Eli Pariser - The Filter Bubble

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An eye-opening account of how the hidden rise of personalization on the Internet is controlling—and limiting—the information we consume. In December 2009, Google began customizing its search results for each user. Instead of giving you the most broadly popular result, Google now tries to predict what you are most likely to click on. According to MoveOn.org board president Eli Pariser, Google’s change in policy is symptomatic of the most significant shift to take place on the Web in recent years—the rise of personalization. In this groundbreaking investigation of the new hidden Web, Pariser uncovers how this growing trend threatens to control how we consume and share information as a society—and reveals what we can do about it.
Though the phenomenon has gone largely undetected until now, personalized filters are sweeping the Web, creating individual universes of information for each of us. Facebook—the primary news source for an increasing number of Americans—prioritizes the links it believes will appeal to you so that if you are a liberal, you can expect to see only progressive links. Even an old-media bastion like
devotes the top of its home page to a news feed with the links your Facebook friends are sharing. Behind the scenes a burgeoning industry of data companies is tracking your personal information to sell to advertisers, from your political leanings to the color you painted your living room to the hiking boots you just browsed on Zappos.
In a personalized world, we will increasingly be typed and fed only news that is pleasant, familiar, and confirms our beliefs—and because these filters are invisible, we won’t know what is being hidden from us. Our past interests will determine what we are exposed to in the future, leaving less room for the unexpected encounters that spark creativity, innovation, and the democratic exchange of ideas.
While we all worry that the Internet is eroding privacy or shrinking our attention spans, Pariser uncovers a more pernicious and far-reaching trend on the Internet and shows how we can—and must—change course. With vivid detail and remarkable scope,
reveals how personalization undermines the Internet’s original purpose as an open platform for the spread of ideas and could leave us all in an isolated, echoing world.

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231 “the common good”:Arthur Nauman, “News Ombudsmanship: Its Theory and Rationale,” Press Regulation: How Far Has it Come? symposium, Seoul, South Korea, June 1994.

232 that this expectation is one that… most Americans share:Jeffrey Rosen, “The Web Means the End of Forgetting,” New York Times Magazine , July 21, 2010, www.nytimes.com/2010/07/25/magazine/25privacy-t2.html?_r=1&pagewanted=all.

235 “help it find a larger audience”:Author interview with confidential source.

237 Google is just a company:“Transcript: Stephen Colbert Interviews Google’s Eric Schmidt on The Colbert Report, ” Search Engine Land , Sept. 22, 2010, accessed Dec. 20, 2010, http://searchengineland.com/googles-schmidt-colbert-report-51433.

237 expose their audiences to both sides:Cass R. Sunstein, Republic .com (Princeton: Princeton University Press, 2001).

240 “we shouldn’t have to accept”:Caitlin Petre phone interview with Marc Rotenberg, Nov. 5, 2010.

241 and 70 percent do:“Mistakes Do Happen: Credit Report Errors Mean Consumers Lose,” US PIRG, accessed Feb. 8, 2010, http://www.uspirg.org/home/reports/report-archives/financial-privacy–security/financial-privacy-security/mistakes-do-happen-credit-report-errors-mean-consumers-lose.

INDEX

accessibility bias

Act of Creation, The (Koestler)

Acxiom

Adderall

advertars

advertiser-funded media (AFM)

advertising

augmented reality and

brand fragmentation and

day-parting and

disclosure of personalization in

in social spaces

on television

Afghanistan

agents:

humanlike

intelligent

Alexander, Christopher

algorithms

CineMatch

EdgeRank

Google search

OkCupid

PageRank

political districts and

Amazon

Kindle

Web Services

ambient intelligence

Americans for Job Security

Anderson, Chris

Angleton, James Jesus

anonymity

Anti, Michael

Apple

Newton

architecture and design

Arendt, Hannah

argument styles

Ariely, Dan

Arnold, Stephen

art

Asimov, Isaac

AT&T

Atlantic

attention crash

augmented cognition (AugCog)

augmented reality

Barlow, John Perry

Battelle, John

Bay, Michael

behavioral retargeting

Bell, Gordon

Benkler, Yochai

Berners-Lee, Tim

Bezos, Jeff

Bharat, Krishna

Bhat, Tapan

Bing

Bishop, Bill

Blades, Joan

blogs

BlueCava

BlueKai

Bohm, David

Bohr, Niels

books

advertising in

digitized

Bosworth, Andrew

Bowling Alone (Putnam)

boyd, danah

Boyd, Wes

BP

brain

Brand, Stewart

brand fragmentation

bridges

Brin, Sergey

Burnham, Brad

Burnham, Terence

Bush, George W.

