The Paradigm Shifts in Artificial Intelligence
This provides a historical and theoretical perspective on AI progress, relevant for researchers and policymakers, but is incremental as it applies an existing framework to AI.
The paper analyzes paradigm shifts in AI over 60 years using Kuhn's framework, focusing on the current shift driven by large pre-trained systems like GPT-3 and ChatGPT, which commoditize intelligence as a general-purpose technology, and discusses associated risks and issues.
Kuhn's framework of scientific progress (Kuhn, 1962) provides a useful framing of the paradigm shifts that have occurred in Artificial Intelligence over the last 60 years. The framework is also useful in understanding what is arguably a new paradigm shift in AI, signaled by the emergence of large pre-trained systems such as GPT-3, on which conversational agents such as ChatGPT are based. Such systems make intelligence a commoditized general purpose technology that is configurable to applications. In this paper, I summarize the forces that led to the rise and fall of each paradigm, and discuss the pressing issues and risks associated with the current paradigm shift in AI.