Shaping New Norms for AI
- URL: http://arxiv.org/abs/2307.08564v2
- Date: Thu, 27 Jun 2024 17:18:10 GMT
- Title: Shaping New Norms for AI
- Authors: Andrea Baronchelli,
- Abstract summary: Article aims to offer readers interpretive tools to understand society's response to the growing pervasiveness of AI.
An outlook on how AI could influence the formation of future social norms emphasises the importance for open societies to anchor their formal deliberation process in an open, inclusive, and transparent public discourse.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: As Artificial Intelligence (AI) becomes increasingly integrated into our lives, the need for new norms is urgent. However, AI evolves at a much faster pace than the characteristic time of norm formation, posing an unprecedented challenge to our societies. This paper examines possible criticalities of the processes of norm formation surrounding AI. Thus, it focuses on how new norms can be established, rather than on what these norms should be. It distinguishes different scenarios based on the centralisation or decentralisation of the norm formation process, analysing the cases where new norms are shaped by formal authorities, informal institutions, or emerge spontaneously in a bottom-up fashion. On the latter point, the paper reports a conversation with ChatGPT in which the LLM discusses some of the emerging norms it has observed. Far from seeking exhaustiveness, this article aims to offer readers interpretive tools to understand society's response to the growing pervasiveness of AI. An outlook on how AI could influence the formation of future social norms emphasises the importance for open societies to anchor their formal deliberation process in an open, inclusive, and transparent public discourse.
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) - Using AI Alignment Theory to understand the potential pitfalls of regulatory frameworks [55.2480439325792]
This paper critically examines the European Union's Artificial Intelligence Act (EU AI Act)
Uses insights from Alignment Theory (AT) research, which focuses on the potential pitfalls of technical alignment in Artificial Intelligence.
As we apply these concepts to the EU AI Act, we uncover potential vulnerabilities and areas for improvement in the regulation.
arXiv Detail & Related papers (2024-10-10T17:38:38Z) - The Call for Socially Aware Language Technologies [94.6762219597438]
We argue that many of these issues share a common core: a lack of awareness of the factors, context, and implications of the social environment in which NLP operates.
We argue that substantial challenges remain for NLP to develop social awareness and that we are just at the beginning of a new era for the field.
arXiv Detail & Related papers (2024-05-03T18:12:39Z) - 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) - 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) - Learning Norms via Natural Language Teachings [0.0]
This paper introduces and demonstrates a computational approach to learning norms from natural language text.
It provides a foundation for everyday people to train AI systems about social norms.
arXiv Detail & Related papers (2022-01-20T22:09:42Z) - Toward a Theory of Justice for Artificial Intelligence [2.28438857884398]
It holds that the basic structure of society should be understood as a composite of socio-technical systems.
As a consequence, egalitarian norms of justice apply to the technology when it is deployed in these contexts.
arXiv Detail & Related papers (2021-10-27T13:23:38Z) - Norm Identification through Plan Recognition [22.387008072671005]
Societal rules aim to provide a degree of behavioural stability to multi-agent societies.
Many implementations of normative systems assume various combinations of the following assumptions.
We develop a norm identification mechanism that uses a combination of parsing-based plan recognition and Hierarchical Task Network (HTN) planning mechanisms.
arXiv Detail & Related papers (2020-10-06T11:18:52Z) - 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.