Mind Over Models: An Economist’s Take on AI Speculation
In this bingecast installment of the Mind Matters News podcast, host Robert J. Marks welcomes economics professor and author Gary Smith to discuss the hype around artificial intelligence and its impact on the market. Smith is the Fletcher Jones Professor of Economics at Ponoma College and a frequent contributor to Mind Matters News. Smith argues that generative AI, embodied in services like ChatGPT and Google’s Gemini, exhibits many characteristics of past market bubbles, including excessive hype, lack of profitability, and unrealistic expectations. Smith holds that generative AI models have limited practical economic value. They may be good at finding statistical patterns but struggle to distinguish meaningful, useful correlations from coincidental ones. Smith describes the fundamental challenge of teaching machines true understanding that goes beyond mere pattern recognition. A number of examples and stories are shared throughout.
Smith goes on to explain how current large language models lack true reasoning and creative capabilities, despite regular claims of impending AGI from people like OpenAI’s Sam Altman. He provides examples demonstrating how these models make nonsensical or incorrect responses to logical problems and financial questions, highlighting their inability to understand context and perform meaningful reasoning. He also notes that the “Band-Aid” approach of fixing model failures is not a viable path to achieving AGI.
Additional Resources
- The Promise of Artificial General Intelligence is Evaporating – Mind Matters News
