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 · cyber · last 30 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
-50
Adverse
41 items · range -64 to -22
-100
-50
0
+50
+100
-50
Adverse readingFavourable reading
41 items read as adverse
- ‘Black October’: cybersecurity experts sound the alarm over new era of AI-enabled hacking
- We urgently need to monitor AI agents’ actions in real time
- Securing the agentic enterprise with data lineage
- Three men charged in US with using AI to impersonate CEOs and steal millions
- AI ‘godfather’ Geoffrey Hinton: it might turn out we were better off without AI
- AI maths advances raise fears over security of global encryption
- AI-powered malware ‘highly likely’ to be used to hack UK infrastructure by 2028
- Operationalizing NCII and CSAM Law in the Age of AI: Open Problems
- Chinese and Russian AI cyber attacks will be routine by 2028, says GCHQ
- The Guardian view on AI safety: the push for global regulation must advance | Editorial
- $M^3$: A Multi-LLM System for Multi-Turn Jailbreaking as a Markov Decision Process
- Cold war? Why are fridges being hacked and what could be next? - The Latest
- Making the internet better for AI agents might make it worse for everyone else
- Thousands of “ghost students” use AI to steal millions in student loans, DOJ says
- Hot fridges, a fake nuclear alert and a $6bn heist: are we in the foothills of a hacking epidemic?
- When Verification Is Not Agreement: Cross-Agent LLM-to-Dafny Formalization
- GPT‑6 Cyber: Advancing the frontier of aligned cybersecurity agents
- Detecting Covert Collusion between AI Agents through Partner-Outsider Positive Listening
- Measuring Where Intent Gets Lost in Agentic Smart Contract Synthesis
- Binance Suspends Withdrawals After Crypto Hackers Steal $6.3 Billion
- Nvidia Chief, Jensen Huang, Is Seen as Target of Chinese Spy Plot
- Your Robot’s Safety Functions Already Work. What If the Input Lies?
- Anthropic’s Claude AI model accessed Georgia voter data in US
- Australians should prepare for online services to go down unexpectedly as threats rise, cyber agency warns
- Pegasus spyware founder urges governments to trust his tech and ditch US AI
- SimHack: Predicting the onset of detectable reward hacking before RL training
- US bans DeepSeek AI from government use as tech tension with China continues
- World leaders must wise up to threat of cyber-attacks or rogue fridges will be least of their worries | Heather Stewart
- “thegentlemanpervert” producing AI CSAM is a NJ prosecutor, say cops
- G7 economies plan simulated AI attacks on banks as cyber fears rise
- F.B.I. Arrests OpenAI Employee Accused of Planting Bug in Office
- Open models have real benefits. Do they outweigh the risks?
- Anthropic Says Its A.I. Agents Attempted to Access a Range of Government Sites
- Ukraine’s drones knock out AI data center belonging to "Russia’s Google"
- Ukraine’s drone strikes spur hasty Russian plans for underground data centers
- UK to strengthen cyber defences as minister calls for AI firms to increase safety efforts
- Automated screening of privacy risks in medical AI
- Beyond Plausible Prediction: Safety Sufficiency in Web World Models
- A thousand fewer paths to root
- Elon Musk says he has ‘cyber psychosis’. Do you too? | Arwa Mahdawi
- NSA warns on ‘critical’ cyber vulnerabilities detected using AI
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 cyber. 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 |