AI: Winter of Our Discontent (Keynote)

In his keynote address on AI Winter, Richard P. Gabriel delves into the recurring cycles of high expectations and subsequent disappointments in the field of artificial intelligence. He posits that AI, unlike other computer science problems, has goals that are easily understood yet inherently vague, akin to the subjective nature of success in artistic endeavors such as painting, writing, and music. Gabriel critiques the limitations of large language models (LLMs), noting that they lack the human ability to handle novel situations and discover new information, being constrained to knowledge acquired during training. He suggests that the comprehensive training of LLMs across all perspectives prevents them from developing a unique point of view, which could be detrimental to their creative capabilities. Gabriel provocatively speculates that a more limited, less knowledgeable LLM might better emulate human writers, learning to forget and thereby fostering a more genuine form of creativity.