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

December 2019 • Conference Paper
Carol J Smith

The Human-Machine Teaming (HMT) Framework for Designing Ethical AI Experiences, 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

Publisher:

Software Engineering Institute
DOI (Digital Object Identifier):
10.1184/R1/12119847.v1
Subjects

Abstract

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.