Reading List

An ongoing list of critical research on the study of algorithms and culture or algorithmic culture
By Laila Shereen Sakr and Amr El Abbadi

Critical Algorithm Studies: a Reading List by Tarleton Gillespie and Nick Seaver. This list is also available as a visual timeline and a public Zotero library.

0. overviews

0.1 technical and philosophical precursors / emic “what are algorithms?” essays
0.2 field surveys / keywords / initial provocations
0.3 books about algorithms addressed to broader audiences
0.4 conferences focused on algorithms and society
0.5 lists of algorithm studies resources
0.6 syllabi that focus on algorithms and society

1. the specific implications of algorithms and the choices they make

1.1 algorithms have embedded values / biases, lead to personalization / social sorting / discrimination
1.2 with algorithms come rationalization / automation / quantification, and the erasure of human judgment / complexity / context
1.3 questions of accountability and policy responses around algorithms

2. algorithms fit with, and help advance, specific ideological worldviews

3. algorithms are complex technical assemblages, that have to be mapped

4. algorithms aren’t just technical artifacts, they’re fundamentally human in their design and their use

4.1 people design and maintain algorithms, in specific ways, and that matters
4.2 people work, play, and live with algorithms, in specific ways, and that matters
4.3 what do users understand about algorithms
4.4 the discursive production of algorithms to shape their public perception

5. methods and approaches for studying algorithmic systems

Diakopoulos, Nicholas (May 23, 2016) “We need to know the algorithms the government uses to make important decisions about us.” 

Diakopoulos, Nicholas (Feb 2016) Accountability in Algorithmic Decision Making. Communications of the ACM (CACM). 

Diakopoulos, Nicholas (October 3, 2013)  “Rage Against the Algorithms,” The Atlantic.

Gangadharan, Septa Peña, Ed. (2014) Data and Discrimination: Collected Essays, Open Technology Institute.

Gillespie, Tarleton, “Algorithms, clickworkers, and the befuddled fury around Facebook Trends” (May 18, 2016)

Facebook Trending: It’s made of people!! (but we should have already known that)” (May 9, 2016)

Fuller, Matthew and Graham Harwood, “Algorithms are Not Angels” (video lecture)

Gillespie,Tarleton “The Relevance of Algorithms,” in Gillespie, Boczkowski, and Foot (eds.), Media Technologies: Essays on Communication, Materiality, and Society (Cambridge: MIT Press, 2014), 167–93.

Gillespie (2016). “#TrendingisTrending: When Algorithms Become Culture.”

Hamish Robertson and Joanne Travaglia (2015). “Big data problems we face today can be traced to the social ordering practices of the 19th century

Mackenzie, Adrian and Theo Vurdubakis (2011) “Codes and Codings in Crisis: Signification, Performativity and Excess,” Theory, Culture & Society 28.6, 3–23.

Manovich, Lev “The Science of Culture?” Cultural Analytics, Social Computing, and the Digital Humanities,” (2016).

Pasquale, Frank, The Black Box Society: the secret algorithms that control money and information (Cambridge: Harvard UP, 2015), 1–18, 213–218.

Slavin, Kevin (2011) “How Algorithms Shape Our World” (TEDGlobal, Video lecture)

Stanton, Andrew, Amanda Thart, Ashish Jain, Priyank Vyas, Arpan Chatterjee, Paulo Shakarian (2016) “Mining for Causal Relationships: A Data-Driven Study of the Islamic State.”

Striphas, Ted “Algorithmic Culture,” European Journal of Cultural Studies 18: 4-5 (August-October 2015), 395–412.

Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue” 

A new kind of weather: Social media now play a key role in collective actionThe Economist (Mar 26, 2016)

List of Links:

Week 2: Algorithms, Cultural Analytics