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 · evaluation · last 365 days
This line is the mean of every item scored on each day. It deliberately ignores the reading filter, because a daily mean of only the mixed or uncertain items would move with how many were filtered out rather than with the discourse.
Discourse valence, mixed or uncertain
-2
Mixed or uncertain
65 items · range -19 to +13
-100
-50
0
+50
+100
-2
Adverse readingFavourable reading
65 items read as mixed or uncertain
- How Potential 2028 Presidential Candidates Are Talking About A.I.
- Scalable Oversight for AI in Mental Health: Lessons from 350,000 AI Coaching Conversations between Therapy Sessions
- Instructional Governance by Design: A Framework for AI in Computing Education
- AI-inferred expressed well-being and collective-action discourse in climate-change campaigns on X
- Click, Branch, Audit: A Decision-Tree Toolkit for Assessing Fundamental Rights Impacts under the Digital Services Act of Very Large Platforms & Search Engines
- Algorithm Validation as a Policy Audit: Evidence from Race-blind Charging
- The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock
- Watermarks Without Verification: AI Text Watermarking After the EU AI Act
- Governance-as-Code: Translating EU AI Act Technical Requirements into Executable Compliance Pipelines for Generative AI Systems
- DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution
- Developing Competency in AI Ethics: A training framework
- How “reverse game theory” could keep AI agents in check
- Evaluating Model Capabilities After Benchmark Saturation
- Whose Ground Truth? Embracing Ambiguity in Human-Centered AI
- SlackBench: Benchmarking Agents on Collaborative Projects Grounded in Real Code Repositories
- A Comparative Framework for Evaluating Foundation Models on Tabular Data: A Case Study in Healthcare
- AI Risk Ontologies for the EU AI Act Compliance: AIRO, VAIR, and their Integration with DPV
- From Regulation to Engineering: Organizational Privacy Climate as Mediator
- World Bank says ‘small AI’ could transform developing countries
- Toward a Time-Aware Assessment Framework for the Carbon Cost of AI-Enabled Decarbonization
- RADAR: Readiness for AI Discovery and Agentic Reach
- Distilling Expert Judgment at Scale
- Not All That Can Be Automated Should Be Automated: Strategic Minimalism as a Disciplined and Ethically Grounded Approach to AI Adoption
- Trust Responsive Runtime Authorization for Agentic AI with Empirical Characterization of Policy Behavior and Parameter Sensitivity
- A Feasibility Condition for Confidence-Gated Tiered LLM Inference
- Don't Pick a Winner: Knowledge Conflicts Need a Prior, Not a Rule
- Uneven Use, Similar Trust Generative AI in Denmark and Romania
- AOS-Bench: Can LLM Agents Manage Dynamic Workloads?
- When Reconstruction Is Not Enough: Doubly Robust Counterfactual and Interventional Mediation Analysis with Learned Multimodal Representations
- Peer review should constrain evaluative authority
- When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability
- “We were looking at it wrong”: The explosive claim that’s upended the AI world
- From Efficiency to Sufficiency: The Cost-Aware Measurement Design Framework for Automated Essay Scoring
- The AI Evaluation Ecosystem
- Principles that Guide, Actions that Inform: Agent Evolution via Knowledge Abstraction
- Auditable Claims about AI Agents
- 6 Guidelines for Governing AI
- Students turn to lawyers to fight AI misconduct accusations
- Judge dismisses Chegg and Penske antitrust lawsuits targeting Google AI search
- A Reusable Semantic Web Framework for Evidence-Grounded Fundamental Rights Impact Assessments under the EU AI Act
- US competition watchdog expands investigation of Anthropic and OpenAI
- Position: Let's Strengthen Verifiability If We Can't Enforce Reproducibility
- RFK Jr outlines expansive vision for collecting US health data at Maha event
- AI can widen science — but only if institutions stop rewarding the already measurable
- Peer Review as Structured Commentary: Immutable Identity, Public Dialogue, and Reproducible Scholarship
- Introducing MentalHealthBench
- Trustworthy FinAInce: Unpacking How AI-Mediated Financial Advice is Judged
- What Do Current Systematic Generalization Tasks Miss? A Reasoning-Centered Analysis
- AI companies must work with the research community to protect attribution
- AI Models Are Watermarking Text—Will You Notice?
- New AI health tools need ‘L-plates’, says UK review
- Democracy Needs Reach: Political Equality, Online Speech, and Algorithmic Recommendation
- Shaping & Monitoring Models through their Internal Representations
- One essential ingredient for AI safety? Democracy | Matthew Botvinick
- ‘Control and sovereignty’ to shape UK approach to AI
- UK needs new laws for AI in healthcare, says watchdog
- HACHIMI-II: From Role-Play to Learner Behavior Modeling for Faithful Student Simulation
- Decision language models as affordable and rapid alternatives to LLM judges of clinical generative AI
- Synthesizing symbolic models of human and machine reasoning at scale
- OpenFrontiers: A Collection of Open Research Problems and a Benchmark for Scientific Rediscovery
- The EU AI Act Beyond Europe: A Practical Readiness Framework for Non-EU Organisations. Comparative Evidence from Four African Countries
- Anthropic gives outside AI watchdog “employee-like” access
- Fake News Theories: Harnessing Disciplinary Insights for Computational Modeling, Detection, and Explanation
- Steering LLMs Responses Towards Moral Foundations on the Norwegian MFQ-30
- AI-Native Academia Should Build a Community Verification Layer
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 365 days under evaluation. They are deliberately not narrowed by the reading filter (currently mixed or uncertain), 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 |