The Filter Bubble by Eli Pariser
My rating: 4 of 5 starsThough our angles are slightly different, Pariser and I are worried about similar things: how platforms like Google and Facebook are compiling our personal data to create a “theory of identity for each user.” Pariser’s worried about what personalization means for human curiosity, serendipity, and democracy when personalization filters show us more of what we already like. I’m more concerned with how personal identity as profiled and collected on these platforms, what control we have over these profiles, as well as our sense of ownership (both legally and in terms of a mental model) over this data.
Pariser’s aim is noble: he follows up on a personal curiosity to explain to the average user how Facebook and Google’s roles as intermediaries filter our experience of the web. He successfully brings to light some features and biases inherent in the algorithms that come between us and the information we seek that are not always obvious to the non-tech savvy user. This is a goal I identify with; it’s something I aim to accomplish in my own research and writing.
But where Pariser falls short in letting the work of others speak for him. The book reads like a Who’s Who of the non-fiction technology and behavioral psychology best sellers over the last decade (Lessig, Kelly, Ariely, and he even makes the amateur faux pas of invoking McLuhan). Granted, these guys have contributed a lot that’s worth reference. But aside from Pariser’s basic premise, I’m afraid he’s doing more summarizing than he is adding to the discourse. The result is that the book reads as his own filter bubble: the experts anecdotes and observations, presented in support his largely political argument.
Pariser also fails at seeing his suggestions for improvement through. Though engineers could feasibly develop algorithms that introduce serendipity, for example, he doesn’t take it further to speculate how such algorithmic tweaks might be profitable or beneficial to their platforms, which leaves little chance for this to be practically implemented. While some users might prefer a search platform with such features, the it’s difficult to see how users would demand for such a market to bear these tweaks. Pariser doesn’t reconcile algorithmic biases with the business models they optimize and support.
Pariser also gets into trouble by basing his arguments in privacy debates. In paragraphs like the following, he starts from a privacy argument and extends it to his own information consumption concern:
“Marc Rotenberg, executive director of the Electronic Privacy Information Center, says, ‘We shouldn’t have to accept as a starting point that we can’t have free services on the Internet without major privacy violations.’ And this isn’t just about privacy. It’s also about how our data shapes the content and opportunities we see and don’t see. And it’s about being able to track and manage this constellation of data that represents our lives with the same ease that companies like Acxiom and Facebook already do.”Though these algorithms run on the same data that is as much a concern for privacy as it is for personalization, I fear that these kinds of argumentative extensions conflate concerns in an unproductive and confusing way for the average user. He also makes sloppy errors referring at times to both personal data and private data, two very distinctly different categories with different concerns and implications in my mind. I struggle with these challenges myself, and too often subtly can be lost when you get lumped into the privacy.
Ultimately Pariser succeeds at his aim: a call for awareness, advocating for greater public filter literacy. We all need to question and acknowledge personalization’s affects on our information consumption. He does a good job of reaching a broad audience with concise sentences that bring his point home: “If we want to know what the world really looks like, we have to understand how filters shape and skew our view of it.” Now that we’re all more aware of what’s going on, I’m still left with the question: can personalization be inherently bad or good? I think Pariser believes it’s not so binary (as indicated by his Kranzberg citation), but for his target audience, this is perhaps too subtle a conclusion.
On a funnier note: I have to thank Pariser for pointing out this glaringly obvious observation I had previously missed: “Page had come up with a novel approach, and with a geeky predilection for puns, he called it PageRank.”
![hautepop:
“The best minds of my generation are thinking about how to make people click ads. That sucks”
Jeff Hammerbacher, quoted in This Tech Bubble is Different by Ashlee Vance, Business Week.14 April 2011.
I’m Being Followed: How Google—and 104 Other Companies—Are Tracking Me on the Web Alexis Madrigal, The Atlantic, 29 Feb 2012.
1. Using Mozilla’s tool Collusion to find out how many companies are tracking him online (105).
2. How the online advertising ecosystem is structured - basically:
Helping advertisers buying adspace, e.g. media planning & buying (green, on left)
Helping sellers of adspace, mostly to deliver particular types of people (blue, on right)
Delivering more data or faster service or better measurement (orange)
3. A detailed look at three of these companies & what they actually do:
All three companies want to know as much about me and what’s on my screen as they possibly can, although they have different reasons for their interest. None of them seem like evil companies, nor are they singular companies. Like much of this industry, they seem to believe in what they’re doing. They deliver more relevant advertising to consumers and that makes more money for companies. They are simply tools to improve the grip strength of the invisible hand.
4. You can’t stop data collection. Opt-out tools stop you from receiving targeted ads - they don’t stop data being collected.
5. Why data is still collected - mostly for advertising performance management:
But the NAI code also recognizes that companies sometimes need to continue to collect data for operational reasons that are separate from ad targeting based on a user’s online behavior. For example, online advertising companies may need to gather data to prove to advertisers that an ad has been delivered and should be paid for; to limit the number of times a user sees the same ad; or to prevent fraud. Gathering this operational data may involve the use of cookies separate from those used to enable interest-based ad targeting, or to maintain a consumer’s opt out preference.
Chuck Curran, then-Network Advertising Initiative chief, in Moving the Goal Posts Without Changing the Rule Book, 14 July 2011
6. But opting out from being tracked is exactly what web-users want (and think they’re getting.
7. The bigger questions: should the ability to opt-out of tracking be a right? And why?
Companies’ ability to track people online has significantly outpaced the cultural norms and expectations of privacy. This is not because online companies are worse than their offline counterparts, but rather because what they can do is so, so different. We don’t have a language for talking about how these companies function or how our society should deal with them.
