The Naked Future

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The Naked Future Page 30

by Patrick Tucker


  9. Jim Utsler, “The Crime Fighters,” IBM Systems Magazine, Feb. 2011, http://www.ibmsystemsmag.com/power/trends/ibmresearch/ibm_research_spss.

  10. Matthew Freedman and Emily Owens, “Your Friends and Neighbors: Localized Economic Development, Inequality, and Criminal Activity,” 2012, http://works.bepress.com/matthew_freedman/17.

  11. Utsler, “The Crime Fighters.”

  12. “NYPD and Microsoft Build Hi-tech Crime Fighting ‘Dashboard,’” Telegraph, Feb. 20, 2013, http://www.telegraph.co.uk/technology/news/9884479/NYPD-and-Microsoft-build-hi-tech-crime-fighting-dashboard.html.

  13. CCTV Based Remote Biometric and Behavioral Suspect Detection: Technologies and Global Markets—2011–2016, Homeland Security Market Research (Homeland Security Research, Q1 2011), http://www.homelandsecurityresearch.com/2013/08/china-homeland-security-public-safety-market-2013-edition; for more details https://www.wfs.org/futurist/2013-issues-futurist/march-april-2013-vol-47-no-2/chinas-closed-circuits.

  14. John L. Rep Mica, H.R.658—FAA Modernization and Reform Act of 2012, 2011, http://thomas.loc.gov/cgi-bin/bdquery/z?d112:h.r.658.

  15. “Subcommittee Hearing: Using Unmanned Aerial Systems Within the Homeland: Security Game Changer?” accessed Jan. 22, 2013, http://homeland.house.gov/hearing/subcommittee-hearing-using-unmanned-aerial-systems-within-homeland-security-game-changer.

  16. William Bratton, Zero Tolerance: Policing a Free Society, IEA Health and Welfare Unit: Choice in Welfare, No. 35 (IEA Health and Welfare Unit London, Apr. 1997), http://www.civitas.org.uk/pdf/cw35.pdf.

  17. Marta Molina, “Yo Soy 132 Rejects Election Results, Continues Organizing,” Indy Blog, July 13, 2012, http://www.indypendent.org/2012/07/13/yo-soy-132-rejects-election-results-continues-organizing.

  18. Feng Chen et al., Spatial Surrogates to Forecast Social Mobilization and Civil Unrests1 (Virginia Tech, 2012), http://people.cs.vt.edu/~naren/papers/CCC-VT-Updated-Version.pdf.

  19. David Joachim, “What Is Intelligence Chatter, Anyway?” Slate Explainer, Sept. 12, 2003, http://www.slate.com/articles/news_and_politics/explainer/2003/09/what_is_intelligence_chatter_anyway.html.

  20. Making the World a Witness: Report on the Pilot Phase, Satellite Sentinel Project, Dec. 2010, http://www.satsentinel.org/report/making-world-witness-report-pilot-phase-report.

  21. Andrew Zammit-Mangion et al., “Point Process Modelling of the Afghan War Diary,” Proceedings of the National Academy of Sciences (July 16, 2012), doi:10.1073/pnas.1203177109.

  22. Kalev Leetaru, “Culturomics 2.0: Forecasting Large-scale Human Behavior Using Global Media Tone in Time and Space,” First Monday 16, no. 9 (Sept. 2011), http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/3663/3040.

  23. Marco Lagi, Karla Z. Bertrand, and Yaneer Bar-Yam, “The Food Crises and Political Instability in North Africa and the Middle East,” New England Complex Systems Institute (July 19, 2011).

  CHAPTER 10: CRIME: PREDICTING THE WHO

  1. Adam Higginbotham, “Deception Is Futile When Big Brother’s Lie Detector Turns Its Eyes on You,” Wired, Feb. 2013, http://www.wired.com/threatlevel/2013/01/ff-lie-detector.

  2. Ralph Chatham, “Ralph Chatham’s Informal Summary of the Insights and Findings from DARPA’s Rapid Checkpoint Screening Program,” Jan. 2007, https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CDIQFjAA&url=http%3A%2F%2Fwww.cl.cam.ac.uk%2F~rja14%2Fshb08%2Fchatham1.doc&ei=1AT_UPamCIyq0AHoioHwCQ&usg=AFQjCNFzJAlk-NVHrcb6DcE9SRnREq6NWQ&sig2=21WFlClt-ekMk7qmlCAFsw&bvm=bv.41248874,d.dmQ.

  3. I. Pavlidis, J. Levine, and P. Baukol, “Thermal Image Analysis for Anxiety Detection,” in 2001 International Conference on Image Processing, 2001, Proceedings, vol. 2, 2001, 315–18, doi:10.1109/ICIP.2001.958491.

