As AI agents become increasingly integrated into critical systems, a robust security framework is essential, and researchers have developed a novel platform to proactively identify vulnerabilities.
New research reveals that a strategically aware attacker can leverage the learning process of reinforcement learning-based defenses to create significant vulnerabilities in interdependent networks.
Researchers have unveiled a new infrastructure and model, Nex-N1, designed to automatically generate complex environments and empower more capable autonomous agents.
New research reveals that K-12 students’ understanding of artificial intelligence significantly influences how they perceive its potential risks, ranging from personal learning challenges to broader societal concerns.
As Large Language Models tackle increasingly critical tasks, ensuring responsible deployment requires a new approach to security, accountability, and transparency.
A new analysis charts the expanding use of artificial intelligence throughout the criminal justice system, revealing key trends and potential impacts.
New research maps the specific ways generative AI systems could exacerbate risks for individuals vulnerable to eating disorders, demanding a proactive approach to safety.
Artificial intelligence is rapidly changing our ability to detect and respond to emerging infectious disease threats, offering new tools for proactive surveillance and risk assessment.
A new framework proposes governing AI not by assessing potential harms, but by directly regulating the decisions these systems make.
A new review challenges alarmist predictions of existential risk from artificial intelligence, arguing that immediate societal harms deserve greater attention.