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215: Gathering Data in Machine Learning with Abeba Birhane

01:41 - Descartes was wrong: ‘a person is a person through other persons’

13:59 - Predicting How People Behave and Act via Machine Learning is Ethically Flawed

34:21 - Examining Machine Learning Models and Data

“When you get rid of what you don’t want, you do not necessarily get what you do want and you may get something you want a lot less. It is that simple…..anyone that ever watches television knows that!” – Russell L. Ackoff

  • “Scoring” People Perpetuates Stereotypes
  • Acurracy Confirms Bias

50:09 - Important Ideosyncracies and Contaminating Factors

  • Seeing and appreciating the potential to be different in every person in every situation.
  • The ability to tease apart existing cultural ideas around identity and humanity.
  • Taking concepts from different but related fields and seeing their connectedness and bringing them together into a whole that is more than the sum of their parts.
  • Seeing consequences that don’t belong to any one cause.

Reflections:

Mando: Cartesian thinking and worldview is embedded in us.

Avdi: “Contaminating factors.”

“Dive into yourself to find yourself.”

Rein: Jainism has gotten this right for centuries.

  • The Elephant and the Blindfolded Men Parable
  • The Theory of Conditioned Predication or Contigency
  • The Theory of Partial Standpoints

Jessica: Giving the Cartesian program credit for what it’s good for: using science as a way to break things down into parts and studying them deeply; we’ve learned a lot.

Abeba: It’s not all bad. BUT, we forget to put the pieces back together and acknowledge reality.

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Special Guest: Abeba Birhane.

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