A Methodology for Ethics-by-Design AI Systems: Dealing with Human Value Conflicts

• URL: http://arxiv.org/abs/2010.07610v1
• Date: Thu, 15 Oct 2020 09:14:00 GMT
• Title: A Methodology for Ethics-by-Design AI Systems: Dealing with Human Value Conflicts
• Authors: Fabrice Muhlenbach
• Abstract summary: The introduction of artificial intelligence into activities traditionally carried out by human beings produces brutal changes. This paper is about designing and implementing models of ethical behaviors in AI-based systems. It presents a methodology for designing systems that take ethical aspects into account at an early stage while finding an innovative solution to prevent human values from being affected.
• Score: 0.030458514384586396
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The introduction of artificial intelligence into activities traditionally carried out by human beings produces brutal changes. This is not without consequences for human values. This paper is about designing and implementing models of ethical behaviors in AI-based systems, and more specifically it presents a methodology for designing systems that take ethical aspects into account at an early stage while finding an innovative solution to prevent human values from being affected. Two case studies where AI-based innovations complement economic and social proposals with this methodology are presented: one in the field of culture and operated by a private company, the other in the field of scientific research and supported by a state organization.

Related papers

• Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions [101.67121669727354]
  Recent advancements in AI have highlighted the importance of guiding AI systems towards the intended goals, ethical principles, and values of individuals and groups, a concept broadly recognized as alignment. The lack of clarified definitions and scopes of human-AI alignment poses a significant obstacle, hampering collaborative efforts across research domains to achieve this alignment. We introduce a systematic review of over 400 papers published between 2019 and January 2024, spanning multiple domains such as Human-Computer Interaction (HCI), Natural Language Processing (NLP), Machine Learning (ML)
  arXiv  Detail & Related papers  (2024-06-13T16:03:25Z)
• Towards an Ethical and Inclusive Implementation of Artificial Intelligence in Organizations: A Multidimensional Framework [0.0]
  This article analyzes the impact of artificial intelligence on contemporary society and the importance of adopting an ethical approach to its development and implementation within organizations. Various actors, such as governments, academics, and civil society, can play a role in shaping the development of AI aligned with human and social values.
  arXiv  Detail & Related papers  (2024-05-02T19:43:51Z)
• Hacia una implementación ética e inclusiva de la Inteligencia Artificial en las organizaciones: un marco multidimensional [0.0]
  The article analyzes the impact of artificial intelligence on contemporary society and the importance of adopting an ethical approach to its development and implementation within organizations. Various actors, such as governments, academics and civil society, can play a role in shaping the development of AI aligned with human and social values.
  arXiv  Detail & Related papers  (2024-04-30T22:11:05Z)
• Modelling Human Values for AI Reasoning [2.320648715016106]
  We detail a formal model of human values for their explicit computational representation. We show how this model can provide the foundational apparatus for AI-based reasoning over values. We propose a roadmap for future integrated, and interdisciplinary, research into human values in AI.
  arXiv  Detail & Related papers  (2024-02-09T12:08:49Z)
• Unpacking the Ethical Value Alignment in Big Models [46.560886177083084]
  This paper provides an overview of the risks and challenges associated with big models, surveys existing AI ethics guidelines, and examines the ethical implications arising from the limitations of these models. We introduce a novel conceptual paradigm for aligning the ethical values of big models and discuss promising research directions for alignment criteria, evaluation, and method.
  arXiv  Detail & Related papers  (2023-10-26T16:45:40Z)
• Human-AI Coevolution [48.74579595505374]
  Coevolution AI is a process in which humans and AI algorithms continuously influence each other. This paper introduces Coevolution AI as the cornerstone for a new field of study at the intersection between AI and complexity science.
  arXiv  Detail & Related papers  (2023-06-23T18:10:54Z)
• A computational framework of human values for ethical AI [3.5027291542274357]
  values provide a means to engineer ethical AI. No formal, computational definition of values has yet been proposed. We address this through a formal conceptual framework rooted in the social sciences.
  arXiv  Detail & Related papers  (2023-05-04T11:35:41Z)
• An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
  This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
  arXiv  Detail & Related papers  (2021-05-07T12:01:31Z)
• The Short Anthropological Guide to the Study of Ethical AI [91.3755431537592]
  Short guide serves as both an introduction to AI ethics and social science and anthropological perspectives on the development of AI. Aims to provide those unfamiliar with the field with an insight into the societal impact of AI systems and how, in turn, these systems can lead us to rethink how our world operates.
  arXiv  Detail & Related papers  (2020-10-07T12:25:03Z)
• Implementing AI Ethics in Practice: An Empirical Evaluation of the RESOLVEDD Strategy [6.7298812735467095]
  We empirically evaluate an existing method from the field of business ethics, the RESOLVEDD strategy, in the context of ethical system development. One of our key findings is that, even though the use of the ethical method was forced upon the participants, its utilization nonetheless facilitated of ethical consideration in the projects.
  arXiv  Detail & Related papers  (2020-04-21T17:58:53Z)
• Learning from Learning Machines: Optimisation, Rules, and Social Norms [91.3755431537592]
  It appears that the area of AI that is most analogous to the behaviour of economic entities is that of morally good decision-making. Recent successes of deep learning for AI suggest that more implicit specifications work better than explicit ones for solving such problems.
  arXiv  Detail & Related papers  (2019-12-29T17:42:06Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.