Clifford Pickover (What to think about machines that think)

Clifford Pickover explores the concept of machine consciousness and the potential for machines to think and know things. He suggests that if thinking and consciousness are the result of patterns in brain cells, these patterns could potentially be replicated in other systems, such as moving assemblies of bicycle parts or natural phenomena like tree limbs or termite movements.

Pickover categorizes knowledge into different types, including factual or propositional knowledge, procedural knowledge (knowing how to do something), and direct experiential knowledge (knowledge gained through personal experience). He acknowledges the importance of human-like interaction for considering a machine as having human-like intelligence.

He envisions a future where computers or computer-human hybrids become so advanced that they exhibit emotions and merge with humans. In this future, individuals may create multiple simulated lives and explore various realities, from historical events with slight changes to producing great artworks or solving complex scientific problems.

However, Pickover also acknowledges that machines may think differently from humans, as they don’t perceive the world in the same way. For instance, image recognition algorithms can sometimes misinterpret random static as depictions of animals, raising questions about the limitations and potential pitfalls of machine thinking.

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