Open AccessCertifiable Trust in Autonomous Systems: Making the Intractable Tangible
Author(s) -
Lyons Joseph B.,
Clark Matthew A.,
Wagner Alan R.,
Schuelke Matthew J.
Publication year - 2017
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v38i3.2717
Subject(s) - transparency (behavior) , trustworthiness , computer science , human–computer interaction , variety (cybernetics) , task (project management) , set (abstract data type) , repertoire , knowledge management , process management , artificial intelligence , systems engineering , engineering , computer security , physics , acoustics , programming language
This article discusses verification and validation (V&V) of autonomous systems, a concept that will prove to be difficult for systems that were designed to execute decision initiative. V&V of such systems should include evaluations of the trustworthiness of the system based on transparency inputs and scenario‐based training. Transparency facets should be used to establish shared awareness and shared intent among the designer, tester, and user of the system. The transparency facets will allow the human to understand the goals, social intent, contextual awareness, task limitations, analytical underpinnings, and team‐based orientation of the system in an attempt to verify its trustworthiness. Scenario‐based training can then be used to validate that programming in a variety of situations that test the behavioral repertoire of the system. This novel method should be used to analyze behavioral adherence to a set of governing principles coded into the system.