The word you hear over and over and over is that targeted ads can be “creepy.” It even crops up in the academic literature, despite its vague meaning in this context. My intuition is that we use the word “creepy” precisely because it is an indeterminate word. It connotes that tingling-back-of-the-neck feeling, but not necessarily more than that. The creepy feeling is a sign to pay attention to a possibly harmful phenomenon. But we can’t sort our feelings into categories — dangerous or harmless — because we don’t actually know what’s going to happen with all the data that’s being collected.
8. Two slightly unclear points:
Online searches are tracked by cookies, which serve as identity-markers but aren’t connected to your actual identity through your name or other real-world markers of identity (passport, social security number). That’s a good thing. However this can & will change.
A machine watching what you do is more “private” than a human being watching it. So at the moment that’s ok - but as machine learning develops, that privacy will be lost.
9. Conclusions - it’s difficult:
Tech solutions will be developed, but only small elites will use them. Most internet users will continue to give away vast amounts of information.
However targeted advertising is how websites make money - and it’s hard enough [for magazines & news media] to do that online as it is.
Advertising-supported free media is better than paywalled closed media.
10. Optimistic coda:
Perhaps there are natural limits to what data targeting can do for advertisers and when we look back in 10 years at why data collection practices changed, it will not be because of regulation or self-regulation or a user uprising. No, it will be because the best ads could not be targeted. It will be because the whole idea did not work
*
C O M M E N T
A lot of interesting and important points raised. Very useful to see how the online advertising ecosystem is actually structured - a hell of a lot of companies - and it’s good to see reasons for tracking explained too. What’s important to acknowledge is that these companies aren’t actively malicious or trying to build a dystopia of total surveillance - that’s really the unintended side effect of trying to work out how to sell you a pair of shoes you looked at in a store two days ago. The motivations are very prosaic and not in themselves evil - the “creepy” that Madrigal outlines so well is an emergent property of the system.
Second useful thing was learning that “do not track” options don’t actually deliver not-tracking. It will be incredibly difficult to do this effectively:
The industry will resist any regulation.
Market research is claiming an exemption from do not track settings and I would bet that much of the tracking Madrigal describes (from the orange ‘support’ services) might claim to be market research measurement.
Companies will claim ignorance about the rules, and not follow them
Companies will claim exemption by being based in parts of the world where these laws don’t reach.
Clients (brands buying advertising) will not exercise any oversight - let alone due diligence - on the ad services they’re buying. There’ll be a lot of “don’t ask, don’t tell” to continue delivering illegal or illegit tracking.
Third useful thing: we’ve got to think about how websites can make money. Advertising is the business model enabling the free-at-the-point-of-use web. Subscription is not only a bad idea (a more closed web), it can’t work - I read far too many different news sites to be able to subscribe to them all. Voluntary micropayments? Possibly, though it’d be fascinating to see how those would be distributed - likely to very rapidly shake up what’s a viable web news site.
Fourth point to remember: maybe targeted advertising won’t deliver what brands (ad buyers) need. Definitely some mileage in this argument. Niche targeting can’t deliver that watercooler moment where everyone’s talking about a new ad because they’ve all seen it - and how well can it predict who best to serve ads designed to build brand awareness, not direct purchases? It also undersells strong creative, which can appeal to people beyond the targeted niche. Essentially I can see the prestigious campaigns with the biggest ad spends choosing not to buy targeted space (which is after all more expensive) - and also perhaps premium press choosing not to sell it. (However that still leaves ambulance-chasing lawyers on DailyStar.co.uk, so not a total panacea.)](http://25.media.tumblr.com/tumblr_m0dxgqfTHo1qcq6s5o1_1280.png)
“The best minds of my generation are thinking about how to make people click ads. That sucks”
Jeff Hammerbacher, quoted in This Tech Bubble is Different by Ashlee Vance, Business Week.14 April 2011.
I’m Being Followed: How Google—and 104 Other Companies—Are Tracking Me on the Web
Alexis Madrigal, The Atlantic, 29 Feb 2012.1. Using Mozilla’s tool Collusion to find out how many companies are tracking him online (105).
2. How the online advertising ecosystem is structured - basically:
- Helping advertisers buying adspace, e.g. media planning & buying (green, on left)
- Helping sellers of adspace, mostly to deliver particular types of people (blue, on right)
- Delivering more data or faster service or better measurement (orange)
3. A detailed look at three of these companies & what they actually do:
All three companies want to know as much about me and what’s on my screen as they possibly can, although they have different reasons for their interest. None of them seem like evil companies, nor are they singular companies. Like much of this industry, they seem to believe in what they’re doing. They deliver more relevant advertising to consumers and that makes more money for companies. They are simply tools to improve the grip strength of the invisible hand.4. You can’t stop data collection. Opt-out tools stop you from receiving targeted ads - they don’t stop data being collected.
5. Why data is still collected - mostly for advertising performance management:
But the NAI code also recognizes that companies sometimes need to continue to collect data for operational reasons that are separate from ad targeting based on a user’s online behavior. For example, online advertising companies may need to gather data to prove to advertisers that an ad has been delivered and should be paid for; to limit the number of times a user sees the same ad; or to prevent fraud. Gathering this operational data may involve the use of cookies separate from those used to enable interest-based ad targeting, or to maintain a consumer’s opt out preference.