  4. Hearing on Behavioral Science and Security: Evaluating TSA’s SPOT Program, 2011, http://science.house.gov/sites/republicans.science.house.gov/files/documents/hearings/2011%2003%2030%20Ekman%20Testimony.pdf.

  5. Michael Kimlick, Privacy Impact Assessment for the Screening of Passengers by Observation Techniques (SPOT) Program (Washington, DC: U.S. Department of Homeland Security, Aug. 5, 2008), http://www.dhs.gov/xlibrary/assets/privacy/privacy_pia_tsa_spot.pdf.

  6. Eric Lipton, “Faces, Too, Are Searched at U.S. Airports,” New York Times, Aug. 17, 2006, http://www.nytimes.com/2006/08/17/washington/17screeners.html.

  7. Anthony Kimery, “TSA’s SPOT Program Not Scientifically Grounded GAO Told Congress: TSA, Experts Disagree,” Homeland Security Today, Apr. 7, 2011, http://www.hstoday.us/briefings/daily-news-briefings/single-article/tsa-s-spot-program-not-scientifically-grounded-gao-told-congress-tsa-experts-disagree/66b9300d981c1b1a39ac475411d38739.html.

  8. “Majority Views NSA Phone Tracking as Acceptable Anti-Terror Tactic,” Pew Research Center for the People and the Press, June 10, 2013, http://www.people-press.org/2013/06/10/majority-views-nsa-phone-tracking-as-acceptable-anti-terror-tactic.

  9. Scott Huddleston, “Hasan Sought Gun with ‘High Magazine Capacity,’” My San Antonio, Oct. 21, 2010, http://blog.mysanantonio.com/military/2010/10/hasan-sought-gun-with-high-magazine-capacity.

  10. James C. McKinley Jr. and James Dao, “Fort Hood Gunman Gave Signals Before His Rampage,” New York Times, Nov. 9, 2009, http://www.nytimes.com/2009/11/09/us/09reconstruct.html.

  11. Christine Baker, “A Change of Detection: To Find the Terrorist Within the Identification of the U.S. Army’s Insider Threat” (U.S. Army Command and General Staff College), accessed Jan. 22, 2013, http://www.hsdl.org/?view&did=723130.

  12. “Executive Order 13587—Structural Reforms to Improve the Security of Classified Networks and the Responsible Sharing and Safeguarding of Classified Information,” Oct. 7, 2011, http://www.whitehouse.gov/the-press-office/2011/10/07/executive-order-structural-reforms-improve-security-classified-networks.

  13. “DARPA—Anomaly Detection at Multiple Scales (ADAMS),” Oct. 19, 2010, Scribd, http://www.scribd.com/doc/40392649/DARPA-Anomaly-Detection-at-Multiple-Scales-ADAMS.

  14. Robert H. Anderson and Richard Brackney, Understanding the Insider Threat (RAND Corporation, 2004), http://www.rand.org/pubs/conf_proceedings/CF196.html.

  15. Claire Cain Miller, “Tech Companies Concede to Surveillance Program,” New York Times, June 7, 2013, http://www.nytimes.com/2013/06/08/technology/tech-companies-bristling-concede-to-government-surveillance-efforts.html.

  16. Baker, “A Change of Detection.”

  17. Ibid.

  18. O. Brdiczka et al., “Proactive Insider Threat Detection Through Graph Learning and Psychological Context,” in 2012 IEEE Symposium on Security and Privacy Workshops (SPW), 2012, 142–49, doi:10.1109/SPW.2012.29.

  19. Nate Berg, “Want to Shame a Terrible Parker? There’s an App for That,” Atlantic Cities, May 21, 2012, http://www.theatlanticcities.com/technology/2012/05/want-report-terrible-parker-theres-app/2055.

  20. “Mining Social Networks: Untangling the Social Web,” Economist, Sept. 2, 2010, http://www.economist.com/node/16910031.

  21. Julia Angwin, “U.S. Terrorism Agency to Tap a Vast Database of Citizens,” Wall Street Journal, Dec. 13, 2012, http://online.wsj.com/article/SB10001424127887324478304578171623040640006.html?user=welcome&mg=id-wsj.

  22. David Thissen and Howard Wainer, “Toward the Measurement and Prediction of Victim Proneness,” Journal of Research in Crime and Delinquency 20, no. 2 (July 1, 1983): 243–61, doi:10.1177/002242788302000206.

  CHAPTER 11: THE WORLD THAT ANTICIPATES YOUR EVERY MOVE

  1. Mike Orcutt, “The Pressure’s on for Intel,” MIT Technology Review, Nov. 9, 2012, http://www.technologyreview.com/news/507011/the-pressures-on-for-intel.

