Philosopher David J. Chalmers proposes interpreting AI systems through their attitudes toward propositions - much like we interpret humans. His concept of "propositional interpretability" aims to put mechanistic AI explanation on new footing, drawing on philosophical theories of human understanding.<br /> The article Philosopher David Chalmers: Current AI interpretability methods miss what matters most appeared first on The Decoder. [...]
OpenAI researchers are experimenting with a new approach to designing neural networks, with the aim of making AI models easier to understand, debug, and govern. Sparse models can provide enterprises w [...]
When researchers at Anthropic injected the concept of "betrayal" into their Claude AI model's neural networks and asked if it noticed anything unusual, the system paused before respondi [...]
Model providers want to prove the security and robustness of their models, releasing system cards and conducting red-team exercises with each new release. But it can be difficult for enterprises to pa [...]
Across 116 enterprises, agents are in production and so are the incidents: A majority have already had a confirmed agent security event or a near-miss. Two-thirds of enterprises enforce scoped permiss [...]
Media Matters for America has sued the US Federal Trade Commission, claiming that the agency is unfairly targeting it in retaliation for past criticisms of the social media platform X in violation of [...]
The court has blocked the Federal Trade Commission's investigation into Media Matters, the media nonprofit that previously published research showing that ads appeared on X alongside neo-Nazi and [...]
Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incide [...]