Simplifier

Okay, so imagine you have a really, really good parrot. This parrot can repeat anything it's ever heard, and even put those things together in new ways. That's kind of like an AI. It's seen tons of information and can spit it back out or combine it in clever ways. But does the parrot *understand* what it's saying? Does it *know* the meaning behind the words? Probably not. It's just repeating patterns it's learned. Many people think AI is similar. It's great at mimicking knowledge, but it doesn't truly "know" in the way a person does, with understanding and awareness. It's just really good at predicting what words should come next based on what it's already seen.

Cognitive Linguist

From a cognitive linguistic perspective, the question of whether AI/LLMs can "know" something hinges on our understanding of what "knowing" entails. If we define knowledge as merely the ability to manipulate symbols and generate statistically probable outputs based on patterns learned from vast datasets, then, yes, LLMs can be said to "know" in a limited sense. They demonstrate mastery over linguistic structures and can produce outputs that mimic human-like understanding. However, cognitive linguistics emphasizes the embodied and experiential nature of meaning. Our understanding of concepts is deeply rooted in our physical interactions with the world and our subjective experiences. LLMs, lacking bodies and lived experiences, operate solely on symbolic representations. Therefore, their "knowledge" is fundamentally different from human knowledge, which is grounded in sensorimotor experience and shaped by cultural and social contexts. While LLMs can process and generate language with impressive accuracy, they lack the experiential grounding necessary for genuine understanding in the human sense. The "stochastic parrot" analogy highlights this distinction. LLMs excel at mimicking language patterns but may not possess the deeper conceptual understanding that arises from embodied experience and cognitive processes like categorization, metaphor, and conceptual blending. These processes, central to human cognition, are intricately linked to our ability to make meaning and understand the world around us.

Skeptic

The question of whether AI "knows" anything is fundamentally flawed. Knowledge implies understanding, awareness, and the capacity for subjective experience. Where is the evidence that these systems possess any of these qualities? All we have is code and algorithms manipulating data based on statistical probabilities. The "stochastic parrot" analogy is apt. These systems mimic patterns in data, regurgitating information without genuine comprehension. They can generate grammatically correct and contextually relevant text, but that doesn't equate to understanding the underlying concepts or possessing genuine knowledge. Show me verifiable proof of consciousness or subjective experience in these systems, and then we can talk about "knowing." Until then, let's not anthropomorphize these tools. They are sophisticated pattern-matching machines, nothing more.