"Typically, we evaluate artificial intelligence by capability, which includes things like speed, accuracy, fluency, and even scale. But my take is that this perspective misses something that is both critical and deeply human. Human cognition is fundamentally temporal. We build meaning through continuity, and this includes memory, revision, anticipation, and the lived accumulation of experience. AI does not. It generates coherence entirely inside the present moment."
"For us, meaning is shaped across duration, not inside a single instant. We don't form identity or understanding from isolated frames. We form it from sequence. We don't just learn from a single moment that is compelling or resonant. We learn from many moments that inform and reshape each other. The reliability of our beliefs depends on that slow (emphasis on slow) integration. It's how understanding matures into something stable, or perhaps better said, human."
AI functions in the perpetual present, producing fluent, persuasive outputs without continuity, responsibility for future consequences, or a persisting self. Human cognition relies on temporal continuity: memory, revision, anticipation, and accumulated experience that shape identity and understanding across sequences of moments. Evaluating AI solely by speed, accuracy, fluency, and scale overlooks the temporal difference. AI's statistical coherence can be mistaken for deep understanding because fluency mimics comprehension. The slow integration of experiences is essential to stable beliefs and mature understanding. Adapting human thought processes to machine time risks losing narrative-based, temporal modes of making meaning.
Read at Psychology Today
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