AN ARCHITECTURE FOR NORMATIVE, EXPLAINABLE, AND JUSTIFIED AGENCY

Abstract

Before intelligent systems can gain widespread acceptance in various human-machine teams, they must act in accordance with the rules of the teams and they must communicate their decision making to humans in ways that convince team members that they share the same goals. We want intelligent systems to exhibit an ability to justify its decisions. The aim is to develop a computational theory of intelligent systems that can explain their behavior in understandable terms that relate to human social norms. This work will study various architectures for different classes of AI performance.

Document Details

Document Type
DoD Grant Award
Publication Date
Aug 12, 2021
Source ID
FA95502010130

Entities

People

  • Larry John Leifer

Organizations

  • Air Force Office of Scientific Research
  • Stanford University
  • United States Air Force

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Artificial Intelligence
  • Educational Psychology