RT to help Simon raise awareness of prompt injection attacks in LLMs. Feels a bit like the wild west of early computing, with computer viruses (now = malicious prompts hiding in web data/tools), and not well developed defenses (antivirus, or a lot more developed kernel/user
ETHICS
-
EU Commission Releases In-Depth GenAI Impact Analysis Report
By
–
The @EU_Commission released a report with an in-depth analysis of the technological and social impacts of #GenAI https://
bit.ly/4jS8AN4 #GenerativeAI #AI @mvollmer1 @enilev @anijov @CatherineAdenle @FmFrancoise @AkwyZ @jblefevre60 @BetaMoroney @Kevin_ODonovan @CurieuxExplorer -
AI Decision Contestability: Human Comprehension Limits
By
–
L’idée selon laquelle nous pourrons contester les décisions de l’Intelligence Artificielle est complètement NAÏVE Il devient impossible de contester les décisions de l’IA tant les sujets sont trop compliqués pour les cerveaux humains C’est VIOLENT !
-
xai_evals Framework: Evaluating XAI Methods with Actionable Metrics
By
–
Join us to explore xai_evals — a framework to evaluate SHAP, LIME, Grad-CAM & more with actionable #XAI metrics. 📅 Thursday, 3rd July 🔗 hubs.la/Q03s8-0m0 📄 Paper: hubs.la/Q03s93Yh0 🎙️ Pratinav Seth, Research Scientist at AryaXAI #AIExplainability #RAI #MLAudit
-
UK Children’s AI Usage Reveals Digital Divide Between Schools
By
–
The Alan Turing Institute just revealed an AI divide among UK kids
— Rowan Cheung (@rowancheung) 16 juin 2025
Key highlights:
—22% of children use AI
—Private schools: 52%, State schools: 18%
—Kids mostly use AI for creativity & learning
—Some also avoid AI over energy + water concernspic.twitter.com/bWpM7mtCXrThe Alan Turing Institute just revealed an AI divide among UK kids Key highlights: —22% of children use AI
—Private schools: 52%, State schools: 18%
—Kids mostly use AI for creativity & learning
—Some also avoid AI over energy + water concerns -
Concerns about shallow distance between LLM ethics and real patient harm
By
–
I'd worry that this distance is shallower than the distance between "What are your opinions on medical ethics" and observing what happens when an LLM talks to a susceptible patient.
-
LLMs Produce Plausible but Deeply Wrong Outputs Across Domains
By
–
Terence Tao reporting on the same problem we have seen endlessly in other domains: LLM’s produce output that “looks” correct but is often deeply wrong and even stupid on careful inspection. I know of no domain in which this is NOT the case. And yet people seem surprised over x.com/vitrupo/status…
-
Social Training and Community Dynamics in Online Spaces
By
–
You individually train your followers by acknowledging behavior you like with friendly responses and discouraging what you don’t like. You also set the tone for follower on follower violence. Eg. I read your threads but avoid engaging because I feel you prefer me not to (which is
-
Safe Superintelligence Chief Scientist’s Witty Take on Hair Loss
By
–
hmmm… cranial follicular architecture marked by pronounced involution, culminating in a dramatically rarefied anterior region, evocative of a windswept moor where once a dense forest proudly stood. -> Chief Scientist at Safe Superintelligence
-
Preference: Actions Over Words in AI Agents
By
–
I would not use the term "preference" to describe what an agent *says* is better, only what an agent *does*. It's fragile enough with humans (hence "revealed preference") but with LLMs any relationship between the two must be established from scratch.