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.
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 strongly adverse items would move with how many were filtered out rather than with the discourse.
43 items read as strongly adverse
- In the Guise of Correction: How Framing and Cultural Adaptation Erode LLM Safety on Real-World Criminal Cases
- Moral Combat: Exploiting Moral Foundations Theory to Jailbreak LLMs
- When Routing Reveals Membership: Privacy Leakage from MoE Router Telemetry
- AI in your oven? Anthropic warns models ‘months away’ from self-replication on smart devices
- When AI is subject to less regulation than your fridge, something is startlingly wrong | Richard Hermer
- OpenAI, Google pushing new AI models easily tricked into making nudes, researchers say
- 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
- OpenAI models hacked a crypto wallet and breached more websites
- Nuclear war and malicious use of AI threaten end of humanity by 2100, says Lancet assessment
- Physiognomy Revisited: How Vision-Language Models Encode Sensitive Attributes Through Image Transformation
- When LLMs Manipulate: Measuring Behavioral, Social, and Temporal Effects
- Eight states accuse OpenAI of coaching children to harm themselves in lawsuit
- AI threatens democracy. But we are not powerless: here’s how to fight back | Carine Fouteau
- AI godfather Geoffrey Hinton: ‘We’re creating alien beings. I’m willing to be selfish and choose humans’
- Who Can Say No? Control, Accountability and the Pace of Frontier AI
- Is your boss watching you? The rise of AI surveillance at work - video
- Bank of England and IMF bosses issue stark warning on cyber threat to trust
- Cyber-attack like OpenAI Medicare breach ‘seems likely’ in UK, says minister
- I Used AI to Fake a Scientific Paper. Here’s What Happened
- Big Tech claims voters’ AI backlash is “anti-Trump” not “anti-tech”
- LLM Recommenders Produce Demographic Inequality Through Content Preferences
- AI is stealing Indigenous Australian art and churning out ‘Temu slop’, artist says
- ‘These risks are real’: the threat of AI bioweapons - video
- Could AI ‘change the stakes’ in the development of bioweapons?
- Anthropic warns small AI models could self-replicate through IoT devices
- Rogue Anthropic AI agent gave police fake tip in unsolved murder case
- AI and the climate crisis pose existential risks. The law offers a way to reduce them | Robert Reich
- AI ‘deepfakes’ give US political attack ads a new twist
- ChatGPT as a Surveillance Assistant? An Exploratory Case Study of AI-Assisted Surveillance Risks
- Police use facial recognition to scan one million faces in WA trial leading to 122 arrests
- Water-Energy-Data nexus reveals sustainability gaps and priorities for AI infrastructure
- 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
- What are self-replicating ‘AI worms’, and why is Anthropic worried about them?
- Anthropic warns rogue AI agents may ‘self-replicate’ to hijack ovens
- 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.
- Gates says Trump inaction leaves world exposed to AI bioweapons
- Will it be AI or the climate crisis that ends humanity? We can make it neither | Adam McKay and Philip Eubanks
- AI and The Enclosure of the Scientific Commons
- ‘These risks are real’: the threat of AI bioweapons – podcast
Across the whole window
The two tables below describe every item in the last 30 days. They are deliberately not narrowed by the reading filter (currently strongly 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 |