I believe that accountability becomes more pronounced in the era of AI. While the accountability dynamics between humans and machines may differ, humans will invariably assert that if someone had access to such advanced AI capabilities, they had the means to make more informed decisions.
Proposing a new method to improve the reasoning abilities of LLMs, the paper makes a significant contribution by demonstrating a new approach that is both effective and efficient. We also pull ideas from the science with specific ideas to improve your own prompting.
This month's topic is Agentic AI aka AI Agents, a relatively new type of AI system that can pursue complex goals using capabilities to perceive, reason, and act.
On a surface level, AI might seem like the perfect solution to the challenges of social learning. But is this really true? Is it actually what we want?
Learning with and from others can be incredibly enriching. When we collaborate, discuss, and share ideas, we gain new perspectives, deepen understanding, and achieve things we never could have on our own. That's the power of social learning and it's a cornerstone of human learning and the foundation of our collective intelligence. When we learn in social contexts, we're not just grappling with the material, we're also navigating complex social dynamics. We're constantly aware of how others perceive us, which is both a motivator and a stressor.
This is where the promise and peril of AI in education comes in. On a surface level, AI might seem like the perfect solution to the challenges of social learning. An AI tutor won't react to your silly question or smirk at your wrong answer. It's tempting to think that AI could create a judgment-free learning environment where every question is safe to ask. But is this really true? And even if it is, taken to the extremes of large-scale adoption of AI tutors, is it actually what we want?
The Artificiality Weekend Briefing: About AI, Not Written by AI
