First Principles
Physicist Neil Johnson has mapped the exact moment AI can flip from accurate to false, and he says understanding their underlying physics could be the key to safer systems.
Managing the Trust-Risk Equation in AI: Predicting Hallucinations Before They Strike
Security Week
New physics-based research suggests large language models could predict when their own answers are about to go wrong — a potential game changer for trust, risk, and security in AI-driven systems.
Scrutiny of the Vaccine Injury Compensation Program
Newswise
Newswise — Health Secretary Robert F. Kennedy Jr.’s push to overhaul the Vaccine Injury Compensation Program is stirring debate over vaccine safety and trust in public health. Experts warn his rhetoric could fuel misinformation and undermine confidence in vaccines at a time when hesitancy is already at historic highs.
Here’s why saying ‘please’ and ‘thank you’ costs 158,000,000 bottles of water a day
Metro UK
‘I wonder how much money OpenAI has lost in electricity costs from people saying “please” and “thank you” to their models.’
Multispin Physics of AI Tipping Points and Hallucinations (AI Podcast)
Daily Papers AI
Today’s paper: Multispin Physics of AI Tipping Points and Hallucinations
Should We Trust AI? Three Approaches to AI Fallibility
Security Week
The promise of agentic AI is compelling: increased operational speed, increased automation, and lower operational costs. But have we ever paused to seriously ask the question: can we trust this thing?
Bypassing Covert Resilience in Contentious Online Networks
SIAM News
Tragic acts of terrorism—such as February’s mass stabbing in Austria by a 23-year-old Syrian asylum seeker who was allegedly radicalized online by the Islamic State —accentuate the dangers of radicalization via the internet. Terrorist organizations exploit popular social media platforms to advance their ideology-driven agendas through recruitment, fundraising, and the spread of propaganda — all of which ultimately causes severe harm in communities around the world. From a national security perspective, this drive towards radicalization raises pressing questions about our ability to monitor, quantify, understand, predict, and even mitigate such efforts before they materialize as tragedies.
Physics reveals and explains patterns in conflict casualties
Europhysics Letters
Why humans fight has no easy answer. However, understanding better how humans fight could inform future humanitarian aid planning and insight into hidden shifts for peace efforts. Here we show that an empirically-grounded physics theory of fighter dynamics — which is a generalization of the well-known physics of polymer assembly — can explain casualty patterns observed across decades of violence in a current conflict hotspot. It also suggests the possibility of future ‘super-shock’ surprise attacks that are even more lethal than have already been seen. These insights from physics open the door to new policy discussions surrounding humanitarian aid and peace efforts that account mechanistically for human violence across scales.
Frank Yingjie Huo, Dylan Restrepo, Pedro Manrique, Gordon Woo, Neil Johnson
“Big Sunscreen”: When Misinformation Fuels Extremist Conspiracy Theories
Beauty Matter
A broad spectrum of “sunscreen truthers” on platforms like TikTok, Instagram, and Facebook have peddled the trope that sunscreen causes cancer for at least the last decade. These types of conspiracy theories have reached a fever pitch on social media since the pandemic. From vegan anti-vaxxers and bro-biohackers to MAHA and QAnon supporters, they all have two things in common: a case of chemophobia and a belief that sunscreen is the enemy.
Influence of Twitter social network graph topologies on traditional and meme stocks during the 2021 GameStop short squeeze
NPJ Complexity
In early 2021, groups of Reddit and Twitter users collaborated to raise the price of GameStop stock from $20 to $400 in a matter of days. The heavy influence of social media activity on the rise of GameStop prices can be contrasted with the muted social media influence on other, more traditional stocks. While traditional stocks are modeled quite successfully by current methods, such methods break down when used to model these so-called meme stocks. Our project analyzes the graph topology of retweet graphs built from GameStop-related tweets and other meme stocks to find that the clustering coefficient and network diameter of a retweet graph can be used to decrease the mean absolute error of meme stock trading volume predictions by as much as 46% over the control group during the first 70 trading days of 2021.