Lecture 8 - Chun, McIlwain, Benjamin,

Question 1

Queering homophily – wendy chun:

Answer 1

• Principle of homophily: axiom that similarity breeds connection
• Rise and importance of network science on contemporary digital cultures
• Frames of reference: cybernetic feedback, behavioral psychology, postmodern condition, and neoliberalism (control of populations)
• Strong connection to Lippold: in soft biopower/categorization
• General issue: different modes of abstraction, detached from any reality: dramatic simplification of real world phenomena

Question 2

Status quo of the internet

Answer 2

• Rather than endless difference free utopia, internet becomes echo chamber
• Digital has changed situation: not as much contact with different people with different opinions, because people can communicate with others with the same opinion more easily
• Control societies: state surveillance, tracking, every action is captured
• Big data analytics: separations from real world are perpetuated by big data analytics but along, networks perpetuate identity via default variables and axioms

Question 3

Definition of networks according to Chun

Answer 3

not unstructured masses nor endless rhizomes that cannot be cut or traced. Because of their complexities, noisiness and persistent inequalities foster techniques to manage prune and predict

Question 4

Pattern discrimination

Answer 4

homophily fuels pattern discrimination (think also bateson)
Homophily launders hate into collective love: a transformation that grounds modern white supremacy

Question 5

pattern discrimination further

Answer 5

• Actions are constituted as we perform them
• Problem is how we utilize patterns to discriminate in ways that reflect our previous prejudices
• Link to Benjamin: bias by design and built into technology

Question 6

Algorithmic response to bias

Answer 6

• Data discrimination  problematic categorizations of bias correction
• Differences are already imbedded in other, less crude categories
• Algorithm perpetuates discrimination it finds: algorithms aggregate, they do not think, therefore, if discrimination is to be found on the internet, it can be deployed by algorithms

Question 7

Pattern discrimination causes shift

Answer 7

Shift from narratives to bodily actions: Big Data devalues human language by privy bodily actions (clicking mouse)

Question 8

Challenge for us:

Answer 8

• How do we know what matters?: we need to realize that gap between prediction and reality is space for action
• Predictions can be self-cancelling as well as self-fulfilling
• In order to positively use these features, we have to analyze network sciences

Question 9

What is network science (chun)

Answer 9

• Quantative social sciences + physical and computer sciences to bypass humanities/media studies
• Mapping of world in nodes and edges (simplification)
• Operates by: deciding what is node and edge, how they connect, formalization (mathematical theories of network)

Question 10

Non-normativity of network sciences

Answer 10

• Networks connect us across scales which are not identical
• Consequences:
  o Global concerns impact local decisions
  o Triadic closure: in commonness, homophilious harmony and consensus

Question 11

Hate

Answer 11

• To create different world, we need to question default assumptions about homophily
• Love of the same is never innocent
• Hate transforms the particular into the general: it transforms individuals into types so they become a common threat
• Hate makes a strong bond that defines a core against periphery

Question 12

Ruha Benjamin’s new jim code:

Answer 12

employment of new technologies that reflect/reproduce existing inequities but that are promoted/perceived as more objective/progressive than the previous discrimination.

Question 13

Problematic of new jim code

Answer 13

• Rather than overcoming cycle of inequity, technical fixes too often reinforce and deepen the status quo
• Tech designers encode judgement into system but claim technology and encoding is neutral, they blame user
• Code is not just data, but the way in which a sense is extracted from it (allows bias)

Question 14

Technical fix

Answer 14

• Always a euphemism, seems better but is not
• Discrimination just goes more under the radar

Question 15

The possibility/promise of technical neutrality:

Answer 15

• Human decision makers are biased: but at least there is a diversity of biases
• Neutrality is no safeguard against discriminatory design

Question 16

Consequences of new jim code

Answer 16

• Neglect of ongoing inequity
• Technical fixes justify the biases that are already there
• Reproduction of old biases in new ways: not discriminate but to ‘better serve’ minority groups

Question 17

Technological redlining

Answer 17

by fixing group identities as stable features, difference is codified in digital structures of everyday life

Question 18

Marketing difference:

Answer 18

• Pleasure of devouring difference
• By this we take part in this difference
• Just reproducing inequality in ways that it can be consumed by the dominant culture (in the name of equality)

Question 19

Discriminatory design

Answer 19

• Regimes of personalization are still binary options (not as personal as they seem)
• We need to unsettle such binaries in order to move forward