Expose Uncertainty, Instill Distrust, Avoid Explanations: Towards Ethical Guidelines for AI

• URL: http://arxiv.org/abs/2112.01281v1
• Date: Mon, 29 Nov 2021 14:53:35 GMT
• Title: Expose Uncertainty, Instill Distrust, Avoid Explanations: Towards Ethical Guidelines for AI
• Authors: Claudio S. Pinhanez
• Abstract summary: I argue that the best way to help humans using AI technology is to make them aware of the intrinsic limitations and problems of AI algorithms. I suggest three ethical guidelines to be used in the presentation of results.
• Score: 3.0534660670547864
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this position paper, I argue that the best way to help and protect humans using AI technology is to make them aware of the intrinsic limitations and problems of AI algorithms. To accomplish this, I suggest three ethical guidelines to be used in the presentation of results, mandating AI systems to expose uncertainty, to instill distrust, and, contrary to traditional views, to avoid explanations. The paper does a preliminary discussion of the guidelines and provides some arguments for their adoption, aiming to start a debate in the community about AI ethics in practice.

Related papers

• Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground [55.2480439325792]
  I argue that efforts to promote responsible and ethical AI can inadvertently contribute to and seemingly legitimize this disregard for established contextual norms. I question the current narrow prioritization in AI ethics of moral innovation over moral preservation.
  arXiv  Detail & Related papers  (2024-12-06T15:36:13Z)
• Beyond principlism: Practical strategies for ethical AI use in research practices [0.0]
  The rapid adoption of generative artificial intelligence in scientific research has outpaced the development of ethical guidelines. Existing approaches offer little practical guidance for addressing ethical challenges of AI in scientific research practices. I propose a user-centered, realism-inspired approach to bridge the gap between abstract principles and day-to-day research practices.
  arXiv  Detail & Related papers  (2024-01-27T03:53:25Z)
• Towards a Feminist Metaethics of AI [0.0]
  I argue that these insufficiencies could be mitigated by developing a research agenda for a feminist metaethics of AI. Applying this perspective to the context of AI, I suggest that a feminist metaethics of AI would examine: (i) the continuity between theory and action in AI ethics; (ii) the real-life effects of AI ethics; (iii) the role and profile of those involved in AI ethics; and (iv) the effects of AI on power relations through methods that pay attention to context, emotions and narrative.
  arXiv  Detail & Related papers  (2023-11-10T13:26:45Z)
• The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies [97.5153823429076]
  The benefits, challenges and drawbacks of AI in this field are reviewed. The use of data augmentation, explainable AI, and the integration of AI with traditional experimental methods are also discussed.
  arXiv  Detail & Related papers  (2022-12-08T23:23:39Z)
• Seamful XAI: Operationalizing Seamful Design in Explainable AI [59.89011292395202]
  Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps. We propose that seamful design can foster AI explainability by revealing sociotechnical and infrastructural mismatches. We explore this process with 43 AI practitioners and real end-users.
  arXiv  Detail & Related papers  (2022-11-12T21:54:05Z)
• Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation [61.77881142275982]
  This interdisciplinary position paper considers various concerns surrounding fairness and discrimination in AI, and discusses how AI regulations address them. We first look at AI and fairness through the lenses of law, (AI) industry, sociotechnology, and (moral) philosophy, and present various perspectives. We identify and propose the roles AI Regulation should take to make the endeavor of the AI Act a success in terms of AI fairness concerns.
  arXiv  Detail & Related papers  (2022-06-08T12:32:08Z)
• Metaethical Perspectives on 'Benchmarking' AI Ethics [81.65697003067841]
  Benchmarks are seen as the cornerstone for measuring technical progress in Artificial Intelligence (AI) research. An increasingly prominent research area in AI is ethics, which currently has no set of benchmarks nor commonly accepted way for measuring the 'ethicality' of an AI system. We argue that it makes more sense to talk about 'values' rather than 'ethics' when considering the possible actions of present and future AI systems.
  arXiv  Detail & Related papers  (2022-04-11T14:36:39Z)
• Cybertrust: From Explainable to Actionable and Interpretable AI (AI2) [58.981120701284816]
  Actionable and Interpretable AI (AI2) will incorporate explicit quantifications and visualizations of user confidence in AI recommendations. It will allow examining and testing of AI system predictions to establish a basis for trust in the systems' decision making.
  arXiv  Detail & Related papers  (2022-01-26T18:53:09Z)
• From the Ground Truth Up: Doing AI Ethics from Practice to Principles [0.0]
  Recent AI ethics has focused on applying abstract principles downward to practice. This paper moves in the other direction. Ethical insights are generated from the lived experiences of AI-designers working on tangible human problems.
  arXiv  Detail & Related papers  (2022-01-05T15:33:33Z)
• Ethics as a service: a pragmatic operationalisation of AI Ethics [1.1083289076967895]
  gap exists between theory of AI ethics principles and the practical design of AI systems. This is the question we seek to address here by exploring why principles and technical translational tools are still needed even if they are limited.
  arXiv  Detail & Related papers  (2021-02-11T21:29:25Z)
• AI virtues -- The missing link in putting AI ethics into practice [0.0]
  The paper defines four basic AI virtues, namely justice, honesty, responsibility and care. It defines two second-order AI virtues, prudence and fortitude, that bolster achieving the basic virtues.
  arXiv  Detail & Related papers  (2020-11-25T14:14:47Z)

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.