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 30 days
Discourse valence, window mean
-17
Mixed or uncertain
80 items · range -82 to +50
-100
-50
0
+50
+100
-17
Adverse readingFavourable reading
80 items scored in this window
- When Routing Reveals Membership: Privacy Leakage from MoE Router Telemetry
- I Used AI to Fake a Scientific Paper. Here’s What Happened
- Whose Data, Whose Benchmark? A User-Centric Framework for Auditing Evaluation Resources
- Securing the agentic enterprise with data lineage
- Representation Alignment from a Few Paired Data via Distilled Optimal Transport
- Operationalizing NCII and CSAM Law in the Age of AI: Open Problems
- Albanese government warned it’s ‘sleepwalking into another robodebt scenario’ over use of algorithms and AI
- AI is less regulated than milk, says Microsoft president
- AI evaluators favor job applications written by certain AI models, independent of candidate quality
- Voters Rejected A.I. in the Midterms. Now Comes an Era of Scrutiny.
- OpenAI’s approach to mathematics does not add up
- Will AI grant reviews make science more conservative?
- Opening the Box Changes the Cat: LLMs Detect Chain-of-Thought Monitoring - What now?
- Language Non-Invariance in the Ideological Evaluation of Large Language Models
- Seq@K: Evaluating Language Models Under Sequential Feedback
- Measuring Where Intent Gets Lost in Agentic Smart Contract Synthesis
- What Does an Ontology Catch? Curated, LLM-Generated and Data-Derived Ontologies as Checkers of LLM Agents over Knowledge Graphs
- Propensities Please: Exposing Alignment-Faking LLMs using Synthetic Document Finetuning
- Generalized green and red concepts for artificial intelligence, big data, and information and communication technologies: Multidimensional framework and countermeasures
- AI oversight needs a different model to banking
- Fixing Britain’s welfare state and the limits of AI policymaking
- Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?
- The AI boom stumbles
- Proof-based general-purpose computing with Magnetar
- Atlas of MICCAI: 28 Years of Representation, Collaboration, and the Road to Inclusion
- ChronoCulture: Evaluating Cultural Awareness Across Time in Large Language Models
- Who Can Evaluate AI Independently? A Framework for Analysing Evaluation Infrastructure
- Executives play catch-up as AI governance risks evolve
- NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting
- Open-world AI: a Tale of Three Requirements
- Artificiality's First Exam: An LLM-Referenced C-test for Supraintelligence
- Functional Welfare for AI Safety
- Qistas: A Pre-Registered, Portable Protocol for Fairness Evaluation of Large Language Models
- Can a System-One LLM Perform Knowledge Tracing When Few or No Learners Are Logged?
- Matched but Not Better: An Equivalence-Tested Benchmark of Quantum Machine Learning on Six Clinical Datasets and the QML-Health-READY Reporting Framework
- Conditional Values: The Contingent Foundations of Attitudes toward Artificial Intelligence
- David Pocock concerned senior Albanese adviser ‘vetted’ bipartisan AI letter that was sent to PM
- Conformance as a Distribution: Delegation Contracts, Error Budgets, and the Allocation of Evaluation Authority in Use-Based AI Regulation
- AusClinBench: a deterministically scored benchmark of large language models against current Australian clinical policy
- The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock
- 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
- 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
- Distilling Expert Judgment at Scale
- 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
- 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
- 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
- AI-Native Academia Should Build a Community Verification Layer
- Designing an AI serving harness built to last
- Who Should We Listen to More? Welfare-Aware Preference Acquisition for Pluralistic Alignment
- Meet the Anthropic Engineer Keeping Its AI Agent Trustworthy
- Community safety report and new protections for teens
- OpenHamoye: A Multi-Scale Open Geospatial Intelligence Framework for Decision Support Across Nigeria
- ClinGuard: a governance framework for reliable, transparent, and auditable clinical coordination
- The Privacy Paradox Is a Misnomer: Data Under Structural Uncertainty
- ValiAssist: Scaling LLM-generated Programming Feedback Validation by Demonstration
- SPEM: Structure-Aware Procedural Memory for Efficient Skill Use in LLM Agents
- L2G-SR: Learning to Guide LLM-based Symbolic Regression
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 evaluation. 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 |