An empirical study on the current state of practice in artificial intelligence ethics is conducted by means of a multiple case study of five case companies, which indicates a gap between research and practice in the area.
Abstract
Progress in the field of artificial intelligence has been accelerating rapidly in the past two decades. Various autonomous systems from purely digital ones to autonomous vehicles are being developed and deployed out on the field. As these systems exert a growing impact on society, ethics in relation to artificial intelligence and autonomous systems have recently seen growing attention among the academia. However, the current literature on the topic has focused almost exclusively on theory and more specifically on conceptualization in the area. To widen the body of knowledge in the area, we conduct an empirical study on the current state of practice in artificial intelligence ethics. We do so by means of a multiple case study of five case companies, the results of which indicate a gap between research and practice in the area. Based on our findings we propose ways to tackle the gap.
Autonomous systems (ASs) will eventually make many decisions in moral dilemmas without human oversight. How humans will respond to the presence of ASs and whether humans will accept them will crucially depend on how ASs’ decisions are programmed. For example, how moral dilemmas are approached in the programming of au...
Anja Bodenschatz, Matthias W. Uhl, G. Walkowitz· AI & SOCIETY· 0 citations
The analysis indicates that the pragmatist narrative of the sociotechnical systems approach emphasizes the real-world functioning of AI and its societal impacts.
Mohammad-Ali Ashouri-Kisomi, M. Parvizi, S. Momeni· 0 citations
This paper aims to draw out ideas from recent work in metanormative theory that can be useful for designing artificial moral and value-aligned agents and examine the RL architecture through the lens of these ideas.
The assessments indicate that the European Union's desire to compete with the United States and China in the global artificial intelligence race creates a context that may make prioritizing ethical principles difficult.
Tolgay Ercan· Düzce Üniversitesi Sosyal Bi...· 0 citations
The paper highlights challenges such as value ambiguity, contextual differences, and technical limitations in encoding ethics and proposes a mixed-method approach involving stakeholder analysis, value elicitation, algorithm auditing, and ethical performance evaluation.
Shalini Gupta· International Journal of Inn...· 0 citations
It is proposed to rethink social and tech ethics from the standpoint of a renewed attention to the constitutions of these economic actors within the capitalist system.
J. Schulz, Laura Robinson, Katia Moles· International journal of kno...· 0 citations
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Known for his clear and elegant writing style, Bertsekas shaped fields from control and optimization to large-scale computation and artificial intelligence.