Parrot or Raven? Explorations with GPT-3 & Peering into the OpenAI Black Box

Presenter's Name(s)

Kathryn CramerFollow

Abstract

This project explores qualitative methods for analyzing block-box artificial intelligence systems. To understand the AI system GPT-3, the researcher uses interviewing techniques to answer research questions such as:

• Why is GPT-3 so bad at facts?

• How can there be empathy with no empathizer?

• Is GPT-3 merely a “Stochastic Parrot?” Or is it a tool user with capacities beyond what is imagined by the Stochastic Parrot framework?

The researcher infers the existence of a Multi-Agent Reinforcement Learning System servicing user queries. Negative reinforcement from this learning system seems to collide problematically with artificial empathy.

Primary Faculty Mentor Name

Peter Sheridan Dodds

Secondary Mentor Name

Chris Danforth

Status

Graduate

Student College

College of Engineering and Mathematical Sciences

Program/Major

Complex Systems

Primary Research Category

Engineering & Physical Sciences

Secondary Research Category

Arts & Humanities

Tertiary Research Category

Social Sciences

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Parrot or Raven? Explorations with GPT-3 & Peering into the OpenAI Black Box

This project explores qualitative methods for analyzing block-box artificial intelligence systems. To understand the AI system GPT-3, the researcher uses interviewing techniques to answer research questions such as:

• Why is GPT-3 so bad at facts?

• How can there be empathy with no empathizer?

• Is GPT-3 merely a “Stochastic Parrot?” Or is it a tool user with capacities beyond what is imagined by the Stochastic Parrot framework?

The researcher infers the existence of a Multi-Agent Reinforcement Learning System servicing user queries. Negative reinforcement from this learning system seems to collide problematically with artificial empathy.