XXIX Salon: Principles of Language for Autonomous Systems
Salon: Principles of Designing for Autonomous Systems: Communication 11/11/19

1. Premise: language is crucial in newness

  • How the system communicates to users
  • Branding of AI
  • Communicating responsibility and legibility of the system — just because they’re hidden / hard to pinpoint doesn’t mean we can’t do interpretive work / rectify

2. Everyone wants to know the future: hunting for predictions

Subliminal desire for futurism
Next / new psychology
  • The culture of hope
  • Other terms for prediction:
  • Estimate
  • Projection
  • Guess
  • Probability
  • Forecast
  • Segmentation — individual vs. collective
  • What language can we use to identify that we are part of a segment?
  • Personas and archetypes — is this the bias that led here in the first place?
  • Human factors that led to cultural segmentation
  • Articulating the unknowns in your prediction
  • “people like you like”

3. Ethical Issues with False Definitions

  • “My system is going to predict x, and x affects people” — problematic
  • Human filter, bias

4. Avoid the hype (machines can’t be smart)

  • Given: machines can’t be smart
  • Through language, is there a way to help people be thoughtful in creating systems?

5. Gradients of machine autonomy: the use of language in setting expectations

  • Machine work --------------- Human work
  • What’s explicit, what’s insinuated?
  • Agency: single-turn, multi-turn… how many turns before one can lose human agency?
  • How do you tell somebody that their car is going to drive itself? How do you communicate
  • A task is a decision point that progresses the system’s goal
  • Communication → perception = decision (Signal → receiving the signal = result)
  • High stakes ↔ low stakes / human ↔ machine
  • Not a point, a vector
A Model for Types and Levels of Human Interaction with Automation Raja Parasuraman, Thomas B. Sheridan, Fellow, IEEE, and Christopher D. Wickens (Sam Kellogg) (Claire Mitchell)

6. Language in User Interfaces

  • The ambiguity of language when using an autonomous system
  • Translation, literal and nuanced of user intent
  • Accounting for non-binary terms in a binary system
  • Sentiment (volume…) : untranslatable affects