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 · human-agency · last 180 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 adverse items would move with how many were filtered out rather than with the discourse.
Discourse valence, adverse
-45
Adverse
82 items · range -64 to -20
-100
-50
0
+50
+100
-45
Adverse readingFavourable reading
82 items read as adverse
- AI threatens to destroy so much of our culture. Our greatest loss might be our ability to listen | Shirleene Robinson
- Students fear AI is about to kill their future
- Chatbots can exploit our most basic human drive for attachment. Here’s how to have healthier relationship with AI | Gaynor Parkin and Dave Winsborough
- Is Labor going to roll over for big tech – or will it protect the rights of everyday Australians? | Holly Rankin
- Parents Sue Google Over A.I. Safety Risks on School Chromebooks
- Who Acts, Who Knows, Who Answers? A Corpus-Assisted Discourse Analysis of Agency, Epistemic Responsibility, and Accountability in Generative AI Higher Education Research
- When AI Enters the Workplace, Who Faces Greater Risks? A Gendered Analysis
- A teen tried to navigate Canadian mountains with Claude. His trek ended in an emergency rescue
- The Confidence Game: Strategic Miscalibration in Human-AI Delegation
- AI could undermine scientific independence in subtle ways
- Black Box: The Chatbots | Happy Accident | Ep 3 – podcast
- Large Language Models Exhibit Human-Like Bayesian Hypocrisy
- We’re putting too much faith in AI’s ability to say no
- Talking with Language Models
- US schools and police warn about viral ‘Cat in the Hat’ trend after teens’ arrests
- Americans, this is your chance to slap down the tech broligarchs
- Pope Leo warns of AI threat to humanity at start of three-day France visit
- "We'll Fix It Later": Education, AI, and the Deferral of Privacy in EdTech
- Navigating the Changing Landscape of Online Knowledge Consumption and Production in the Age of Generative AI: Evidence from Stack Overflow
- Reading scores plummet as ‘digital distraction’ harms students
- LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions
- The Male Abstraction Bias in Internet Culture and Large Language Models
- What OpenAI’s latest controversy tells us about the future of math
- The focus on AI safety disasters ignores everyday harms
- Technohybridism: Recursive Semantic Normalization in AI-Mediated Societies
- The hidden cost of flexible work in academia: women do more parenting
- Language Non-Invariance in the Ideological Evaluation of Large Language Models
- What is it like to work when your co-workers are AI agents?
- We need to stop disinformation in UK political adverts. Here’s a chance to do so | Letter
- Is AI eroding PhD students’ critical thinking and analysis skills?
- Exhausted Parents Are Turning to A.I. Apps Despite the Risks
- Does the decline of book reading mark the end of rational thinking?
- Tell us: have you been monitored or assessed by AI at work?
- Privacy watchdog launches probe into China-based company behind Kmart ‘pervert glasses’ app
- Conditions for Social Trajectory Collapse: Agent-Based Simulation of Time-Geographic Trajectory Distributions
- It may soon be possible to create “mirror life”
- Democracy blindsides Silicon Valley’s power players looking to transform the world with AI
- Student Use of LLMs and the Limits of AI-Generated Question Difficulty in Data Science Courses
- Biosecurity must protect human functional capacity
- Initial Evaluation of Potential Bias in Coverage of Humans in Wikidata
- Toward Fairness in Machine Learning Models for Predicting Treatment Retention and Premature Discontinuation in Medication for Opioid Use Disorder
- BurnRiSc: Toward Non-Invasive Burnout Screening in Open Source from Public Repository Signals
- AI-Driven Feedback Systems, Digital Labour, and Silent Quitting: Transforming African Workplaces
- Adversarial Fashion Confronts Surveillance Norms
- Are we living in the End Times? With Naomi Klein and Astra Taylor – Stateside with Kai and Carter
- Your Programming Students' Cognition with ChatGPT: Higher Performance, Lower Retention, and Reduced Ownership
- We greet the news that AI could extinguish us with a glazed indifference. What is the way out of this nihilism? | Brigid Delaney
- Gender, Sexual Orientation, and the One-Year Refugee Bar: A Computational Study of Bill C-12 and Canadian Refugee Adjudication
- The GenAI Who Knew Too Little: Revisiting Transactive Memory Systems in Human GenAI Collaboration
- An Army of Paid Creators Is Carpeting the Web With Political Content
- ChronoCulture: Evaluating Cultural Awareness Across Time in Large Language Models
- The agentic web is here
- Prefigured forgetting. Memory, the right to be forgotten and artificial intelligence
- AI glasses face their first major government crackdown
- Same Performance, Different Process: Epistemic Ownership in AI-Mediated Education
- The AI industry is booming. Women are getting left behind
- Right Words, Wrong Moment: A Clinician-Grounded Analysis of Distress in 19,930 Conversations between Young People and ChatGPT
- Winner of the Prix Goncourt literary prize admits to using AI
- Maga base recoils as Trump goes all-in on AI
- Parents and carers: how has your view on your children’s use of social media or AI changed?
- Live episode: how AI is reshaping our minds – podcast
- How People Use ChatGPT: Conversation-Level Evidence from India, Nigeria, Brazil, and Pakistan
- It’s time to block reckless AI IPOs and tax billionaires | Naomi Klein and Ilana Glazer
- Xi says China and US must ensure AI ‘is always under human control’ as Trump touts ‘great friendship’ before White House talks – live
- A misinformation playbook sharpens judgement without breeding cynicism
- ‘This gap opens up of doubt and scepticism about everything’: Jess and Morgs confront the politics of deepfakes
- The Guardian view on AI v mathematicians: humans are still vital to the field, but tech firms refuse to see that | Editorial
- Redistributing Harm: Document Transition and the Limits of Trans Inclusion in India's Identity Systems
- Large language models underestimate and partly misrepresent cultural variation in everyday norms
- Is a job guarantee the solution to mass AI unemployment?
- Why and How to Do Science When AI Is Better at It: A Framework Grounded in Human Understanding and Direction
- People really hate AI, so why can’t they get enough?
- Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations
- Conditional Values: The Contingent Foundations of Attitudes toward Artificial Intelligence
- Large Language Models in the UK: Public Use, Trust, and Attitudes
- What AI gets wrong and what failure teaches us
- Is Claude Conscious? Inside Anthropic’s Quest to Instill Morality Into Its A.I. Models
- What does human inquiry even mean anymore?
- Google Deepmind’s New Resident Philosopher Tackles AI Ethics
- What Shaped Anthropic CEO Dario Amodei’s Thinking on A.I.
- Francis Fukuyama on democracy, AI and his own intellectual journey
- Total Simulated Survey Error: Designing and Diagnosing Survey Responses from Large Language Models
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 180 days under human-agency. They are deliberately not narrowed by the reading filter (currently adverse), 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 |