A Capability Approach to AI Ethics

• URL: http://arxiv.org/abs/2502.03469v1
• Date: Fri, 10 Jan 2025 12:08:21 GMT
• Title: A Capability Approach to AI Ethics
• Authors: Emanuele Ratti, Mark Graves,
• Abstract summary: We show that conceptualizing AI ethics through the capability approach has two main advantages for AI ethics as a discipline.<n>First, it helps clarify the ethical dimension of AI tools.<n>Second, it provides guidance to implementing ethical considerations within the design of AI tools.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a conceptualization and implementation of AI ethics via the capability approach. We aim to show that conceptualizing AI ethics through the capability approach has two main advantages for AI ethics as a discipline. First, it helps clarify the ethical dimension of AI tools. Second, it provides guidance to implementing ethical considerations within the design of AI tools. We illustrate these advantages in the context of AI tools in medicine, by showing how ethics-based auditing of AI tools in medicine can greatly benefit from our capability-based approach.

Related papers

• Making Power Explicable in AI: Analyzing, Understanding, and Redirecting Power to Operationalize Ethics in AI Technical Practice [12.114215545709818]
  We first describe the phenomenon (i.e., the "symptoms") of ineffective implementation of AI ethics in explainable AI.<n>From the "symptoms", we diagnose the root cause (i.e., the "disease") being the dysfunction and imbalance of power structures in the sociotechnical system of AI.<n>Based on the understanding of power mechanisms, we propose three interventional recommendations to tackle the root cause.
  arXiv  Detail & Related papers  (2025-10-12T13:09:22Z)
• AI as IA: The use and abuse of artificial intelligence (AI) for human enhancement through intellectual augmentation (IA) [45.88028371034407]
  This paper offers an overview of the prospects and ethics of using AI to achieve human enhancement.<n>We discuss potential ethical problems, namely inadequate performance, safety, coercion and manipulation, privacy, cognitive liberty, authenticity, and fairness.<n>We conclude that while there are very significant technical hurdles to real human enhancement through AI, and significant ethical problems, there are also significant benefits that may realistically be achieved.
  arXiv  Detail & Related papers  (2025-08-18T09:39:11Z)
• Ethics through the Facets of Artificial Intelligence [0.0]
  We argue that concerns stem from a blurred understanding of AI, how it can be used, and how it has been interpreted in society.<n>We propose a framework for the ethical assessment of the use of AI.
  arXiv  Detail & Related papers  (2025-07-22T21:21:37Z)
• Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence [0.08192907805418582]
  This study attempts to identify the major ethical principles influencing the utility performance of AI at different technological levels. Justice, privacy, bias, lack of regulations, risks, and interpretability are the most important principles to consider for ethical AI. We propose a new utilitarian ethics-based theoretical framework for designing ethical AI for the healthcare domain.
  arXiv  Detail & Related papers  (2023-09-26T02:10:58Z)
• 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)
• Ethics in AI through the Practitioner's View: A Grounded Theory Literature Review [12.941478155592502]
  In recent years, numerous incidents have raised the profile of ethical issues in AI development and led to public concerns about the proliferation of AI technology in our everyday lives. We conducted a grounded theory literature review (GTLR) of 38 primary empirical studies that included AI practitioners' views on ethics in AI. We present a taxonomy of ethics in AI from practitioners' viewpoints to assist AI practitioners in identifying and understanding the different aspects of AI ethics.
  arXiv  Detail & Related papers  (2022-06-20T00:28:51Z)
• 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)
• A Deployment Model to Extend Ethically Aligned AI Implementation Method ECCOLA [5.28595286827031]
  This study aims to extend ECCOLA with a deployment model to drive the adoption of ECCOLA. The model includes simple metrics to facilitate the communication of ethical gaps or outcomes of ethical AI development.
  arXiv  Detail & Related papers  (2021-10-12T12:22:34Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)
• 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)
• 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)
• On the Morality of Artificial Intelligence [154.69452301122175]
  We propose conceptual and practical principles and guidelines for Machine Learning research and deployment. We insist on concrete actions that can be taken by practitioners to pursue a more ethical and moral practice of ML aimed at using AI for social good.
  arXiv  Detail & Related papers  (2019-12-26T23:06:54Z)

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.