"I was able to see the rise of ChatGPT and other LLMs, and how people were using them in my academic life. Some people would use it unethically on tests or assignments, but it could also be used to create practice problems. Being able to see how rapidly it's evolving in front of me was the main reason I became interested. It's affecting our academic life so much that it's imperative that we're at the forefront of how it's being developed."
"One of the main things I worked on was how LLMs can sometimes indirectly give out private data. Say you ask it to code something for you that requires an API key, which is sensitive information. Because it's trained on a vast amount of data, it could have an API key in its data set, and it'll give you code, possibly including the API key."
High school students face uncertain career prospects as AI changes valued skills and federal research funding cuts stall scientific work. STEM career trajectories are evolving, prompting new educational strategies and hands-on research. Rapid LLM advances affect academic practices, enabling helpful tools and enabling unethical uses. LLMs can inadvertently expose private data—for example, revealing API keys from training data—so students are developing algorithms and privacy-preserving techniques. Specialized math and science programs provide opportunities for independent research and skill-building to prepare students for AI-driven scientific careers.
Read at WIRED
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