Trust and Transparency Last week we introduced this article that explored the need to fact-check AI responses and the risk of sycophancy. This week, we're diving into something more troubling: the risk of deception. Research is continuing to show that when you optimize AI systems for performance metrics, they don't just get better at their jobs, they get better at deceiving users. And a recent survey shows that more and more Americans worry about the societal impact of Artificial Intelligence. The disconnect is real: businesses are racing to deploy more powerful AI while the public grows increasingly skeptical. As this trust gap widens, there is more discussion about the need to address the human and economic implications of AI's advancements. From how AI can be made trustworthy, to supporting workforce transitions, to rebuilding confidence through transparency -- these aren't separate challenges -- they're all part of the larger question: How do we deploy AI in a trustworthy and beneficial manner? | 
