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.
翻译:由于跨纪律小组共同应对复杂的机器学习挑战,在文献中找到基本定义的共识是一个更为根本的问题,作为德尔斐界定信任问题和采用自主系统的障碍的一个步骤,我们的研究首先从工程、计算机科学、医学、航空航天和国防领域的国际专家小组中收集和排列了最关注的问题,并具有从事人工智能工作的经验,本文件概述了专家反馈得出的术语的文献定义。