Guiding the Way: A Comprehensive Examination of AI Guidelines in Global Media

• URL: http://arxiv.org/abs/2405.04706v1
• Date: Tue, 7 May 2024 22:47:56 GMT
• Title: Guiding the Way: A Comprehensive Examination of AI Guidelines in Global Media
• Authors: M. F. de-Lima-Santos, W. N. Yeung, T. Dodds,
• Abstract summary: This study analyzes 37 AI guidelines for media purposes in 17 countries. Our analysis reveals key thematic areas, such as transparency, accountability, fairness, privacy, and the preservation of journalistic values. Results highlight shared principles and best practices that emerge from these guidelines.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: With the increasing adoption of artificial intelligence (AI) technologies in the news industry, media organizations have begun publishing guidelines that aim to promote the responsible, ethical, and unbiased implementation of AI-based technologies. These guidelines are expected to serve journalists and media workers by establishing best practices and a framework that helps them navigate ever-evolving AI tools. Drawing on institutional theory and digital inequality concepts, this study analyzes 37 AI guidelines for media purposes in 17 countries. Our analysis reveals key thematic areas, such as transparency, accountability, fairness, privacy, and the preservation of journalistic values. Results highlight shared principles and best practices that emerge from these guidelines, including the importance of human oversight, explainability of AI systems, disclosure of automated content, and protection of user data. However, the geographical distribution of these guidelines, highlighting the dominance of Western nations, particularly North America and Europe, can further ongoing concerns about power asymmetries in AI adoption and consequently isomorphism outside these regions. Our results may serve as a resource for news organizations, policymakers, and stakeholders looking to navigate the complex AI development toward creating a more inclusive and equitable digital future for the media industry worldwide.

Related papers

• 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)
• Domain-Specific Evaluation Strategies for AI in Journalism [3.2566808526538873]
  We consider different aspects of AI evaluation that can benefit from domain-specific tailoring. In doing so, we lay out a potential framework to guide AI evaluation in journalism.
  arXiv  Detail & Related papers  (2024-03-26T17:47:25Z)
• Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits [54.648819983899614]
  General purpose AI seems to have lowered the barriers for the public to use AI and harness its power. We introduce PARTICIP-AI, a framework for laypeople to speculate and assess AI use cases and their impacts.
  arXiv  Detail & Related papers  (2024-03-21T19:12:37Z)
• Responsible Artificial Intelligence: A Structured Literature Review [0.0]
  The EU has recently issued several publications emphasizing the necessity of trust in AI. This highlights the urgent need for international regulation. This paper introduces a comprehensive and, to our knowledge, the first unified definition of responsible AI.
  arXiv  Detail & Related papers  (2024-03-11T17:01:13Z)
• POLARIS: A framework to guide the development of Trustworthy AI systems [3.02243271391691]
  There is a significant gap between high-level AI ethics principles and low-level concrete practices for AI professionals. We develop a novel holistic framework for Trustworthy AI - designed to bridge the gap between theory and practice. Our goal is to empower AI professionals to confidently navigate the ethical dimensions of Trustworthy AI.
  arXiv  Detail & Related papers  (2024-02-08T01:05:16Z)
• 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)
• FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare [73.78776682247187]
  Concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare.
  arXiv  Detail & Related papers  (2023-08-11T10:49:05Z)
• Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance [0.0]
  This paper conducts a meta-analysis of 200 governance policies and ethical guidelines for AI usage published by public bodies, academic institutions, private companies, and civil society organizations worldwide. We identify at least 17 resonating principles prevalent in the policies and guidelines of our dataset, released as an open-source database and tool. We present the limitations of performing a global scale analysis study paired with a critical analysis of our findings, presenting areas of consensus that should be incorporated into future regulatory efforts.
  arXiv  Detail & Related papers  (2022-06-23T18:03:04Z)
• 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)
• The Short Anthropological Guide to the Study of Ethical AI [91.3755431537592]
  Short guide serves as both an introduction to AI ethics and social science and anthropological perspectives on the development of AI. Aims to provide those unfamiliar with the field with an insight into the societal impact of AI systems and how, in turn, these systems can lead us to rethink how our world operates.
  arXiv  Detail & Related papers  (2020-10-07T12:25:03Z)

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.