Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness
Metrics
- URL: http://arxiv.org/abs/2311.05227v2
- Date: Mon, 26 Feb 2024 21:22:51 GMT
- Title: Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness
Metrics
- Authors: Carlos Mougan, Joshua Brand
- Abstract summary: Deontological ethics, specifically understood through Immanuel Kant, provides a moral framework that emphasizes the importance of duties and principles.
This paper explores the compatibility of a Kantian deontological framework in fairness metrics, part of the AI alignment field.
- Score: 4.373803477995854
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Deontological ethics, specifically understood through Immanuel Kant, provides
a moral framework that emphasizes the importance of duties and principles,
rather than the consequences of action. Understanding that despite the
prominence of deontology, it is currently an overlooked approach in fairness
metrics, this paper explores the compatibility of a Kantian deontological
framework in fairness metrics, part of the AI alignment field. We revisit
Kant's critique of utilitarianism, which is the primary approach in AI fairness
metrics and argue that fairness principles should align with the Kantian
deontological framework. By integrating Kantian ethics into AI alignment, we
not only bring in a widely-accepted prominent moral theory but also strive for
a more morally grounded AI landscape that better balances outcomes and
procedures in pursuit of fairness and justice.
Related papers
- Quelle {é}thique pour quelle IA ? [0.0]
This study proposes an analysis of the different types of ethical approaches involved in the ethics of AI.
The author introduces to the contemporary need for and meaning of ethics, distinguishes it from other registers of normativities and underlines its inadequacy to formalization.
The study concludes with a reflection on the reasons why a human ethics of AI based on a pragmatic practice of contextual ethics remains necessary and irreducible to any formalization or automated treatment of the ethical questions that arise for humans.
arXiv Detail & Related papers (2024-05-21T08:13:02Z) - Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? [78.3738172874685]
Making moral judgments is an essential step toward developing ethical AI systems.
Prevalent approaches are mostly implemented in a bottom-up manner, which uses a large set of annotated data to train models based on crowd-sourced opinions about morality.
This work proposes a flexible top-down framework to steer (Large) Language Models (LMs) to perform moral reasoning with well-established moral theories from interdisciplinary research.
arXiv Detail & Related papers (2023-08-29T15:57:32Z) - Factoring the Matrix of Domination: A Critical Review and Reimagination
of Intersectionality in AI Fairness [55.037030060643126]
Intersectionality is a critical framework that allows us to examine how social inequalities persist.
We argue that adopting intersectionality as an analytical framework is pivotal to effectively operationalizing fairness.
arXiv Detail & Related papers (2023-03-16T21:02:09Z) - Macro Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions [1.864621482724548]
We develop a taxonomy of 21 normative ethical principles which can be operationalised in AI.
We envision this taxonomy will facilitate the development of methodologies to incorporate normative ethical principles in reasoning capacities of responsible AI systems.
arXiv Detail & Related papers (2022-08-12T08:48:16Z) - 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) - Designing a Future Worth Wanting: Applying Virtue Ethics to HCI [11.117357750374035]
Out of the three major approaches to ethics, virtue ethics is uniquely well suited as a moral guide in the digital age.
It focuses on the traits, situations and actions of moral agents, rather than on rules (as in deontology) or outcomes (consequentialism)
arXiv Detail & Related papers (2022-04-05T14:18:35Z) - 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) - Case Study: Deontological Ethics in NLP [119.53038547411062]
We study one ethical theory, namely deontological ethics, from the perspective of NLP.
In particular, we focus on the generalization principle and the respect for autonomy through informed consent.
We provide four case studies to demonstrate how these principles can be used with NLP systems.
arXiv Detail & Related papers (2020-10-09T16:04:51Z) - An Impact Model of AI on the Principles of Justice: Encompassing the
Autonomous Levels of AI Legal Reasoning [0.0]
It is argued that the infusion of AI into existing and future legal activities and the judicial structure needs to be undertaken by mindfully observing an alignment with the core principles of justice.
By examining the principles of justice across the Levels of Autonomy (LoA) of AI Legal Reasoning, the case is made that there is an ongoing tension underlying the efforts to develop and deploy AI.
arXiv Detail & Related papers (2020-08-26T22:56:41Z) - 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.