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TitleProfiling Machines: Mapping the Personal Information Economy
Author
LanguageEnglish
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Total Pages191
Table of Contents
                            ACKNOWLEDGMENTS
1 The Culture and Technologies of Profiling
2 A Diagram of Panoptic Surveillance
3 Consumption in the Network Age: Solicitation, Automation, and Networking
4 Mapping Profiles
5 Deploying Profiles in Promotional Events
6 The "State" of a Panoptic Medium
7 The Politics of Profiling
NOTES
BIBLIOGRAPHY
INDEX
                        
Document Text Contents
Page 1

GREG ELMER

Mapping

the Personal

Information

Economy

P R O F I L I N G M A C H I N E S

Mapping

the Personal

Information

Economy

G R E G E L M E R

In this book Greg Elmer brings the perspectives of cul-
tural and media studies to the subject of consumer pro-
filing and feedback technology in the digital economy.
He examines the multiplicity of processes that monitor
consumers and automatically collect, store, and cross-
reference personal information. When we buy a book at
Amazon.com or a kayak from L.L. Bean online, our
transactions are recorded, stored, and deployed to
forecast our future behavior—thus we may receive so-
licitations to buy another book by the same author or
the latest in kayaking gear. Elmer charts this process,
explaining the technologies that make it possible and ex-
amining the social and political implications.

Elmer begins by establishing a theoretical frame-
work for his discussion, proposing a “diagrammatic ap-
proach” that draws on but questions Foucault’s theory of
surveillance. In the second part of the book, he presents
the historical background of the technology of consumer
profiling, including such pre-electronic tools as the cen-
sus and the warranty card, and describes the software and
technology in use today for demographic mapping. In the
third part, he looks at two case studies: a marketing
event sponsored by Molson that was held in the Cana-
dian Arctic (contrasting the attendees and the indige-
nous inhabitants) and the use of “cookies” to collect
personal information on the World Wide Web, which
(along with other similar technologies) automate the
process of information collection and cross-referencing.
Elmer concludes by considering the politics of profiling,
arguing that we must begin to question our everyday
electronic routines.

Greg Elmer is Associate Professor in the Depart-
ment of Communication at Florida State University. He is
the editor of Critical Perspectives on the Internet and
coeditor of the journal Space and Culture.

Elmer's study of profiling zeroes in on a key aspect of modern media spaces. He takes us
beyond the study of texts and contexts to look at the forms of linkage and feedback that
media regimes use to define and delimit the role of the consumer and the citizen. This is a
great book for anybody trying to puzzle out how media, technology, power, and subjectiv-
ity function in the contemporary world.”
McKenzie Wark, New School University

An important study of how consumers are tracked and solicited in the new information
economy. Drawing on Deleuze's concept of control societies, Elmer introduces a much
needed update of the literature on surveillance to account for profiling and data mining
technologies, and, most crucially, maps out potential spaces of resistance.”
William C. Bogard, Professor of Sociology, Whitman College

In a world increasingly networked, automated, and invisibly connected, Greg Elmer's Pro-
filing Machines is a health alert, a political prophecy, and an ethical challenge. Forget the
surveillance state: data mining, cookies, and personal profiling are the tools of increas-
ingly powerful global commercial corporations. Somehow we always thought the Web
would combine anonymity with the right to become truly individual. Elmer shows how the
erosion of anonymity has turned us into economic and lifestyle data sets, traded without
our even knowing it. Thoroughly researched, passionately argued, this is a bracing ac-
count of the ethics, aesthetics, and likely futures of the Web that should be read by every-
one who has ever surfed, as well as every student of public relations and marketing.”
Sean Cubitt, Professor of Screen and Media Studies, University of Waikato, New Zealand

Greg Elmer has produced a lucid and concise analysis of the panoptic information society.
Profiling Machines makes a very important contribution to what is now a critical agenda
in contemporary cultural and political debate.”
Kevin Robins, Goldsmiths College, University of London

The MIT Press

Massachusetts Institute of Technology

Cambridge, Massachusetts 02142

http://mitpress.mit.edu

0-262-05073-0

P R O F I L I N G
M A C H I N E S

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45469Elmer 1/27/04 3:22 PM Page 1

