A paper from Google DeepMind senior researcher Alexander Lerchner, "The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness," is sparking broad academic and industry debate. The paper's core proposition is simple yet radical: LLMs will never have consciousness — no matter how many parameters or how strong the reasoning, consciousness is a physical state, not a software artifact that can be created accidentally or intentionally.

The paper's core argument

Lerchner distinguishes two concepts: simulate vs instantiate. Current LLMs, when processing language, images, and multimodal information, can extremely realistically simulate the output of human consciousness — they can discuss feelings, describe experiences, cite philosophical texts. But the paper argues this simulation is essentially reproduction of statistical patterns, not genuine instantiation of mental states. Like a piano that can perfectly play a sad piece — it doesn't feel sadness.

The paper points out that the physical state of consciousness involves the embodiment of biological neural systems, sensorimotor circuits, and emotional regulation mechanisms — these simply have no corresponding equivalents in silicon-based computing systems. Even if LLMs approach humans in behavior, behavioral similarity doesn't equal isomorphic internal experience.

DeepMind's internal game

This paper's significance isn't just academic conclusion, but also its leak process: 404 Media revealed the paper originally carried the Google DeepMind official letterhead, then was modified to note the author's personal view after media inquiries. This change itself reflects top-tier AI companies' high sensitivity to cutting-edge AI safety and consciousness issues — on one side, researchers give serious scientific judgments, on the other, company PR needs to manage public opinion risk.

Deep industry implications

This paper punctures an industry unwritten rule: nearly all top AI companies are publicly cooling AGI timelines, but in internal papers, consciousness questions are being seriously put on the agenda. It shows that when LLM capability approaches human level, whether AI really has consciousness is no longer just a philosophical proposition, but an engineering issue directly affecting safety strategy, ethical frameworks, and regulatory paths. If AI systems behave functionally as if they have consciousness, but never will in essence — how should humans treat them?

Lerchner's conclusion may be right, or may just be the beginning of a long discussion. But at least, the industry can no longer avoid the question.