Bush, Vannevar

Buzzfeed

California

Calo, Ryan

Campbell, Donald

Caro, Robert A.

Catalist

categories, wide

censorship

Chait, Jon

China

Internet police in

Pabst in

CIA

CineMatch

cities

architecture and design in

Clarium

click signals

Clinton, Bill

cloud

Coca-Cola Village Amusement Park

code and programmers

coding, conceptual

Cohen, Claudia

Cohler, Matt

Coleman, Gabriella

collaborative filtering

confirmation bias

Conley, Dalton

cookies

Cortés, Hernán

Coyne, Chris

craigslist

creativity and innovation

credit reports

Cropley, Arthur

curators, see editors and curators

curiosity

cybernetics

DARPA

data laundering

dating sites

OkCupid

day-parting

De Castro, Henrique

defaults

democracy

dialogue and

design and architecture

Dewey, John

dialogue

Digg

DirectLife

discovery

disintermediation

Dixon, Pam

DNA

Do Not Track list

Dostoyevsky, Fyodor

Downey, Tom

Duncker, Karl

Dyson, Esther

EchoMetrix

Eckles, Dean

EdgeRank

editors and curators

Eliza

e-mail

constitutional protections and

Gmail

engineers

Erowid

Europe

evolution

Eysenck, Hans

Facebook

advertisements and

EdgeRank and

Everywhere

Google and

identity and

Like button on

local-maximum problem and

lock-in and

News Feeds on

political advertising and

political involvement and

privacy policy of

Twitter compared with

facial recognition

Fair Credit Reporting Act

Fair Information Practices

Fallows, James

Farah, Martha

FBI

Flatow, Alfred

Foer, Josh

Foisie, Philip

Founder’s Fund

Foursquare

France

Fried, Charles

Friedman, Patri

Friedman, Tom

friendly world syndrome

Friendster

From Counterculture to Cyberculture (Turner)

fundamental attribution error

Gawker

geeks

Gelernter, David

Gellman, Robert

genetic data

Gerbner, George

Gibson, William

Gilbert, Dan

Glass, Ira

Gmail

Google

China and

dashboard of

digitized books and

Docs

“Don’t be evil” slogan of

ethics and

Facebook and

facial recognition and

Gmail

Instant

lock-in and

News

Oceana and

PageRank

Picasa

political advertising and

political involvement and

Reader

Research

search algorithm of

Translate

Voice

government

Graber, Doris

gun registration

Habermas, Jurgen

Hackers (Levy)

hackers, hacking

Hare, Brian

Harris, Vincent

Hastings, Reed

Hauser, John

Hayes, Gary

Heiferman, Scott

Heuer, Richards

Hillis, Danny

Hoekstra, Pete

Huffington Post

humanlike agents

Hume, David

IBM

identity

identity loops

induction

infomercials

information gap

Inglehart, Ron

Institute

intelligent agents

Interactive Advertising Bureau (IAB)

iPhone

IQ

Iraq

i-traffic

iTunes

Iyengar, Shanto

jet pilots

Jiang Zemin

Jobs, Steve

Johnson, Steven

Joy, Bill

Kaczinski, Ted

Kafka, Franz

Kalathil, Shanthi

Kane, Patrick

Kantorovich, Aharon

Katona, George

Kayak

Kazmaier, Dick

Kekule, Friedrich

Keller, Bill

Kelly, Kevin

Kennedy, John F.

Kirkpatrick, David

Klein, Paul

Koestler, Arthur

Kranzberg, Melvin

Krohn, Max

Kwan, Julianne

language translation

Lanier, Jaron

Last Question, The (Asimov)

LeanBack

learning

machine

least objectionable programming

Lee, Kai-Fu

Lessig, Larry

Levy, Steven

Lewis, Andrew

Liberty and the News (Lippmann)

Liebling, A. J.

LinkedIn

Linux

Lippmann, Walter

Livingston, Jessica

local-maximum problem

lock-in

“Long Live the Web” (Berners-Lee)

Loopt

Lovell, Todd

Lowenstein, George

luck

Lynch, Zack

Ma, Jack

MacDougald, Harry

machine learning

Mancini, Paul

Mark, David

Mayer, Marissa

Mayer-Schonberger, Viktor

McLarty, Mack

McLuhan, Marshall

McPhie, Jonathan

Meadowlands

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