AI - is it really intelligent?
Posted: Thu Jul 31, 2025 8:54 am
The term "artificial intelligence" is often misleading. Intelligence, in its truest sense, implies not just the ability to compute or process information but to understand—to grasp meaning, truth, and context. Current AI systems, despite their sophistication, lack this essential quality. They do not understand the rules they follow, nor the reasons behind them. This distinction lies at the heart of Roger Penrose’s critique, which draws upon Gödel’s incompleteness theorems. Gödel demonstrated that in any formal system capable of arithmetic, there exist true statements that cannot be proven within the system itself. These truths require a form of insight or understanding that transcends mechanical rule-following.
Penrose argues that a conscious human mathematician can see why certain rules lead to truth, and why others do not. This capacity to "see" or grasp truth is not simply a function of computational power; it is an act of understanding that requires consciousness. A machine may simulate reasoning, but it cannot know why a proof is true. This knowing—this internal awareness—is fundamental to intelligence, and it is precisely what machines lack.
This idea resonates with Hans-Georg Gadamer’s conception of understanding in the human sciences. For Gadamer, understanding is not the extraction of information through methodical procedures. It is a dialogical process, shaped by history, tradition, and the interpreter’s own preconceptions. Understanding emerges not through calculation but through engagement—a “fusion of horizons” between the self and the other, between the present and the past. Meaning is not a fixed object to be retrieved but something that unfolds within the interpretive act.
Both thinkers thus critique the reduction of understanding to algorithm. Penrose uses mathematical logic to show that computation has intrinsic limits, while Gadamer uses philosophical hermeneutics to show that meaning arises only through situated, conscious participation. Together, they challenge the assumption that machines, no matter how advanced, can truly understand. They remind us that while AI may replicate the form of intelligent behavior, it cannot replicate the essence—the conscious, interpretive, and transcendent nature of human thought.
https://youtu.be/e9484gNpFF8?si=4TFTePGRS2XiFE2A
Penrose argues that a conscious human mathematician can see why certain rules lead to truth, and why others do not. This capacity to "see" or grasp truth is not simply a function of computational power; it is an act of understanding that requires consciousness. A machine may simulate reasoning, but it cannot know why a proof is true. This knowing—this internal awareness—is fundamental to intelligence, and it is precisely what machines lack.
This idea resonates with Hans-Georg Gadamer’s conception of understanding in the human sciences. For Gadamer, understanding is not the extraction of information through methodical procedures. It is a dialogical process, shaped by history, tradition, and the interpreter’s own preconceptions. Understanding emerges not through calculation but through engagement—a “fusion of horizons” between the self and the other, between the present and the past. Meaning is not a fixed object to be retrieved but something that unfolds within the interpretive act.
Both thinkers thus critique the reduction of understanding to algorithm. Penrose uses mathematical logic to show that computation has intrinsic limits, while Gadamer uses philosophical hermeneutics to show that meaning arises only through situated, conscious participation. Together, they challenge the assumption that machines, no matter how advanced, can truly understand. They remind us that while AI may replicate the form of intelligent behavior, it cannot replicate the essence—the conscious, interpretive, and transcendent nature of human thought.
https://youtu.be/e9484gNpFF8?si=4TFTePGRS2XiFE2A