Chuck Curran, then-Network Advertising Initiative chief, in Moving the Goal Posts Without Changing the Rule Book, 14 July 2011
6. But opting out from being tracked is exactly what web-users want (and think they’re getting.
7. The bigger questions: should the ability to opt-out of tracking be a right? And why?
Companies’ ability to track people online has significantly outpaced the cultural norms and expectations of privacy. This is not because online companies are worse than their offline counterparts, but rather because what they can do is so, so different. We don’t have a language for talking about how these companies function or how our society should deal with them.
The word you hear over and over and over is that targeted ads can be “creepy.” It even crops up in the academic literature, despite its vague meaning in this context. My intuition is that we use the word “creepy” precisely because it is an indeterminate word. It connotes that tingling-back-of-the-neck feeling, but not necessarily more than that. The creepy feeling is a sign to pay attention to a possibly harmful phenomenon. But we can’t sort our feelings into categories — dangerous or harmless — because we don’t actually know what’s going to happen with all the data that’s being collected.
8. Two slightly unclear points:
- Online searches are tracked by cookies, which serve as identity-markers but aren’t connected to your actual identity through your name or other real-world markers of identity (passport, social security number). That’s a good thing. However this can & will change.
- A machine watching what you do is more “private” than a human being watching it. So at the moment that’s ok - but as machine learning develops, that privacy will be lost.
9. Conclusions - it’s difficult:
- Tech solutions will be developed, but only small elites will use them. Most internet users will continue to give away vast amounts of information.
- However targeted advertising is how websites make money - and it’s hard enough [for magazines & news media] to do that online as it is.
- Advertising-supported free media is better than paywalled closed media.
10. Optimistic coda:
Perhaps there are natural limits to what data targeting can do for advertisers and when we look back in 10 years at why data collection practices changed, it will not be because of regulation or self-regulation or a user uprising. No, it will be because the best ads could not be targeted. It will be because the whole idea did not work*
C O M M E N T
A lot of interesting and important points raised. Very useful to see how the online advertising ecosystem is actually structured - a hell of a lot of companies - and it’s good to see reasons for tracking explained too. What’s important to acknowledge is that these companies aren’t actively malicious or trying to build a dystopia of total surveillance - that’s really the unintended side effect of trying to work out how to sell you a pair of shoes you looked at in a store two days ago. The motivations are very prosaic and not in themselves evil - the “creepy” that Madrigal outlines so well is an emergent property of the system.
Second useful thing was learning that “do not track” options don’t actually deliver not-tracking. It will be incredibly difficult to do this effectively:
- The industry will resist any regulation.
- Market research is claiming an exemption from do not track settings and I would bet that much of the tracking Madrigal describes (from the orange ‘support’ services) might claim to be market research measurement.
- Companies will claim ignorance about the rules, and not follow them
- Companies will claim exemption by being based in parts of the world where these laws don’t reach.
- Clients (brands buying advertising) will not exercise any oversight - let alone due diligence - on the ad services they’re buying. There’ll be a lot of “don’t ask, don’t tell” to continue delivering illegal or illegit tracking.
Third useful thing: we’ve got to think about how websites can make money. Advertising is the business model enabling the free-at-the-point-of-use web. Subscription is not only a bad idea (a more closed web), it can’t work - I read far too many different news sites to be able to subscribe to them all. Voluntary micropayments? Possibly, though it’d be fascinating to see how those would be distributed - likely to very rapidly shake up what’s a viable web news site.
Fourth point to remember: maybe targeted advertising won’t deliver what brands (ad buyers) need. Definitely some mileage in this argument. Niche targeting can’t deliver that watercooler moment where everyone’s talking about a new ad because they’ve all seen it - and how well can it predict who best to serve ads designed to build brand awareness, not direct purchases? It also undersells strong creative, which can appeal to people beyond the targeted niche. Essentially I can see the prestigious campaigns with the biggest ad spends choosing not to buy targeted space (which is after all more expensive) - and also perhaps premium press choosing not to sell it. (However that still leaves ambulance-chasing lawyers on DailyStar.co.uk, so not a total panacea.)
Syllabus for Paul Duguid & Geoffrey Nunberg’s Concept of Information at Ischool, Berkeley
I love this syllabus.
As it’s generally used, “information” is a collection of notions, rather than a single coherent concept. In this course, through readings, discussions, exercises, and lectures, we’ll examine various conceptions of information based in information theory, philosophy, social science, law, economics, and history. Issues include: How compatible are these conceptions; can we talk about “information” in the abstract? What work do these various notions play in discussions of the public sphere, the media, the political process and political science, economics, organization studies, and just plain search? We’ll also explore the implications of the range of conceptions for “information studies” and “the information society”?
Gleick, James. 2011. The Information: A History, A Theory, A Flood New York: Viking.
Week 1
17 Jan: Introduction
Slides: Geoff
19 Jan: Exercise: I-School Identities
Reading
- Wobbrock, Jacob O., Andrew J. Ko, & Julie A. Kientz, 2009. ““Reflections on the Future of iSchools from Inspired Junior Faculty,” Interactions 16 (September-October)
- Pollock, Martha E. 2010. “Reflections on the Future of iSchools,” Interactions 17(January-February)
- iSchool Faculty. 2008. “Elevator Stories.“
Background
- Brouillon, L. 1956. Science and Information Theory. New York: Academic Press.
- Schrader,Alvin M. 1984. “In Search of a Name: Information Science and Its Conceptual Antecedents,” Library and Information Science Research 6(3): 227-272
Zeitgeist
- Verity, John, 1994. “The Information Revolution: Introduction,” Business Week, May 18, 1994.
