2014/10/16 12:00 Gabi Schaffzin and Zach Kaiser, “Designing For Our New Scale”, #RSD3

@GabiSchaffzin and @zacharykaiser, first day presentation at #RSD3 Relating Systems Thinking and Design 3, in Theories and Methods track, at AHO, Oslo, Norway, moderated by @redesign

This digest was created in real-time during the meeting, based on the speaker’s presentation(s) and comments from the audience. The content should not be viewed as an official transcript of the meeting, but only as an interpretation by a single individual. Lapses, grammatical errors, and typing mistakes may not have been corrected. Questions about content should be directed to the originator. The digest has been made available for purposes of scholarship by David Ing.

Program is at http://systemic-design.net/rsd3-2014/program/


Gabi is at Massachusetts College of Art; Zach is at Michigan State U.

Will present a provocation

  • What does it mean to design for scale?

A critical theoretical frame

Growth hacking:  a subgenre of value creation

  • Some based in Boston
  • Startups are design for astronomical growth, e.g. 30% month over month
  • Growth as typical business executives not enough now
  • Attitude and ideology brings up unquestioned value of growth

Historical critiques of economic growth isn’t new

  • Meadows, Limits to Growth
  • Schumacher, Small is Beautiful
  • Can such causes be effective for long, or do they have their own seeds of construction
  • Economic growth will lead to bottlenecks
  • Schumacher is being read by startups, recreating in cloud, away from materiality

Correlation between growth and innovation

  • Big data
  • Algorithms and increasing computational power
  • Platform technologies

Value in intangible, scalability has a new importance and meaning

  • Dynamic scalable

Met with a small internal group at an insurance company

  • New developments changing ways that consumer were interacting:  platforms, big data and algorithms
  • Insurance is more complicated than plane travel
  • Computation has become more sophisticated, can analyze how customers are similar

Web page:  coverhound, enter auto insurance information

  • In practice, really complicated
  • Data
  • Signing with Facebook or Google Plus
  • Similar people, or to some connected people
  • Of a thousand data points, fill in a few

Can gather data, crunch to spit out inferences

Problems:

  • Underlying ideologies, e.g. APIs, more than just neutral or true
  • Ideologies impacting technologies and world

Platforms enable access to information, while distancing self

  • API has to submit to metrics that designer of platforms choose, e.g. Youtube gives most popular videos, not least popular

Problems with big data:

  • Apophenia, finding patterns where none exist
  • Unequal access
  • Myth of objectivity: some have non-IRB-approved research

Algorithms

  • Algorithms communicate with one another, leaving humans of bystanders, e.g. $23.6 million book listing on Amazon
  • For insurance, it might not matter that much
  • If we accept terms and conditions in exchange for results, not just a service
  • Everything measurable?

Big data and positivism

  • Turns us away from thinking about wickedness in problems

As designers, as we grapple with platforms, algorithms and big data, what can we do?

  • Make art!
  • Fuller and Goffey, Evil Media — the least systemic work:  affectlessness

Counter afflectlessness though affect, i.e. art

  • Make things visible and tangible

Whisper:  a project where everything is anticipated, making inferences


Sketchnote of presentation by Gabi Schaffzin and Zach Kaiser, drawn by Patricia Kambitsch at https://twitter.com/playthink/status/522864791098912768

Sketchnote of presentation by @gabischaffzin and @zacharykaiser, drawn by Patricia Kambitsch