  2. Jeff Hawkins and Sandra Blakeslee, On Intelligence, 1st ed. (New York: Times Books, 2004), 6.

  3. Jason P. Gallivan et al., “Decoding Action Intentions from Preparatory Brain Activity in Human Parieto-Frontal Networks,” The Journal of Neuroscience 31,
no. 26 (June 29, 2011): 9599–610, doi:10.1523/JNEUROSCI.0080-11.2011.

  4. Moshe Bar, “The Proactive Brain: Memory for Predictions,” Philosophical Transactions of the Royal Society B: Biological Sciences 364, no. 1521 (May 12, 2009): 1235–43, doi:10.1098/rstb.2008.0310.

  5. Ibid.

  6. Scott A. Huettel, Peter B. Mack, and Gregory McCarthy, “Perceiving Patterns in Random Series: Dynamic Processing of Sequence in Prefrontal Cortex,” Nature Neuroscience 5, no. 5 (May 2002): 485–90, doi:10.1038/nn841.

  7. David Brin, The Transparent Society: Will Technology Force Us to Choose Between Privacy and Freedom? 1st trade paper ed. (New York: Basic Books, 1999).

  INDEX

  The page numbers in this index refer to the printed version of this book. The link provided will take you to the beginning of that print page. You may need to scroll forward from that location to find the corresponding reference on your e-reader.

