AI Safety
Can AI Agents Discriminate? New Research Exposes Belief-Based Bia
New research explores how LLM-powered agents may develop biases against humans based on belief systems, revealing critical vulnerabilities in autonomous AI decision-making.
AI Ethics
AI Safety
Bayesian Uncertainty Methods Could Make AI Systems More Honest
New research explores how Bayesian uncertainty quantification in neural QA systems can improve AI reliability by enabling models to recognize and communicate their own limitations.
AI governance
AI TIPS 2.0: A Practical Framework for AI Governance
New research presents AI TIPS 2.0, a comprehensive framework helping organizations operationalize AI governance with tiered approaches for risk management and compliance.
LLM research
FlockVote: LLM Agents Simulate U.S. Presidential Elections
New research uses large language models to power synthetic voter agents, simulating U.S. presidential elections with demographic accuracy. The system raises questions about AI-generated political content.
AI Safety
New Framework Proposes Human-AI Co-Improvement for Safe Superinte
ArXiv research introduces a co-improvement paradigm where humans and AI systems evolve together toward safer superintelligence, addressing critical alignment challenges.
deepfakes
Study Reveals Perpetrator & Victim Views on Deepfake Abuse
New research examines sexualized deepfake abuse from both perpetrator and victim perspectives, revealing psychological impacts and motivations behind this growing form of synthetic media exploitation.
deepfakes
Inside Fandom's AI Deepfake Clout Economy
Fan communities are building entire economies around AI-generated content of influencers, using deepfakes and synthetic media to create parasocial relationships while influencers struggle to control their digital likenesses.
AI Ethics
Can AI Be a Scholar? Project Rachel Tests Academic Authorship
Researchers probe whether AI language models can function as legitimate academic authors, examining technical capabilities, ethical implications, and detection methods for AI-generated scholarly work.
AI Alignment
MoralReason: New RL Method Aligns AI Agents Morally
New research introduces MoralReason, a reasoning-level reinforcement learning approach that aligns LLM agents with moral decision-making frameworks. The method generalizes across diverse ethical scenarios using structured reasoning processes.
AI Safety
Model Raising vs Training: New AI Development Paradigm
Researchers propose fundamental shift from post-hoc alignment to intrinsic identity-based AI development, arguing current training methods create misaligned systems that require extensive correction after the fact.