Page 95

C l e a n i n g D i r t y D a t a : T h e C y c l e

N e v e r E n d s

It is . . . subsumed and amassed cultural capital that map-

making societies bring to the task of making maps; not the

patiently acquired mastery of this or that individual more or

less carefully passed on—often in secret—through speech or

gesture or inculcated habit. It is the endlessly reproduced and

everywhere disseminated wisdom of thousands of such indi-

viduals, caught up, stored, annotated, corrected, indexed,

epitomized, reduced to formulae, taught by rote, so that

what once was an epochal discovery or invention is reduced

to common knowledge, grounded into a taken-for-granted

fact of life. (Wood 1992, 48)

In attempting to rethink database technology (and dataveillance)

within the context of computer networks, solicitation techniques,

and information mapping software, information is consistently

updated in a cybernetic or cyclical fashion—a process that is

heightened by its constant production of graphic representations of

space (maps). Although one could rightly argue on purely tech-

nological grounds that computerized maps can condense data more

e‰ciently than database outputs or that the power of maps stems

from their representational status as iconic, easily recognizable

signs, such approaches nevertheless fail to account for the reflexive

element of reproduction, spurred on by the need to accumulate

increasingly more precise data profiles. Geocoding psychographics

from a database, for example, is essential for successful mail-order

campaigns (catalogues), yet at the same time there is no absolute

requirement to view (in the graphical sense of the term) the

addresses and geographical entity in question (that is, the topo-

graphical market). As such, this indexical approach could be inter-

preted as making a clear distinction between human features and

topological characteristics: ‘‘It is important to understand that geo-

84

Page 96

coding software applications do not require a mapping system

[such as GIS]. A geocoder simply reads data, analyzes the address

specific portion of the data, and then attempts to match each

address with a location, a latitude and longitude’’ (MapInfo 1995,

3).

The introduction of computer maps by GIS, however, calls into

question this ‘‘split’’ between human and geographic data—a

bifurcation often characterized by empirical and scientific claims.

In other words, traditionally (Martin 1991, 4–5),

data relating to dynamic human populations are very di¤er-

ent in their geographic properties to those relating to the

physical world: the location of any individual is almost

always referenced via some other spatial object, such as a

household address or a census data collection unit. Unlike a

road intersection or a mountain summit, we are rarely able

to define the location of an individual simply by giving their

map reference.

Thus in addition to the obvious claims of e‰ciency and ‘‘clarity’’

—to the extent that GIS produces pictures of relationships—

such computer maps also enter into a search for empirical or

‘‘true’’ representations of both the geographic and human world.

Given the inherent problems in predicting human behavior and

the ever-changing environment (natural and human), we might

ask ourselves how an accurate picture is ever achieved. One

answer (to return to the cybernetic qualities of diagrammatic

thinking) is by cleaning. According to the Group 1 Software cor-

poration, ‘‘Dirty data is the number one cause behind inaccurate

mapping analysis’’ (MapWorld 1996, 5). In the case of the data-

base, then, the process of capturing the world ‘‘out there’’ must be

up to date. It cannot be missing a zip code, or consumer promo-

tions, political campaign material, and state documents would

M
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Page 190

of personal information, 11, 22,

80–82

Tracking

of business inventories, 64–66

and Web cookies, 116–119

Trademarks, 53

Tuktoyaktuk, Canada, 98, 99,

105–107, 109

Tulloch, John, 8–9

Typographical profile, 22

United States Chamber of

Commerce, 61

United States government, 69–70

UNIVAC I computer, 60

Universal Product Code (UPC),

70. See also Bar codes

characteristics of, 66

concerns about, 67–68

use of, 65

Varela, Francisco, 43

Virgin Airlines, 91, 93

Visual representations, 22

V96 Festival, 91, 93

von Neumann, John, 63

Wang, Paul, 75

Warranty cards, 25

Warren, William E., 80

Web. See also Internet

and predictive techniques, 49

and privacy, 112–113 (see also

Cookies [Web])

Web browsers and browsing. See

Browsers and browsing (Web)

Web cookies. See Cookies (Web)

Weber, Max, 17

Webster, Frank, 15

Wernick, Andrew, 4

Whitaker, Reg, 30

Wiener, Norbert, 43, 62, 147n2

Williams, Raymond, 16–17

Wood, Denis, 84

Woodstock 1994, 99

Woollacott, Janet, 8

Xanadu system, 113

X-Files, The (television show), 134

Yahoo!, 115, 116, 117, 126–128,

129

In
d

e
x

179

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