Page 45

or detecting socially detrimental activities, because it avoids the uncertainty and confusion that may arise from multiple identities (notwithstanding that multiple identities can serve useful and socially desirable purposes, as described previously). Credit card companies, for example, can conduct behavior-pattern analysis for fraud detection. 23 Similar technologies must be used to detect behavior indicative of impending criminal or terrorist activities, although this raises concerns about profiling.

On the negative side, such analysis also enables invasions of personal privacy. The extent to which this occurs would depend heavily on the circumstances under which an individual can be compelled to present an ID, what information is retained, and which activities are tracked within the system (a topic explored above). Indeed, detecting a problem might only be possible in some instances through broad analysis. This would necessitate examining the behavior of many people who do not pose a risk—most human behavior involves law-abiding citizens pursuing constitutionally protected activities—in order to identify the few who do. 24

23Credit card companies make these correlations using both standard statistical methods and neural networks.

24For a discussion of some of the effects and implications of ubiquitous surveillance cameras, see the October 7, 2001, article by Jeffrey Rosen, “A Watchful State,” New York Times Magazine.

The National Academies of Sciences, Engineering, and Medicine
500 Fifth St. N.W. | Washington, D.C. 20001

Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement