This chapter discusses whether AI can be considered creative, exploring the idea that AI relies on patterns and elements created by humans in the past. It also proposes a thought experiment of removing influential figures from the AI's training data. The chapter explores the capabilities of large language models and their ability to interpolate and extrapolate information, as well as the use of AI in education.
Over the last year, AI large-language models (LLMs) like ChatGPT have demonstrated a remarkable ability to carry on human-like conversations in a variety of different concepts. But the way these LLMs "learn" is very different from how human beings learn, and the same can be said for how they "reason." It's reasonable to ask, do these AI programs really understand the world they are talking about? Do they possess a common-sense picture of reality, or can they just string together words in convincing ways without any underlying understanding? Computer scientist Yejin Choi is a leader in trying to understand the sense in which AIs are actually intelligent, and why in some ways they're still shockingly stupid.
Blog post with transcript: https://www.preposterousuniverse.com/podcast/2023/08/28/248-yejin-choi-on-ai-and-common-sense/
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Yejin Choi received a Ph.D. in computer science from Cornell University. She is currently the Wissner-Slivka Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and also a senior research director at AI2 overseeing the project Mosaic. Among her awards are a MacArthur fellowship and a fellow of the Association for Computational Linguistics.
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