Designing Trustworthy AI: A Human-Machine Teaming Framework to Guide Development

Abstract

Artificial intelligence (AI) holds great promise to empower us with knowledge and augment our effectiveness. We can and must ensure that we keep humans safe and in control, particularly with regard to government and public sector applications that affect broad populations. How can AI development teams harness the power of AI systems and design them to be valuable to humans? Diverse teams are needed to build trustworthy artificial intelligent systems, and those teams need to coalesce around a shared set of ethics. There are many discussions in the AI field about ethics and trust, but there are few frameworks available for people to use as guidance when creating these systems. The Human-Machine Teaming (HMT) Framework for Designing Ethical AI Experiences described in this paper, when used with a set of technical ethics, will guide AI development teams to create AI systems that are accountable, de-risked, respectful, secure, honest, and usable.

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Document Details

Document Type
Technical Report
Publication Date
Dec 09, 2019
Accession Number
AD1086299

Entities

People

  • Carol J. Smith

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognitive Systems Engineering
  • Commerce
  • Data Rights
  • Data Visualization
  • Education
  • Engineering
  • Human-Computer Interaction
  • Human-Machine Interaction
  • Human-Machine Systems
  • Language
  • Online Communications
  • Quality Of Life
  • Software Development
  • Standards
  • Technical Standards
  • Training

Fields of Study

  • Computer science

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy