Chief Academic Officer at Code.org | Lead of TeachAI | Systems Changer | Hip Hop Head
You don't have to understand the type of math Terence Tao studies (I don't) to glean takeaways from his comments about using AI to explore the boundaries of math. Having strong subject matter expertise is crucial for getting the most out of AI tools. AI use cases are often complex and context-dependent, so identifying which ones are valuable also requires at minimum a basic understanding of how the tools work, including their capabilities and limitations. Determining which problems can best be addressed with AI, how to define them properly, and then integrating the tool into the workflow demands a high level of expertise - both topic and tool. Here's a great quote: "I think at the frontier, we will always need humans and AI. They have complementary strengths. AI is very good at converting billions of pieces of data into one good answer. Humans are good at taking 10 observations and making really inspired guesses." Lane Dilg, thanks for sharing the article :)
Dorothy Carlson
5mo
The line about humans and AI as “complementary strengths” stands out for me as well. It’s a strong framework for thinking and learning about AI Literacy.
Director of Technology and Innovation, Stanford Accelerator for Learning
5moI was struck by his prediction about using AI as glue to achieve new insights. And not just human-to-idea glue, but also human-to-highly specialized math software-to-idea glue.