Delegating Responsibilities to Intelligent Autonomous Systems: Challenges and Benefits
- URL: http://arxiv.org/abs/2411.15147v1
- Date: Wed, 06 Nov 2024 18:40:38 GMT
- Title: Delegating Responsibilities to Intelligent Autonomous Systems: Challenges and Benefits
- Authors: Gordana Dodig-Crnkovic, Gianfranco Basti, Tobias Holstein,
- Abstract summary: As AI systems operate with autonomy and adaptability, the traditional boundaries of moral responsibility in techno-social systems are being challenged.
This paper explores the evolving discourse on the delegation of responsibilities to intelligent autonomous agents and the ethical implications of such practices.
- Score: 1.7205106391379026
- License:
- Abstract: As AI systems increasingly operate with autonomy and adaptability, the traditional boundaries of moral responsibility in techno-social systems are being challenged. This paper explores the evolving discourse on the delegation of responsibilities to intelligent autonomous agents and the ethical implications of such practices. Synthesizing recent developments in AI ethics, including concepts of distributed responsibility and ethical AI by design, the paper proposes a functionalist perspective as a framework. This perspective views moral responsibility not as an individual trait but as a role within a socio-technical system, distributed among human and artificial agents. As an example of 'AI ethical by design,' we present Basti and Vitiello's implementation. They suggest that AI can act as artificial moral agents by learning ethical guidelines and using Deontic Higher-Order Logic to assess decisions ethically. Motivated by the possible speed and scale beyond human supervision and ethical implications, the paper argues for 'AI ethical by design', while acknowledging the distributed, shared, and dynamic nature of responsibility. This functionalist approach offers a practical framework for navigating the complexities of AI ethics in a rapidly evolving technological landscape.
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) - AI Ethics by Design: Implementing Customizable Guardrails for Responsible AI Development [0.0]
We propose a structure that integrates rules, policies, and AI assistants to ensure responsible AI behavior.
Our approach accommodates ethical pluralism, offering a flexible and adaptable solution for the evolving landscape of AI governance.
arXiv Detail & Related papers (2024-11-05T18:38:30Z) - 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) - Towards Responsible AI in Banking: Addressing Bias for Fair
Decision-Making [69.44075077934914]
"Responsible AI" emphasizes the critical nature of addressing biases within the development of a corporate culture.
This thesis is structured around three fundamental pillars: understanding bias, mitigating bias, and accounting for bias.
In line with open-source principles, we have released Bias On Demand and FairView as accessible Python packages.
arXiv Detail & Related papers (2024-01-13T14:07:09Z) - A Review of the Ethics of Artificial Intelligence and its Applications
in the United States [0.0]
The paper highlights the impact AI has in every sector of the US economy and the resultant effect on entities spanning businesses, government, academia, and civil society.
Our discussion explores eleven fundamental 'ethical principles' structured as overarching themes.
These encompass Transparency, Justice, Fairness, Equity, Non- Maleficence, Responsibility, Accountability, Privacy, Beneficence, Freedom, Autonomy, Trust, Dignity, Sustainability, and Solidarity.
arXiv Detail & Related papers (2023-10-09T14:29:00Z) - Beneficent Intelligence: A Capability Approach to Modeling Benefit,
Assistance, and Associated Moral Failures through AI Systems [12.239090962956043]
The prevailing discourse around AI ethics lacks the language and formalism necessary to capture the diverse ethical concerns that emerge when AI systems interact with individuals.
We present a framework formalizing a network of ethical concepts and entitlements necessary for AI systems to confer meaningful benefit or assistance to stakeholders.
arXiv Detail & Related papers (2023-08-01T22:38:14Z) - 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) - 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) - An Ecosystem Approach to Ethical AI and Data Use: Experimental
Reflections [0.0]
This paper offers a methodology to identify the needs of AI practitioners when it comes to confronting and resolving ethical challenges.
We offer a grassroots approach to operational ethics based on dialog and mutualised responsibility.
arXiv Detail & Related papers (2020-12-27T07:41:26Z) - Hacia los Comit\'es de \'Etica en Inteligencia Artificial [68.8204255655161]
It is priority to create the rules and specialized organizations that can oversight the following of such rules.
This work proposes the creation, at the universities, of Ethical Committees or Commissions specialized on Artificial Intelligence.
arXiv Detail & Related papers (2020-02-11T23:48:31Z)
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.