Kleiner Johannes, Ludwig Tim
Munich Center for Mathematical Philosophy, Ludwig Maximilian University of Munich, Geschwister-Scholl-Platz 1, Munich 80539, Germany.
Munich Graduate School of Systemic Neurosciences, Ludwig Maximilian University of Munich, Großhaderner Str. 2, Planegg-Martinsried 82152, Germany.
Neurosci Conscious. 2024 Dec 26;2024(1):niae037. doi: 10.1093/nc/niae037. eCollection 2024.
We apply the methodology of no-go theorems as developed in physics to the question of artificial consciousness. The result is a no-go theorem which shows that under a general assumption, called dynamical relevance, Artificial Intelligence (AI) systems that run on contemporary computer chips cannot be conscious. Consciousness is dynamically relevant, simply put, if, according to a theory of consciousness, it is relevant for the temporal evolution of a system's states. The no-go theorem rests on facts about semiconductor development: that AI systems run on central processing units, graphics processing units, tensor processing units, or other processors which have been designed and verified to adhere to computational dynamics that systematically preclude or suppress deviations. Whether our result resolves the question of AI consciousness on contemporary processors depends on the truth of the theorem's main assumption, dynamical relevance, which this paper does not establish.
我们将物理学中发展起来的不可行定理方法应用于人工意识问题。结果是一个不可行定理,该定理表明,在一个被称为动态相关性的一般假设下,运行在当代计算机芯片上的人工智能(AI)系统不可能有意识。简单地说,如果根据一种意识理论,意识与系统状态的时间演化相关,那么意识就是动态相关的。这个不可行定理基于半导体发展的事实:人工智能系统运行在中央处理器、图形处理器、张量处理器或其他经过设计和验证以遵循系统地排除或抑制偏差的计算动力学的处理器上。我们的结果是否解决了当代处理器上的人工智能意识问题,取决于该定理主要假设——动态相关性——的真实性,而本文并未证实这一点。