Artificial Intelligence Nomenclature Identified From Delphi Study on Key Issues Related to Trust and Barriers to Adoption for Autonomous Systems
The rapid integration of artificial intelligence across traditional research domains has generated an amalgamation of nomenclature. As cross-discipline teams work together on complex machine learning challenges, finding a consensus of basic definitions in the literature is a more fundamental problem...
Saved in:
Main Authors | , , , , , , , , , |
---|---|
Format | Journal Article |
Language | English |
Published |
14.10.2022
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | The rapid integration of artificial intelligence across traditional research
domains has generated an amalgamation of nomenclature. As cross-discipline
teams work together on complex machine learning challenges, finding a consensus
of basic definitions in the literature is a more fundamental problem. As a step
in the Delphi process to define issues with trust and barriers to the adoption
of autonomous systems, our study first collected and ranked the top concerns
from a panel of international experts from the fields of engineering, computer
science, medicine, aerospace, and defence, with experience working with
artificial intelligence. This document presents a summary of the literature
definitions for nomenclature derived from expert feedback. |
---|---|
DOI: | 10.48550/arxiv.2210.09086 |