On the Computability of Artificial General Intelligence

TL;DR

This paper establishes theoretical upper bounds on artificial general intelligence, proving that no algorithm can generate genuinely new capabilities beyond its initial programming, impacting future AI development and understanding human intelligence.

Contribution

It provides a formal proof that algorithms cannot create truly novel functionalities, defining fundamental limits of AI creativity and innovation.

Findings

No algorithm can demonstrate capabilities not present initially.

AI can only combine or permute existing functionalities.

Implications for AI development and understanding human intelligence.

Abstract

In recent years we observed rapid and significant advancements in artificial intelligence (A.I.). So much so that many wonder how close humanity is to developing an A.I. model that can achieve human level of intelligence, also known as artificial general intelligence (A.G.I.). In this work we look at this question and we attempt to define the upper bounds, not just of A.I., but rather of any machine-computable process (a.k.a. an algorithm). To answer this question however, one must first precisely define A.G.I. We borrow prior work's definition of A.G.I. [1] that best describes the sentiment of the term, as used by the leading developers of A.I. That is, the ability to be creative and innovate in some field of study in a way that unlocks new and previously unknown functional capabilities in that field. Based on this definition we draw new bounds on the limits of computation. We formally prove that no algorithm can demonstrate new functional capabilities that were not already present in the initial algorithm itself. Therefore, no algorithm (and thus no A.I. model) can be truly creative in any field of study, whether that is science, engineering, art, sports, etc. In contrast, A.I. models can demonstrate existing functional capabilities, as well as combinations and permutations of existing functional capabilities. We conclude this work by discussing the implications of this proof both as it regards to the future of A.I. development, as well as to what it means for the origins of human intelligence.