On March 29, 2024, the 12th annual Marshall M. Weinberg Symposium took place at the University of Michigan, focusing on the theme "Natural vs. Artificial Intelligence in the Age of ChatGPT." Esteemed speakers tackled the complexities of language models and the nature of intelligence, both human and artificial.
Yejin Choi presented "Possible Impossibilities, Impossible Possibilities, and Paradoxes," questioning the limits and potential of AI, and highlighting the Generative AI Paradox where AI's ability to generate content may eclipse its understanding.
Melanie Mitchell addressed the heated debate about whether AI can truly understand language, emphasizing the need for credible methods to test AI intelligence.
Paul Smolensky turned to the crisis in theories of cognition posed by AI’s success, contrasting traditional symbolic systems with modern neural-network models which, contrary to earlier beliefs, demonstrate compositional strengths.
Raphaël Millière underscored the necessity of understanding the causal mechanisms behind large language models' behavior instead of solely their outputs.
Amidst the expert panel discussions, the Weinberg Symposium also set the stage for the next generation of scholars through its inaugural poster session for undergraduates. Sixteen students showcased their research, engaging with peers and distinguished members of the academic community. Hannah Feng and Sophia Micale were recognized with outstanding poster awards, while Grace DesJardins secured the Best Poster award, exhibiting her poster titled "Cumulative Risk and Icon Arrays: Attempting to Increase Risk Perception".
The symposium fostered a dynamic exchange of ideas, advancing the conversation on the evolving relationship between natural and artificial intelligence.
