Jun 2019· arXiv.org· Vol abs/1906.12307· 2 citations· 23 references
Computer Science
TL;DR
This paper provides a baseline for ethics in AI based software development by reporting results from an industrial multiple case study on AI systems development in the health care sector, and explores the current state of practice out on the field in the absence of formal methods and tools for ethically aligned design.
Abstract
Solutions in artificial intelligence (AI) are becoming increasingly widespread in system development endeavors. As the AI systems affect various stakeholders due to their unique nature, the growing influence of these systems calls for eth-ical considerations. Academic discussion and practical examples of autonomous system failures have highlighted the need for implementing ethics in software development. However, research on methods and tools for implementing ethics into AI system design and development in practice is still lacking. This paper be-gins to address this focal problem by providing a baseline for ethics in AI based software development. This is achieved by reporting results from an industrial multiple case study on AI systems development in the health care sector. In the context of this study, ethics were perceived as interplay of transparency, re-sponsibility and accountability, upon which research model is outlined. Through these cases, we explore the current state of practice out on the field in the ab-sence of formal methods and tools for ethically aligned design. Based on our data, we discuss the current state of practice and outline existing good practic-es, as well as suggest future research directions in the area.
A comprehensive model for integrating ethical standards into the phases of the Software Development Life Cycle (SDLC) is proposed, founded on the pillars of fairness, transparency, accountability, and sustainability, offering practical recommendations aimed at developers, organizations, and policymakers.
A. Alaswad· Al-Farooq Journal of Science...· 0 citations
This paper proposes the ARCHON framework, a set of ten requirements derived from the technical architecture of AI systems, to facilitate ethical compliance of scientific research for experts and practicioners engaging in roles such as proposal evaluators, project officers, ethics board members, or research administrato...
Jesus Manuel Benitez Baleato· Open Research Europe· 0 citations
Three steps of the ENACT methodology are described and details three steps of the ENACT methodology and its potential and limitations for qualitative ethical risk assessment of AI in organisational settings are discussed.
N. Murashova, Leonora Onarheim Bergsjø, Heidi Dahl et al.· Nordic Machine Intelligence· 0 citations
The canvas presented is applicable to all public administrations within the European Union who wish to adopt AI in their operations, as it references to core European legislation such as General Data Protection Regulation, AI Act, Data Act, and Data Governance Act.
Riccardo Nanni, P. G. Bizzaro, Albana Celepija et al.· Data & Policy· 0 citations
The findings indicate that AI integration in research ethics oversight is shaped not only by technological feasibility but by institutional concerns regarding responsibility, legitimacy, and deliberative authority.
Daniel Wang, Marta Guix Arnau, Cristina Llop Julià et al.· Research Ethics· 0 citations
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
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