Slides: Geoff
Week 2
24 Jan: Playing With Words: “Technology,” “Platform,” and Other “Keywords”
Reading
- Marx, Leo. 2010. ”Technology: The Emergence of a Hazardous Concept,” Technology & Culture 51(3):561-577.
- Gillespie, Tarleton. 2010. “The Politics of ‘Platforms,’” New Media & Society 12(3): 347-364.
Background
- Duff, A. S., Craig, D., & McNeill, D. A. 1996. “A Note On the Origins Of the ‘Information Society.’” Journal of Information Science, 22(2): 117 -122.
- Jones, William. 2010, “No Knowledge but through information”
<=”” em=”“> 15(9-6).
- Rosenberg, Daniel. 2012. “Toward a Quantitative History of Data,” Paper Presented at the American Historical Association Meetings, Chicago. [author’s draft; available through bspace]
- Tuomi, Ilkka. 1999. “Data is More Than Knowledge: Implications of the Reversed Knowledge Hierarchy for Knowledge Management and Organizational Memory,” Journal of Management Information Systems 16(3): 103-117.
Zeitgeist
- Kelly, Kevin. 2010. What Technology Wants. New York: Viking.
- Duguid, Paul. 2011. “Spin Cycle” (Review of Tim Wu, The Master Switch, & Kevin Kelly, What Technology Wants. Nation, January 10/17
Slides
26 Jan: Exercise: Producing and Consuming Information
Reading
- Lyman, Peter, & Hal Varian,. 2003. “How Much Information?: Executive Summary
- Bohn, Roger E. & James E. Short. 2009. How Much Information? 2009: Report on American Consumers
Week 3
31 Jan: How Much Information?
Reading
- Blair, Ann. 2003 ”
Reading Strategies for Coping with Information Overload, ca 1550-1700,” Journal of the History of Ideas 64(1): 11-28
Background
- Bell, Daniel. 1976. The Coming of Post-Industrial Society: A Venture in Social Forecasting.New York, NY: Basic Books.
Blair, Ann, 2011. Too Much to Know: Managing Scholarly Information before the Modern Age. New Haven: Yale University Press.
- Brown, John Seely & Paul Duguid. 2000. “Limits to Information,” chapter 1 in The Social Life of Information, Boston: Harvard University Press.
- Green, John C. 1964. “The Information Explosion: Real or Imaginary,” Science 144(3619): 646-648.
- Kallinkikos, Jannis. 2006. The Consequences of Information: Institutional Implications of Technological Change. Cheltenham, UK: Edward Elgar.
- Lesk, Michael. 1996. “How Much Information is There in the World?”
- Mayer-Schönberger, Viktor. 2009. Delete: The Virtue of Forgetting in the Digital Age, Cambridge: Harvard University Press.
- Machlup, Fritz. 1962. The Production and Distribution of Knowledge in the United States. Princeton, NJ: Princeton University Press.
- Pool, I. de S. 1983. “Tracking the Flow of Information.” Science, 221(4611): 609-613.
- Porat, Marc U. 1977. The Information Economy: Sources and Methods for Measuring the Primary Information Sector, Washington, D.C.
- Rosenberg, Daniel. 2010. Introduction [to panel of historians on Information Overload]. Journal of the History of Ideas. 64(1): 1-9.
Zeitgeist
- IBM Global Technology Services, 2006. “The Toxic Terabyte: How Data-Dumping Threatens Business Efficiency,” July.
- Hemp, Paul. 2009. “Death by Information Overload,” Harvard Business Review 87(9): 82-89
- Schiffman, Betsy. 2008. “Web 2.0 Preview: Torture by Information Overload,” Wired Blog
- Foley, John. 1995. “New Tools Can Help Tame an Ocean of Data,” Information Week. October 30.
Slides: Paul
2 Feb: History of “Information”—1
Reading
- Nunberg, Geoffrey, 1996. “Farewell to the Information Age” in G. Nunberg, ed., The Future of the Book, Berkeley: University of California Press. Read pp. 1-23.
- The Oxford English Dictionary entry for ‘information’. Go to the OED here and look up information. You can skip the first senses under I, but look closely at senses II.4.a; II.5a-e, 6. Look also at the compounds at the end of the entry. Try to read the citations as well, at least from the 18th c. on — often these help to fill in exactly what the definition means.
- Gleick, James. 2011. The Information. Pantheon. “Prologue.” Online here if you haven’t received/dowloaded your copy yet.
Background
- Salthe, Stanley N. 2011. “Naturalizing Information.” Information 2011, 2, 417-425.
- Nunberg, G. 2011. Review of The Information, by James Gleick. The New York Times Book Review, March 18, 2011.
- Newman, Julian. 2001. “Some Observations on the Semantics of ‘Information.’“ Information System Frontiers, 3:2, 155-167.
Zeitgeist
Slides
Week 4
7 Feb: History of “Information”—2
Reading: See 2 Feb.
9 Feb: The “Public,” the Public Sphere, and Public Opinion
Reading
- Habermas, Jürgen, 1989. “Introduction: Preliminary Demarcation of a Type of Bourgeois Public Sphere” pp 1-13 in Jürgen Habermas, 1989. The Structural Transformation of the Public Sphere: An Inquiry into a Category of Bourgeois Society. Cambridge, MA: MIT Press. [download from bspace]
- Calhoun, Craig. 1996. “Introduction: Habermas and the Public Sphere,” pp 1-48 in Calhoun, ed., Habermas and the Public Sphere. Cambridge, MA: MIT Press
Background:
- Calhoun, Craig, ed. 1996. Habermas and the Public Sphere. Cambridge, MA: MIT Press.
