nytimes.com/​interactive/​2011/11/20/nyregion/nypd-crime​-scene-panoramas.html
; Wilson, “Crime Scene Investigation.”

In another New York City innovation:
Wendy Ruderman, “New Tool for Police Officers: Records at Their Fingertips,”
New York Times
, April 11, 2013,
http://www.nytimes.com/​2013/04/12​/nyregion/​new-tool-for-police​-officers-quick-access​-to-information.html
.

Coming across an individual on the street:
Ruderman, “New Tool for Police Officers.”

This
apartment, according to the details:
Ruderman, “New Tool for Police Officers.”

Such technology does raise civil liberties concerns:
We will have to engage in a similar balancing calculation when it comes to new tracking technology, like the StarChase system, which allows officers to shoot a small sticky GPS device from the front of their squad car at a fleeing vehicle. Mike Riggs, “The End of Car Chases,”
The Atlantic
, October 31, 2013,
http://www.theatlanticcities.com/​technollogy/2013/10​/end-car-chases/7425/
; StarChase, “How it Works—Overview,” 2013, accessed May 21, 2014,
http://www.starchase.​com/​howitworks.​html
. Already being used in Florida and Iowa, the hope is that the system will eliminate the need for dangerous police chases that lead to loss of life and significant property damage, as we saw in Victor Harris's case. Riggs, “The End of Car Chases.” Critics, though, worry that such warrantless tracking presents a significant threat to citizens' privacy rights. Riggs, “The End of Car Chases.”

All that said, the best way to:
Indeed, the best solution to a problem is not always the obvious one and we should be creative. One of my favorite demonstrations of this principle
relates to an unexpected way that researchers discovered to cut down on illiteracy in the developing world. Amy Yee, “In India, a Small Pill with Positive Side Effects,”
New York Times
, April 4, 2012,
http://opinionator.blogs.​nytimes.com/​2012/04/04/in-india​-a-small-pill​-with-positive-side-effects/?hp
. It wasn't hiring better teachers or instituting monetary rewards for learning milestones; it was deworming pills. Yee, “In India, a Small Pill.” It turns out that 600 million children suffer from worms and it is a leading reason why they miss school. Yee, “In India, a Small Pill.” For less than the cost of a coffee per student, however, the parasites can be wiped out, resulting in a big boost in attendance and a significantly increased chance that a child will learn to read and write. Yee, “In India, a Small Pill.”