  AAdvantage, 111

  AbouttheData.com, 120–21

  Accidents in workplace, prediction of, 176–77

  Acxiom, 119–21

  Advertising, 103–9. See also Marketing

  cookies, impact on, 105–6

  data brokerage companies, 119–21

  digital media, growth of, 104–6

  Facebook studies, 121–26

  smartphone AdWorks, 119–20

  traditional, lack of effectiveness, 104–6, 128

  user data, use of, 106–9

  AdWords, 81

  AdWorks, 119–20

  Affectiva, 44

  Afghanistan, eavesdropping sensors in, 8

  African Americans, stereotype threat and learning, 134–36

  Agriculture, climate insurance, 80–87

  Ailment Topic Aspect Model (ATAM), 61–65

  Airline rewards programs, 110

  Airport security

  lie detectors for, 202–5

  natural resistance to, 205–6

  PreCheck, 207, 210

  present ineffectiveness of, 205

  sensors, use in airlines, 8

  Allan, Alasdair, 20–21

  Alloy, 177

  Almeida, David, 41

  Alter, Alexandra, 99

  Amatriain, Xavier, 87–89, 98

  Amazon, reader-behavior analysis, 99–100

  American Airlines, AAdvantage, 110

  American Civil Liberties Union (ACLU), 30

  Animal behavior, earthquake prediction, 3–4

  Annalect, 108

  Anomaly Detection at Multiple Scales (ADAMS), 209

  Apps, and naked future, xvi–xvii

  Arab Spring, predictive indicators, 200

  ArcGIS, 119

  Aristotle, 92–93

  Artificial intelligence, brain and predictive systems, 227–32, 236

  Astrology, Vedic, matchmaking in, 152–53, 182

  AT & T, advertisers, connecting to users, 119–20

  Attention span

  film shot length based on, 100–101

  and interactive quizzes, 133–34

  Audience Propensities, 120

  Automobiles, tracking, 212

  Bakshy, Eytan, 122–24

  Balance theory, and matchmaking services, 158–61

  Banjo, 19

  Bar, Moshe, 232–35

  Bastardi, Joe, 69

  Bayes, Thomas, 23–24

  Bayesian Additive Regression Tree for Quasi-Linear (BART-QL), 94–98

  Bayes theorem, 23–25

  Bergen meteorology school, 71

  Betts, Phyllis, 189

  Biden, Joe, 196

  Big data, xiii–xvi

  availability to public, xiv

  Internet searches on, xiii

  media reports on, xiii–xiv

  and metadata, xv–xvi

  and overfitting, 5

  prediction, use of, xiii–xiv, 181–82

  pros and cons of, xvii

  retail sector use of, xiv

  and telemetry, xiv–xvi

  bin Laden, Osama, 199–200

  Black Death, 49–50

  Blacker, Irwin, 91

  Blinder, Martin, 43

  Blipcare, 43

  Blondel, Vincent, 18

  BlueDar, 163

  Bogost, Ian, 149

  Borden, Ed, 11

  Bowman, Courtney, 218–19, 221

  Brain

  future as product of, 232–36

  neocortex, structure and functions, 227–28

  and personality traits, 172–74

  predictive power of, 227–36

  predictive systems modeled on, 227–36

  Bratton, William, 186–87

  Brdiczka, Oliver, 211–12

  Bream Brush, 44

  Breunig, Drew, 108

  Brin, David, 238

  Broken-windows theory, 184

  Bugeja, Michael, 150

  Bush, George W., 79

  Caldwell, Cindy, 176–77

  Canopy Labs, 113–16

  Carter, Graydon, 32

  Cascio, Jamais, 20

  CELab, 163

  Centers for Disease Control (CDC), flu data collection, 61–62

  Central Intelligence Agency (CIA), 218, 239

  Chemistry.com, 173

  Cheney, Dick, 7

  China, predictive policing, 187

  Christakis, Nicholas, 60

  Christal, Raymond, 173

  Chua, Sacha, 33–34, 44

  Cigarette smoking, Twitter data analysis, 108–9

  CiviGuard, 16–17

  Climate. See Weather and climate prediction

  Climate Corporation, 81–86

  Closed-circuit TV (CCTV), for predictive policing, 194–95

  Cloud, student records in, 129–30

  Cogito, 44

  Communication

  character established by, 168

  interaction patterns in, 168–69

  marriage partners, 178–79

  Obama-Romney debate, 170–71

  poker players, visual cues, 169–70

  sociometers/honest signals, 167–72, 174

  Computing

  machine-to-machine connections, scope of, 6

  memory, development of, 231–32

  mobile technology. See Mobile devices

  ubiquitous, 6, 238

  Connection tracking system, 218–21

  Consent to Research project, 46–48

  Consumers

  behavior prediction product, 120–21

  data brokerage companies, 119–21

  of grocery items. See Grocery stores; Walmart

  and rewards programs, 111–13

  ZIP code for classifying, 118–19

  Cookies, and digital ads, 105–6

  Cooper, Kimbal E., 57

  Cosm (Pachube), 10–12

  Coursera, 133–40, 150–51

  Coyne, Chris, 157

  Craigslist, 156

  Creative class cities, 150

  Crime prediction. See Predictive policing

  Crowd-sourcing, evidence of crimes, 213–17

  Culham, Jody, 232

  Customer loyalty programs, gambling casinos, 109–13

  Cutting, James E., 100

  Data

  big data, xiii–xvi

  data brokerage companies, 119–21

  personal. See Personal data

  resellers, 156

  sensory, xv–xvi

  Data leakage, 20–21

  Daydreaming, 233

  Defense Advanced Research Projects Agency (DARPA), 204, 209, 211, 237–38

  DeLong, Jordan E., 100

 
Denby, David, 96

  Department of Homeland Security, 207

  Doctrine of Critical Days, 49–50

  Domestic Communications Assistance Center (DCAC), 212

  Dopamine-based personality, 172

  Dorgan, Bryan, 237

  Downing, King, 204

  Dredze, Mark, 61–65

  Duhigg, Charles, xiii

  Dunning-Kruger effect, 36

  Dyson, George, 74–75

  Eagle, Nathan, 163–65

  Earthquake Early Warning (EEW) system, 2–4, 9

  Earth Shaker myth, 3–4

  eBay, 156

  e-books, reader-behavior analysis, 99–100

  Education, 129–51

  cloud, student records in, 129–30

  Coursera, 133–40, 150–51

  flip model of, 137–38

  higher, benefits of, 131

  interactive quizzes, 133–34

  Ivy League online courses, 138

  massively open online course (MOOC), 133, 148–50

  One Laptop per Child (OLPC) concept, 142–47

  online, and telemetric data collection, 134, 136–38, 140–42

  remedial learning online, 149

  self-learning via computer interface study, 144–48

  stereotype threat and minority students, 134–36

  team-learning, 144, 146

  traditional, lack of effectiveness, 132–33, 143–44, 149

  Udacity, 138–40

  U.S. costs per student, 131

  edX program, 138

  eHarmony, 156

  Eigendecomposition, 27–28

  Eisenhower, Dwight D., 71–72

  Ekman, Paul, 203–4

  Electronic Frontier Foundation, 30

  Electronic Numerical Integrator and Computer (ENIAC), 72–74

  Electronic Surveillance (ELSUR) Strategy, 212

  Eliashberg, Jehoshua, 89–91, 94–98, 102

  Emergency response systems

  for earthquakes, 2–4, 9

  geographically-based, 16–17

  Guardian Watch, 15–16, 213–16

  neighborhood watch network, 213–17

  Enlightenment, progress as concept of, xii

  Environmental disasters

  earthquake prediction, 2–4

  Fukushima Daiichi meltdown, 9–11

  Gowanus Canal toxicity, 12–14

 

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