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 · education · last 365 days
Discourse valence, window mean
-17
Mixed or uncertain
29 items · range -61 to +50
-100
-50
0
+50
+100
-17
Adverse readingFavourable reading
29 items scored in this window
- Who Acts, Who Knows, Who Answers? A Corpus-Assisted Discourse Analysis of Agency, Epistemic Responsibility, and Accountability in Generative AI Higher Education Research
- Argus: Academic Integrity in the Era of Generative AI
- Reading scores plummet as ‘digital distraction’ harms students
- The focus on AI safety disasters ignores everyday harms
- Big AI is trying to own the pathway to work. Universities shouldn’t play along | Ella Hafermalz
- Is AI eroding PhD students’ critical thinking and analysis skills?
- Beyond Score Accuracy: Examining the Diagnostic Quality of LLM-Generated Structured Assessment in Higher Education
- Student Use of LLMs and the Limits of AI-Generated Question Difficulty in Data Science Courses
- Your Programming Students' Cognition with ChatGPT: Higher Performance, Lower Retention, and Reduced Ownership
- Same Performance, Different Process: Epistemic Ownership in AI-Mediated Education
- AI-written admissions essays are widespread but penalized
- What does human inquiry even mean anymore?
- U.S. State Guidance on AI in K-12 Education: A Comparative Content and Citation Analysis
- With a Thermomix You Lose the Ability to Cook: A Kitchen Machine Analogy for Applications of Generative AI in Education
- Instructional Governance by Design: A Framework for AI in Computing Education
- Developing Competency in AI Ethics: A training framework
- AI Security Literacy: Ecosystem-based Competency Framework and K-12 Learning Platform
- Can our children still prosper in the age of AI?
- An AI Factory for Technology Education: An Agentic Pipeline with Closed Loop Audience Feedback
- AI Can Do Your Homework. Now What? Report from an Online Workshop on Computing Assessment in the Age of Generative AI
- Who Decides? Agency and Legitimacy in Digital Educational Systems
- Scaffolding GenAI Use in Ethical Essay Writing: A Three-Year Experience Report in Introductory Computing
- Alternative AI Philosophy: Daoism as Method for AI in Education
- HACHIMI-II: From Role-Play to Learner Behavior Modeling for Faithful Student Simulation
- Playing Bias: Epistemic Games for Interpreting Text-to-Image Models
- Offline Apprenticeship Learning for Human-Centric Environments
- Learning by Collaborating in the Age of AI: Research Mentorship for Polymathic, Workflow-Centered Science
- A pedagogically guided LLM framework for scaffolding human-AI cocreation and preserving learners' agency and creativity
- ValiAssist: Scaling LLM-generated Programming Feedback Validation by Demonstration
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 education. 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 |