- Darnton, Robert. 2000. “An Early Information Society: News and the Media in Eighteenth-Century Paris” American Historical Review 105(1).
- Darnton, Robert. 1991. “An Enlightened Revolution,” New York Review of Books 38 (17 October 24)
- Habermas, Jürgen, Sara Lennonx, & Frank Lennox. 1974. “The Public Sphere: An Encyclopedia Article.” New German Critique 3(Autumn): 49-55.
- Hohendahl, Peter. 1974. “Jürgen Habermas: &39;The Public Sphere.&39 New German Critique 3(Autumn): 45-48.
- Raymond, Joad, ed. 1999.
News, Newspapers and Society in Early Modern Britain. London: Frank Cass
- Sommerville, C. John. 1997. “Surfing the Coffeehouse,” History Today 47(6): 8-10
Zeitgeist:
- Shirky, Clay. 2008. “The Newspaper Industry and the Arrival of the Glaciers,” Boing Boing, December 28
Slides Paul
Week 5
14 Feb: From the Bourgeois Public Sphere to the Internet
Reading
- Habermas, Jürgen, 1989. “On the Concept of Public Opinion” pp 236-250 in Jürgen Habermas, The Structural Transformation of the Public Sphere: An Inquiry into a Category of Bourgeois Society. Cambridge, MA: MIT Press.
- Papacharissi, Zizi. 2002. “The Virtual Public Sphere: The Internet as a Public Sphere,” New Media & Society 4(1): 9-27
- Poster, Mark. 1995. “The Net as a Public Sphere,” Wired 3.11 (November)
Slides: Paul
16 Feb: Exercise: Public Opinion
Week 6
21 Feb: Information and the State
Reading
- Giddens, Anthony. 1981. “Surveillance and the Capitalist State,” pp 169-176 in A. Giddens, A Contemporary Critique of Historical Materialism, vol 1 Power, Property, and the State. Berkeley: University of California Press.
- Scott, James C., John Tehranian, & Jeremy Mathias. 2002. “The Production of Legal identities Proper to States: The Case of the Permanent Family Surname,” Comparative Studies in Society and History 44(1): 4-44.
Background:
- Agar, John. 2003. The Government Machine: A Revolutionary History of the Computer. Cambridge, MA: MIT Press.
- Campbell-Kelly, Martin, 2002. “Information Technology and Organizational change in the British Census, 1801-1911,” Information Systems Research 7(1): 35-57.
- Cullen, Michael J. 1975 The Statistical Movement in Early Victorian Britain: The Foundations of Empirical Social Research. Harvester Press: New York.
- Hacking, Ian. 1990. The Taming of Chance. Cambridge: Cambridge University Press.
- Headrick, Daniel R.. 2000. When Information Came of Age: Technologies of Knowledge in the Age of Reason and Revolution. New York: Oxford University Press.
- Oettinger, Anthony. 1980. “Information Resources: Knowledge and Power and the 21st Century,” Science[Centennial Issue, July 4] 209 (4452): 191-198.
- Rusnock, Andrea A. 2002. Vital Accounts: Quantifying Health and Population in England and France. Cambridge: Cambridge University Press.
Zeitgeist:
- Barlow, John Perry. 1996. “ A Declaration of the Independence of Cyberspace.
- Dyson, Esther, et al. 1994. “Cybespace and the American Dream: A Magna Carta for the Knowledge Age”
- Read, William H. 1978. “Information as a National Resource,” Journal of Communication 29(1): 172-178.
Slides: Paul
23 Feb: Information and the Organization
Reading
- Kline, Ronald, R. 2006. “Cybernetics, Management Science, and Technology Policy, The Emergence of ‘Information Technology’ as a Keyword, 1948-1985.” Technology and Culture 74: 513-535
Background
- Raff, Daniel & Peter Temin. 1991. “Business History and Recent Economic Theory: Imperfect Information, Incentives and the Internal Organization of Firms” pp: 7-41 in Peter Temin, ed., Inside the Business Enterprise: Historical Perspectives on the Use of Information. Chicago: Chicago University Press.
Zeitgeist
Slides: Paul
Week 7
28 Feb: Information and Objectivity
- Schudson, Michael. “The Objectivity Norm in American Journalism,“ Journalism 2(2): 149-170.
- Mindich, David. 2000. Just the Facts: How “Objectivity” Came to Define American Journalism. NYU Press. Introduction and Ch 1, pp. 1-39.
- Datson, Lorraine and Peter Galison. 1992. “The Image of Objectivity.” Representations 40 (Special Issue: Seeing Science): 81-128.
Background:
- Schudson, Michael. 2003. “Where News Came From: The History of Journalism,” pp. 64-89 in Michael Schudson, The Sociology of News. New York: Norton.
- Chalaby, Jean K. 2000. The Invention of Journalism. Palgrave Macmillan.
- Tucker, J. 1997. “Photography as Witness, Detective, and Impostor: Visual Representation in Victorian Science,” in Bernard Lightman, ed. Victorian Science in Context. Chicago: University of Chicago Press.
- Green, David. 1984. “Veins of Resemblance: Photography and Eugenics.” Oxford Art Journal7(2): 3-16.
Zeitgeist:
- Nunberg, Geoffrey. 2006. “The War on Truth,” pp. 168ff in Nunberg, G. Talking Right: How Conservatives Turned Liberalism into a Tax-Raising, Latte-Drinking, Sushi-Eating, Volvo-Driving, New York Times-Reading, Body-Piercing, Hollywood-Loving, Left-Wing Freak Show. NewYork, PublicAffairs. Chapter 11, (175 in pdf) to 185 (191 in pdf). [download from bSpace.]
