Take a seat, weary traveler – we know it’s hard to keep pace with the velocity of AI updates. As we did our diligence for this month’s post, there were almost too many AI and education breakthroughs to choose from, and literally hundreds more are being printed every day. Each week seems to bring new developments, partnerships, and educational experiments, inching us ever closer to an AI-saturated society. While some developments are incremental and others profound, they all share a common signal: we’re moving from speculative promise to structured practice. This month, we’re examining efforts to close critical gaps in AI understanding, skill-building, and system reliability. Let’s take a look.
At MIT’s Computer Science and Artificial Intelligence Laboratory, researchers have launched Themis AI, a startup focused on teaching AI systems to recognize their own limitations. Their Capsa platform wraps around existing machine learning models to detect ambiguity and surface uncertainty before errors propagate. This capability is already being deployed in high-stakes contexts like drug development, telecommunications, and autonomous systems. According to the researchers, knowing what an AI model doesn’t know is key to building public trust and minimizing harm.
A new education and technology hub opened last week in Inglewood’s Hollywood Park, thanks to Google’s Code Next initiative. The lab is designed to bring free AI and coding education directly to youth in underserved communities. Local officials celebrated the lab’s potential to increase exposure to STEM careers while offering a space where students can build skills alongside professional mentors. The launch adds another node to Google’s growing network of community-rooted tech learning centers across the country.
Another authoritative voice has weighed in on the AI revolution: the American Psychological Association has recently released an advisory that lays out the case for integrating AI literacy into middle and high school education. According to the report, young people need to think beyond technical skills. They must learn to spot bias, question outputs, and resist the illusion of objectivity that AI systems often project. Researchers stress that without explicit instruction, teens may accept AI-generated content at face value, especially in areas like mental health or historical analysis. The report urges schools, policymakers, and developers to collaborate on age-appropriate, ethics-focused AI education.
This fall, Texas A&M’s Mays Business School will launch a new “AI and Business” minor designed for upper-level undergraduates across all disciplines. The program combines hands-on work in generative AI and machine learning with coursework in business ethics, storytelling, and decision science. Taught fully online in eight-week terms, the program reflects Mays’ stated goal of preparing students to lead responsibly in an AI-powered economy. It’s the latest signal that AI is becoming a prerequisite for modern leadership.
Anthropic has quietly launched one of the most practical tools to date for anyone looking to get better at prompt engineering. Their Interactive Prompt Engineering Tutorial is a free, self-paced course that teaches users how to write better prompts for Claude 3. The course features nine structured lessons, hands-on exercises, and a sandbox environment to experiment in real time. While the tutorial is aimed at developers and knowledge workers, the company notes it’s also a useful resource for educators seeking to integrate prompt design into the classroom.
Y Combinator recently released a video titled “State-Of-The-Art Prompting For AI Agents,” featuring a discussion on advanced techniques in prompt engineering. The video delves into strategies for optimizing AI agent performance through effective prompting methods. It serves as a valuable resource for those interested in enhancing their understanding of prompt engineering in AI applications.
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From prompt tuning to pedagogy, June’s updates show AI education is growing deeper and more distributed. Whether through a GitHub repo or a high school health class, efforts to improve AI understanding are expanding in both scope and substance. Ready to bring these powerful new capacities into your own learning tools or curriculum? Let’s talk.