Motivation

Notes of whatever resources that I have looked into on the topic of Conversational Agent.

What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents https://www.youtube.com/watch?v=QrESSP5Jrps

2022 HAI Fall Conference on AI in the Loop: Humans in Charge

Panel I: Designing for AI

https://youtu.be/SbIN4bFl-Es

Unpredictable Black Boxes are Terrible Interfaces

Presenter: Maneesh Agrawala, Standford University

  • A good conceptual model let's users predict how input controls affect the output
  • When the conceptual model is not predictive, users resort to trial-and-error
  • Reason why black box AIs (humans as well) are terrible interfaces
    • cannot predict how input prompt affects output image
    • does not understand the context and expectation of a given word (which can mean a lot of things, at various intensity)
  • How to fix it?
    • have conceptual model based on model of self (human, which we likely understand better)
    • allow conversational interactions to
      • build common ground/shared semantics
      • repair or fix ambiguity/misunderstanding
      • iteractions still required
  • What happens with black box AI
    • conceptual model either is non-existent or incorrect
    • no conversation: each prompt generates new output
    • lots of trial-and-error
  • New research migh want to focus on:
    • establishing common ground/shared semantics
    • repair mechanisms
    • conversation via program code

Measuring what matters for human-AI teams

Presenter: Saleema Amershi, Microsoft

  • Human-centered experiences require human-centered metrics
    • examples of code generation and how to improve the system by using alternative metrics such as edit distance/similarity on top of pass@k suggestion