- “Press Accuracy Rating Hits Two-Decade Low” Pew Research Center, 9/14/09.
- Liberman, Mark (2005-12-23). “Multiplying Ideologies Considered Harmful.” Language Log.
- “Media Bias Is Real, Finds UCLA Political Scientist,” UCLA newsroom
- Visit the websites of Media Research Center, Fair.org, mediamatters.org.
1 Mar: Exercise: Objectivity
Week 8
6 Mar: Information and Political Science
Reading
- Lippmann, Walter. 1922. Public Opinion. New York: Harcourt Brace. ch. 6-7, 13-14.
(Google Book; Also available at Project Gutenberg)
- Popkin, Samuel L.1994. The Reasoning Voter. Chicago: Chicago University Press. Chch. 1-3, 5. (Google Book). An abridged version is available via Google Books as “Information Shortcuts and the Reasoning Voter,” in Bernard N. Grofman, ed. Information, Participation, and Choice, Michigan, 1995
Background:
- Dewey, John. “The Public and its Problems,” in Andreas Hess, ed., 2003, American Social and Political Thought, New York: NYU Press. Selection from Dewey’s The Public and its Problems, 1927 (Swallow Press, 1991).
- Carey, James W. 1991. “The Press, Public Opinion, and Public Discourse,” in Theodore Lewis Glasser & Charles T. Salmon, eds., Public Opinion and the Communication of Consent.
- Anthony Downs. 1957. An Economic Theory of Democracy. New York: Harper and Row. See also “An Economic Theory of Political Action in a Democracy,” The Journal of Political Economy16(2): 135-150.
- Kinder, Donald R., 2003. “Communication and Politics in the Age of Information,” in David O. Sears and Leonie Huddy, eds., Oxford Handbook of Political Psychology. Oxford: Oxford University Press.
- Page, Benjamin I. and Robert Y. Shapiro, 1992.
The Rational Public: Fifty Years of Trends in Americans’ Policy Preferences. Chicago: University of Chicago Press
Slides
8 Mar: Exercise: Political Science
Slides
Week 9
13 Mar: Information and the Organization of Knowledge
Reading
- Burke, Peter. “Classifying Knowledge” chapter 5 in Peter Burke, A Social History of Knowledge. Cambridge: Polity.
Background:
- Yeo, Richard. 1991. “Reading Encyclopedias: Science and the Organization of Knowledge in British Dictionaries of Arts and Sciences, 1730-1850.” Isis, 82: 24-49.
- McArthur, Tom. 1986. Ch 12-15, pp. 91-133 in Worlds of Reference. Cambridge: Cambridge University Press.
- Samuel Johnson. 1755. Preface to the Dictionary of the English Language, London.
- Foucault, Michel. 2002. “Classifying.” Chapter 5 of The Order of Things. London: Routledge. (trans. of Les Mots et Les Choses, 1966).
Most of the chapter is viewable at Google Books, and a plaintext version is also available here. - d’Alembert, Jean Le Rond. 1751. Preliminary Discourse to the Encyclopedia of Diderot, Selections from Part I. (Entire text can be found here.)
Book of plates from Diderot’s Encylopedie at archive.org. Slide hand icon at bottom to browse.
Slides
15 Mar: Exercise: The Internet and the Organization of Knowledge
Final Paper/Project Proposals Due
Slides
Week10
20 Mar: Theories of Information—1
Reading
- Gleick, James. 2001. “Information Theory” Chapter 7 in Gleick, James The Information:: A History, A Theory, A Flood. New York: Viking.)
- Shannon, C. E. 1948. “A Mathematical Theory of Communication,” Bell Systems Technical Journal, July & October (Reprinted in ACM SIGMOBILE 5(1) 2001: 3-55
- Shannon, C. E. 1956. “The Bandwagon,” IRE Transactions on Information Theory 2 (March): 3.
Background
- Gallager, G. 2001. “ Claude E. Shannon: A Retrospective on His Life, Work, and Impact.” IEEE Transactions on Information Theory 47:7 (November).
- Dretske, F. I. 1981. Knowledge and the Flow of Information. Cambridge, MA: MIT Press.
- Hartley, R.V.L. 1928. “Transmission of Information,” Bell System Technical Journal 535-584.
- Israel, David and John Perry, What is Information? pp. 1-19 in Philip Hanson, ed., Information, Language and Cognition. Vancouver: University of British Columbia Press.
- Weaver, Warren. 1998 (1949). “Some Recent Contributions to The Mathematical Theory of Communication,” introduction to The Mathematical Theory of Communication. University of Illinois Press.
Zeitgeist
Slides
22 Mar: Information, Economics, and Development
- Stiglitz, Joseph E. 2002. “Information and the Change in the Paradigm in Economics,” The American Economic Review 92(3): 460-501.
- Romer, Paul. 1993. “Idea Gaps and Object Gaps in Economic Development,” Journal of Monetary Economics 32(3): 543-573.
Background:
- Ancori, Antoine Bureth & Patrick Cohendet. 2000. “Economics of Knowledge: The Debate about Codification & Tacit Knowledge,” Industrial and Corporate Change, 9(2): 255-287.
- Arrow, Kenneth J. 1984. “Information and Economic Behavior” pp: 136-152 in K. Arrow, Collected Papers. Cambridge, MA: Harvard University Press.
