Discourse monitor
How the monitored publications were assessed
Discourse valence across every scored item: what the sampled sources published and how independent models read it. It is not a measure of public opinion, not a measure of the state of the world, and article volume is not agreement.
Mean discourse valence per day · misinformation · last 30 days
Discourse valence, window mean
-41
Adverse
55 items · range -79 to +50
-100
-50
0
+50
+100
-41
Adverse readingFavourable reading
55 items scored in this window
- Knowing Is Not Telling: Identity Ossification in LLM Representations of Trans-border Communities
- Auditing AI-Washing in German Startups: A Mixed-Methods Study of Marketing Claims and Perceptions
- When LLMs Manipulate: Measuring Behavioral, Social, and Temporal Effects
- AI threatens democracy. But we are not powerless: here’s how to fight back | Carine Fouteau
- I Used AI to Fake a Scientific Paper. Here’s What Happened
- LLM Recommenders Produce Demographic Inequality Through Content Preferences
- AI is stealing Indigenous Australian art and churning out ‘Temu slop’, artist says
- AI ‘deepfakes’ give US political attack ads a new twist
- Generative AI Produces and Transmits Beauty Bias
- What do AI chatbots do after users decline therapeutic redirection for suicide thoughts?
- AI-driven disinformation running rampant on social media before US midterms, experts warn
- Automated Disinformation and Malicious AI Swarms: Risks for Democracy and Development in Africa
- Lawsuit: Man introduced his wife to ChatGPT. She used it to plan his murder.
- Tool and target: US law enforcement grapple with AI-enabled terrorism and anti-tech extremism
- A.I. and Its Dangers Are Embedded In the Midterm Elections
- How A.I. Is Making It Easier Than Ever to Microtarget Voters
- Adversarial Attacks Reveal Divergent Deception Competence in Humans and Generative Language Models
- The focus on AI safety disasters ignores everyday harms
- ‘A serious failure’: CPS prosecutor cites imaginary case to high court after AI search
- “Does Meta think we can’t read?” Meta abandons sketchy commercial terms update.
- How Generative AI Redefines Personalization and Diversity in the Newsroom
- The Popular Get More Popular: Auditing Brand Bias in Generative Search
- Scare campaigns: Victoria’s major parties trade blows over AI-generated videos of leaders in election ads
- Palantir AI tech unused or little used by 29 NHS trusts said to be benefiting from it
- Language Non-Invariance in the Ideological Evaluation of Large Language Models
- AI bots flooded 2023 UK government consultation on disposable vapes ban
- AI-hallucinated citations should be treated as research misconduct
- In a rush to lure AI companies, the Australian government risks undoing a creative ecosystem that has taken decades to build | Dan Guthrie
- Opposition deepfake video sparks outrage in Spain ahead of election
- Meta Ordered to Pay $25 Billion for Deceiving Users on Privacy
- Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?
- We need to stop disinformation in UK political adverts. Here’s a chance to do so | Letter
- VoteGEO-Bench: Measuring the Impact of Generative Engine Optimization on Electoral Visibility
- Exhausted Parents Are Turning to A.I. Apps Despite the Risks
- AFL tells Sportsbet to stop using players in AI generated content
- Does the decline of book reading mark the end of rational thinking?
- Who Gets Counted? Large Language Models, Informative Refusal, and Downstream Bias in Name-Based Demographic Classification
- DistressBench: Evaluating Multi-Dimensional Crisis Support in Large Language Models
- Winner of the Prix Goncourt literary prize admits to using AI
- NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting
- Can scientists reliably tell if a novel is written using AI?
- A misinformation playbook sharpens judgement without breeding cynicism
- Google AI gets cagey when asked who won the 2020 elections
- CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty
- Google DeepMind and Singapore Government announce new AI tool to protect citizens against scams
- AI Alignment for Digital Democracy: Fairer Voters Representation against LLM Biases
- Guarding the Gates of Knowledge
- Beyond the Monolithic Interface: A Research Agenda for Plural Conversational AI
- Ghost in the machine: how AI is haunting the search for the supernatural
- To Manipulate or Not: Opinion Dynamics in LLM Interactions
- Structural Dependence, Imitation or Herding? A Multi-Agent Simulation of Global Intermedia Agenda Setting
- Asymmetric Decline Rather Than Backfire: A Repost-Network Analysis of Japanese Vaccine-Shedding Misinformation on X
- Counterfactual assessment of social media interventions by separating exposure from engagement
- Toxic algorithms wouldn't let them go - now Australia wants an off switch
- Improving social media for democratic discourse
3560
discovered, all time
984
passed triage
2574
rejected at triage
3464
model assessments
710
multi-model panels
1780
distinct claims tracked
Across the whole window
The two tables below describe every item in the last 30 days under misinformation. They are deliberately not narrowed by the reading filter, because a mean taken only over items already selected for their score would just restate the filter.
By topic
| Topic | Branch | Items | Mean | Position |
|---|---|---|---|---|
| Existential and catastrophic risk | risk | 568 | -42 | |
| Governance and regulation | structural | 459 | -31 | |
| Concentration of power | risk | 451 | -36 | |
| Loss of control and alignment | risk | 337 | -49 | |
| Human agency and epistemics | risk | 166 | -26 | |
| Cyber capability | risk | 165 | -44 | |
| Evaluation and measurement | structural | 159 | -19 | |
| Scaling and architecture | structural | 137 | -16 | |
| AGI and timelines | structural | 132 | -29 | |
| Synthetic media and manipulation | risk | 104 | -44 | |
| Employment and displacement | risk | 62 | -31 | |
| Medicine and health | benefit | 43 | -14 | |
| Scientific acceleration | benefit | 42 | -4 | |
| Education and access to expertise | benefit | 29 | -17 | |
| Biological and chemical uplift | risk | 26 | -25 | |
| Climate and energy | structural | 20 | -33 | |
| Compute and infrastructure | structural | 18 | -8 | |
| Productivity and growth | benefit | 6 | -3 | |
| Abundance and material wellbeing | benefit | 5 | -1 | |
| Hype and disillusionment | structural | 5 | -45 |
By source
A source's mean says how the items it published were read. It is not a rating of the source.
| Source | Kind | Tier | Items | Mean |
|---|---|---|---|---|
| The Guardian: Artificial Intelligence | news | 1 | 241 | -52 |
| arXiv cs.CY (Computers and Society) | academic | 1 | 217 | -24 |
| Financial Times: Artificial Intelligence | news | 1 | 112 | -40 |
| arXiv cs.AI | academic | 1 | 99 | -15 |
| The New York Times: Technology | news | 1 | 60 | -36 |
| Ars Technica: AI | news | 1 | 59 | -51 |
| MIT Technology Review: AI | news | 1 | 34 | -42 |
| Nature | academic | 1 | 31 | -25 |
| BBC News: Technology | news | 1 | 29 | -35 |
| OpenAI | lab | 1 | 24 | -8 |
| arXiv cs.LG (Machine Learning) | academic | 1 | 24 | -16 |
| IEEE Spectrum: AI | news | 1 | 19 | -19 |
| The Economist: Science and Technology | news | 1 | 10 | -37 |
| CSET, Georgetown | government | 1 | 9 | -37 |
| Microsoft Research | lab | 1 | 8 | 0 |
| Google DeepMind | lab | 1 | 6 | -4 |
| Google AI Blog | lab | 1 | 2 | -9 |