by Jochen Szangolies

Recently, the exponential growth of AI capabilities has been outpaced only by the exponential growth of breathless claims about their coming capabilities, with some arguing that performance on par with humans in every domain (artificial general intelligence or AGI) may only be seven months away, arriving by November of this year. My purpose in this article is to examine the plausibility of this claim, and, provided ‘AGI’ includes the ability to know what you’re talking about, find it wanting. I will do so by examining the work of British philosopher and logician Bertrand Russell—or more accurately, some objections raised against it.

Russell was a master of structure in more ways then one. His writing, the significance of which was recognized with the 1950 Nobel Prize in literature, is often a marvel of clarity and coherence; his magnum opus Principia Mathematica, co-written with his former teacher Alfred North Whitehead, sought to establish a firm foundation for mathematics in logic. But for our purposes, the most significant aspect of his work is his attempt to ground scientific knowledge in knowledge of structure—knowledge of relations between entities, as opposed to direct acquaintance with the entities themselves—and its failure as originally envisioned.

Structure, in everyday parlance, is a bit of an inexact term. A structure can be a building, a mechanism, a construct; it can refer to a particular aspect of something, like the structure of a painting or a piece of music; or it can refer to a set of rules governing a particular behavioral domain, like the structure of monastic life. We are interested in the logical notion of structure, where it refers to a particular collection of relations defined on a set of not further specified entities (its domain).

It is perhaps easiest to approach this notion by means of a couple of examples. Read more »