- Cowan, Robin, Paul A. David & Dominique Foray. 2000. “The Explicit Economics of Knowledge Codification and Tacitness,” Industrial and Corporate Change, 9(2): 211-253.
- Duguid, Paul. 2005. “‘The Art of Knowing’: Social and Tacit Dimensions of Knowledge and the Limits of the Community of Practice.” The Information Society 2005 21(2): 109-118.
- Hayek, Frederich. 1937. “Economics and Knowledge,” Economica 4[NS](13): 35-54.
- Hirshleifer, J. 1973. “Where Are We in the Theory of Information?,”American Economic Review, 2: 31-39.
- Krugman, Paul. nd. “The Fall and Rise of Development Economics” Working Paper[?].
- Learner, Edward E. & Michael Storper, 2001. “The Economic Geography of the Internet Age,” Journal of International Business Studies. 32(4): 641-665.
- Machlup, Fritz & Una Mansfield. 1983. “Semantic Quirks in Studies of Information,” in The Study of Information: Interdisciplinary Messages. New York: Wiley: 641-71.
- Richardson, George B. 1960. Information and Investment: A Study in the Working of the Competitive Economy. Oxford: Oxford University Press.
- Shapiro, Carl. 1982. “Consumer Information, Product Quality and Seller Reputation,” Bell Journal of Economics, 13(1): 20-35.
- Shapiro, Carl & Hal R. Varian. 2000. Information Rules: A Strategic Guide to the Network Economy. Boston: Harvard University Press.
Zeitgeist:
- Kelly, Kevin. 1997. “New Rules for the New Economy,” Wired 5.09.
Week 11
Midterm break
- No classes -
Week 12
3 April: Theories of Information—2
Reading
- tba
Background
Zeitgeist
Slides
5 Apr: Information and Cognitive Science—1
Reading
- Gardner, Howard. 1987. Introduction & Ch. 1, pp. 3-44. in Howard Gardner, The Mind’s New Science: A History of the Cognitive Revolution. New York: Basic Books. (At Google Books).
- Miller, George A. 1956. “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information,” The Psychological Review 63: 81-97.
Background:
- Simon, Herbert A. 1980. “Cognitive Science: The Newest Science of the Artificial,“ Cognitive Science 4: 33-46.
- Miller, George A. 2003. “The cognitive revolution: a historical perspective.“ Trends in Cognitive Sciences, 7(3 March): 141-144.
- Chomsky, Noam. 1959. “Review of Verbal Behavior, by B.F. Skinner.”. Originally published in Language 35.
- Bolter, David Jay. 1984. Turing’s Man: Western Culture in the Computer Age. Chapel Hill: University of North Carolina Press.
- Turing, Alan. 1950. “Computing Machinery and Intelligence,” Mind 59(235): 433-460.
- Gardner, Howard, 1987. The Mind’s New Science: A History of the Cognitive Revolution. New York: Basic Books.
- Johnson, George. 1986 Machinery of the Mind: Inside the New Science of Artificial Intelligence. Redmond, WA: Tempus/Microsoft Press.
- Searle, John. 1980. “Minds, Brains, & Programs,” The Behavioral and Brain Sciences 3(3): 417-457
- Waldrup, M. Mitchell. 1987. Man-Made Minds: The Promise of Artificial Intelligence. New York: Walker and Company.
Slides
Week 13
10 Apr: Information and Cognitive Science—2: Critique
Reading
- Suchman, Lucy. 1993. “Response to Vera and Simon’s ‘Situated Action: A Symbolic Interpretation,’” Cognitive Science 17(1): 71-75.
- Vera, Alonso H. & Simon, Herbert A. 1993. “Situated Action: A Symbolic Interpretation,” Cognitive Science 17(1): 7-48.
Background:
- Dreyfus, Hubert L. 1979. What Computers Can’t Do: The Limits of Artificial Intelligence. New York: Harper & Row.
Slides
12 Apr: Discussion: Outline of Finals Papers/Projects
Slides
Week 14
17 Apr: Searching for Information
Reading
- Bush, Vanevar. 1945. “As We May Think.” The Atlantic (July)
- Duguid, Paul. 2010. “The World According to Grep: A Progress from Open to Closed?” in Konrad Becker & Felix Stalder, eds., Deep Search Vienna: Studienverlag, 2009.
Background:
- Battelle, John. 2005. The Search: How Google and Its Rivals Rewrote the Rules of Business and Transformed Our Culture. New York: Portfolio.
- Brin, Sergey & Lawrence Page, 1998. “Anatomy of a Large-Scale, Hypertextual Digital Search Engine.”
- Buckland, Michael K. 1997. “What Is a ‘Document’?“ Journal of the American Society for Information Science 48(9): 804-809.
- Buckland, Michael K. 1992. “Emanuel Goldberg, Electronic Document Retrieval, and Vannevar Bush’s Memex,“ Journal of the American Society for Information Science 43(4): 284-294.
- Raff, Adam. 2009. “Search, but You May Not Find,” New York Times, December 28.
- Chartier, Roger. 1994. The Order of Books: Readers, Authors, and Libraries in Europe between the Fourteenth and Eighteenth Centuries. Stanford: Stanford University Press
- Geertz, Clifford. 1978. “The Bazaar Economy: Information and Search in Peasant Marketing,” 68(2):28-32.
- Otlet, Paul, 1990. “Something about Bibliography,” pp.11-24 in W. Boyd Rayward, ed., International Organisation and Dissemination of Knowledge: Selected Essays of Paul Otlet. Amsterdam: Elsevier. Internet Archive.
