The transcript does not offer a definitive answer to whether machines will become sentient. The speakers extensively discuss the nature of sentience and consciousness, exploring the differences between biological and artificial systems, and debating the potential for AI to achieve these qualities. However, they do not arrive at a conclusive prediction regarding future AI sentience.
This podcast discussion features Joscha Bach and Karl Friston, experts in AI and neuroscience respectively. The conversation centers around consciousness, selfhood, the nature of intelligence (both biological and artificial), and the philosophical implications of these concepts. The discussion progresses from areas of agreement to points of divergence, culminating in a reflection on existential crises stemming from these profound topics.
Inside-Out vs. Outside-In Systems: Biological systems (brains, organisms) are discussed as "inside-out" systems—self-organizing from the bottom up, as opposed to the "outside-in" design of current AI systems. This difference in architecture has significant implications for understanding intelligence and consciousness.
Mortal Computation: The concept of "mortal computation" is introduced, highlighting the importance of the physical substrate in the computational process. This contrasts with the idea of immortal computation (running software on any hardware). Mortality, in this context, is linked to self-organization and the inherent adaptability afforded by life cycles and selective pressure.
The Self and Self-Modeling: The nature of "self" is a central theme, linked to the capacity for self-modeling and agency. The speakers explore whether self-modeling is a necessary component of consciousness and intelligence. They discuss whether multiple, overlapping consciousnesses may coexist within a single mind.
The Role of Curiosity: Curiosity is identified as a crucial element for self-sustaining self-organization and a key aspect of how biological systems adapt and evolve. The conversation examines the tension between exploration (curiosity) and exploitation (utilizing existing knowledge).
AI's Potential and Limitations: While acknowledging AI's impressive capabilities, the speakers address its limitations, particularly in efficiency and the need for more biomimetic approaches. They debate whether current AI, built on Von Neumann architectures, represents the ultimate solution or if more fundamentally different architectures are required.