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Tarleton Gillespie
The Relevance of Algorithms
Julian Ausserhofer
24.07.13, HIIG Journal Club
- Frankfurter Allgemeine Zeitung, 14.07.13, S. 17
- http://www.guardian.co.uk/science/2013/jul/01/
how-algorithms-rule-wor...
http://algopop.tumblr.com/
"What we need is an interrogation of algorithms as a key feature of our
information ecosystem [… &]
of the cultural forms ...
"public relevance algorithms" p. 2
1. Patterns of inclusion
2. Cycles of anticipation
3. The evaluation of relevance
4. The promise of algorithmic objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
1. Patterns of
inclusion
2. Cycles of
anticipation
3. The evaluation
of relevance
4. The promise of
algorithmic
objectivit...
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The Relevance of Algorithms

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Tarleton Gillespie wrote an excellent article on "the relevance of algorithms". I presented a summary of his paper at the weekly so called "journal club" of the Alexander von Humboldt Institute for Internet and Society in Berlin. These are the slides that summarize the talk and his paper.

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The Relevance of Algorithms

  1. 1. Tarleton Gillespie The Relevance of Algorithms Julian Ausserhofer 24.07.13, HIIG Journal Club
  2. 2. - Frankfurter Allgemeine Zeitung, 14.07.13, S. 17 - http://www.guardian.co.uk/science/2013/jul/01/ how-algorithms-rule-world-nsa - http://www.spiegel.de/international/zeitgeist/max- mosley-sues-google-in-landmark-battle-over-digital- rights-a-853008.html - http://mediadecoder.blogs.nytimes.com/ 2009/10/19/the-robots-are-coming-oh-theyre-here/
  3. 3. http://algopop.tumblr.com/
  4. 4. "What we need is an interrogation of algorithms as a key feature of our information ecosystem [… &] of the cultural forms emerging in their shadows [… &] attention to […] political ramifications." p. 2
  5. 5. "public relevance algorithms" p. 2
  6. 6. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics
  7. 7. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion What makes it into an index and what is excluded? - algorithms work on top of databases - data must be collected, processed & made "algorithm ready" - data is designed to be fit for collection - criteria for in- or exclusion are usually not transparent
  8. 8. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Screenshots: http://amaditalks.tumblr.com/post/13513981784/siri Idea: http://vimeo.com/channels/551921/69641358
  9. 9. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Attempts to know and predict users - "second index " (Stalder & Mayer, 2009) - "not just provide information to users, […] also providing users to their algorithms" (Gillespie, 2013, p. 7) - questions of privacy, representation & access - example: real-time bidding
  10. 10. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Evaluation signals are opaque - every algorithmic decision is based on inscribed criteria or signals, that are mostly kept secret - a "black boxed" technology, but not stable (Latour, 1987) - the role of the "inscriber"
  11. 11. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Screenshots, 24.07.13 Idea: http://vimeo.com/ channels/551921/69641358
  12. 12. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion The assurance of impartiality - objectivity has been a disputed concept, long before public relevance algorithms - algorithms work as "stabilizers of trust " p. 13 - a way to deflect responsibility? (Morozov, 2011)
  13. 13. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Screenshot: http://www.businessinsider.com/google-pulls-out-of-china-2010-3
  14. 14. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Users reshape their practices to suit the algorithms - algorithms "induce subtle reorientations of […] practices" p. 18 - content is shaped to make it algorithmically recognizable - testing and reverse engineering of algorithms - users "domesticate" algorithms, changes lead to critique
  15. 15. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Screenshot: https://www.facebook.com/derziegelstein
  16. 16. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Algorithmic presentations of publics shape a public's sense of itself - "algorithms are a key technological component " of mediated publics p. 22 - "calculated publics"? p. 23 - the representations of public get again taken up by users or authorities
  17. 17. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Screenshot: http://www.amazon.com/Software-Command- International-Critical-Aesthetics/dp/1623567459/ref=pd_ys_ir_all_2
  18. 18. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion Ausserhofer & Maireder, 2013
  19. 19. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Conclusion - "[…] thinking not simply about how they [algorithms] work, where they are deployed, or what animates them financially" p. 25 - "not just as codes with consequences, but […] a new knowledge logic" p. 26 - "[…] algorithms remain outside our grasp and they are designed to be." p. 26
  20. 20. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics Discussion - How can we turn algorithms "into an object of productive inquiry"? Barocas et al., 2013, p.1
  21. 21. 1. Patterns of inclusion 2. Cycles of anticipation 3. The evaluation of relevance 4. The promise of algorithmic objectivity 5. Entanglement with practice 6. The production of calculated publics References - Ausserhofer, J., & Maireder, A. (2013). National Politics on Twitter: Structures and Topics of a Networked Public Sphere. Information, Communication & Society, 16(3), 291–314. doi:10.1080/1369118X. 2012.756050 - Barocas, S., Hood, S., & Ziewitz, M. (2013). Governing Algorithms: A Provocation Piece. Presented at the Governing Algorithms Conference, New York. Retrieved from http://papers.ssrn.com/abstract=2245322 - Gillespie, T. (forthcoming). The Relevance of Algorithms. In T. Gillespie, P. Boczkowski, & K. Foot (Eds.), Media Technologies: Paths Forward in Social Research. Cambridge, MA: MIT Press. Retrieved from http:// www.tarletongillespie.org/essays/Gillespie%20-%20The%20Relevance%20of%20Algorithms.pdf - Morozov, E. (2011, July 13). Don’t Be Evil. The New Republic. Retrieved from http:// www.newrepublic.com/article/books/magazine/91916/google-schmidt-obama-gates-technocrats - Latour, B. (1987). Science in Action: How to Follow Scientists and Engineers Through Society. Cambridge, MA: Harvard University Press. - Stalder, F., & Mayer, C. (2009). The Second Index: Search Engines, Personalization and Surveillance. In K. Becker & F. Stalder (Eds.), Deep Search: The Politics of Search beyond Google (pp. 98–115). London: Transaction Publishers. Retrieved from http://felix.openflows.com/node/113

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