Slides
19 Apr: Memes & Political Information
Reading
- Gleick, James. 2001. “Into the Meme Pool ” Chapter 11 in Gleick, James The Information:: A History, A Theory, A Flood. New York: Viking. B&N)
- Dennett, Daniel C. 1990. “Memes and the Exploitation of Imagination.“ The Journal of Aesthetics and Art Criticism, 48(2): 127-135.
Background:
- Dawkins, Richard. 1989. “Memes, The New Replicators,& quot; pp 189-201. The Selfish Gene. Oxford: OUP. Also here.
- Mayr, Ernst. “The Objects of Selection.” 1997. Proc. Natl. Acad. Sci. 94 (March): 2091-2094,
- Sperber, Dan. 2000. “An objection to the memetic approach to culture,” pp 163-173 in Robert Aunger ed., Darwinizing Culture: The Status of Memetics as a Science. Oxford University Press.
- Atran, Scott. “The trouble with memes.“ Human Nature 12(4): 351-381.
- Nettle, Daniel. 2002. “The Elusive Science of the Meme (Aunger’s Darwinizing Culture).” Current Anthropology 43(2 April): 344-346.
Zeitgeist:
- Gunders, John and Damon Brown. 2010. The Complete Idiot’s Guide to Memes, New York: Penguin Books.
Slides
Week 15
24 Apr: Exercise: Memes
26 Apr: Wrap: Has This Course Provided Any Information?
Week 16: Reading Week
1 May: Final Paper/Project Presentations
11 May: Final Paper/Project Due
Our lives often contain too much information to figure out what is triggering a particular behavior. Do you eat breakfast at a certain time because you’re hungry? Or because the morning news is on? Or because your kids have started eating? Experiments have shown that most cues fit into one of five categories: location, time, emotional state, other people or the immediately preceding action.
Privacy is dead not because private data will be exposed but because of what can be inferred in from analysis of your public data.
The value of information is based on familiarity, not scarcity.” @jpbarlow on the phone just now, talking about piracy as free marketing
The problem of course is that the “power” of big data to help answer challenging questions relies upon the quality of that underlying data. And by “quality,” I don’t simply mean whether the data is accurate (which we will see is a fraught term in itself), but instead I am concerned with what sorts of assumptions are present in the collection of that data, what’s being left out, and how does the process of data collection influence the results?
What I am trying to demonstrate is that data, like science, is not as purely objective as we typically think it is. By assuming the objectivity of the underlying data, we set ourselves up to make large-scale decisions without properly challenging them because they are based on data, and that data “can’t be wrong”. The solution however is not to rid the data of all subjective intrusions because at a certain point this is not possible. What I am advocating is to approach big data with a healthy skepticism and an awareness of the ways in which it is lacking or only presenting a part of the picture.
Massive, crucial point, beautifully expressed - and by an undergrad no less (by name of Evan Freedman).
Comment on The Limits of Big Data by Klint Finley on RWW, June 2011
(via hautepop)
(via digitalurbanisms)
“Within the next few years an important threshold will be crossed: For the first time ever, it will become technologically and financially feasible for authoritarian governments to record nearly everything that is said or done within their borders—every phone conversation, electronic message, social media interaction, the movements of nearly every person and vehicle, and video from every street corner.
Plummeting digital storage costs will soon make it possible for authoritarian regimes to not only monitor known dissidents, but to also store the complete set of digital data associated with everyone within their borders. These enormous databases of captured information will create what amounts to a surveillance time machine, enabling state security services to retroactively eavesdrop on people in the months and years before they were designated as surveillance targets. This will fundamentally change the dynamics of dissent, insurgency and revolution.
(via digitalurbanisms)
It looks like a human was involved in choosing what went where,” Marissa told them. “It looks too editorialized. Google products are machine-driven. They’re created by machines. And that is what makes us powerful. That’s what makes our products great.
Marissa Mayer addressing Google designers, as quoted in “In The Plex” by Steven Levy (via buzz)
(via benkraal, Dan W)
(via slavin)
Role of Information in Cyberpunk
“Information is, in fact, the true medium of exchange in cyberpunk. (As Snow Crash adeptly points out, even the franchized service industries really boil down to nothing more than information.) Perhaps the fact that so many heroes in cyberpunk literature are criminals can be explained by authors largely committed to the old hacker ethic: information wants to be free. In a world where bits are the only real commodity—those bits could represent a coded Swiss bank account, new military icebreakers, or the formula for a new synthetic drug giving a cheaper high (or, for that matter, Coca-Cola)—only the informed survive. Drugs are perhaps the closest physical analogue to information; all you need is a formula and a hired chemical lab, and you’ve got a salable good. How will it be purchased, though? In most cyberpunk literature, physical dollar bills are no longer even widely accepted currency. Many works posit other currencies (yen, Euros) replacing the dollar in importance; many more suggest either that folding money will be replaced entirely by digital transactions or that private currencies will be issued. In Gibson and Swanwick’s short story “Dogfight,” antique laminated dollars circulate as money, but only for their value as collectables.
Our guides to the post-industrial economy come from several quarters. Future guru Alvin Toffler and his Gingrinchian allies provide relatively positive visions of the future as slowly but inexorably shaped by the market. Black and Bey provide models of resistance (dropping out of the rat race or creating new, rhizomatic economies) that, often as not, look toward the past. Primarily, though, the guides are Marshall McLuhan, Guy Debord, Jean Baudrillard, and Pierre LÈvy, each of whom has his own take on what the knowledge space (to use LÈvy’s term) will be like.”
(Source: cyberartsweb.org)
