AI Must Embrace Specialization via Superhuman Adaptable Intelligence

TL;DR

This paper argues that AI should focus on developing specialized, superhuman capabilities in specific areas rather than pursuing a vague and potentially flawed concept of general intelligence, introducing the idea of Superhuman Adaptable Intelligence (SAI).

Contribution

It proposes the concept of SAI, emphasizing specialization and superhuman performance in AI, challenging traditional AGI notions and guiding future AI development strategies.

Findings

SAI can surpass human abilities in key skills.

Specialization leads to more practical AI advancements.

Reframing AI goals around SAI clarifies future directions.

Abstract

Everyone from AI executives and researchers to doomsayers, politicians, and activists is talking about Artificial General Intelligence (AGI). Yet, they often don't seem to agree on its exact definition. One common definition of AGI is an AI that can do everything a human can do, but are humans truly general? In this paper, we address what's wrong with our conception of AGI, and why, even in its most coherent formulation, it is a flawed concept to describe the future of AI. We explore whether the most widely accepted definitions are plausible, useful, and truly general. We argue that AI must embrace specialization, rather than strive for generality, and in its specialization strive for superhuman performance, and introduce Superhuman Adaptable Intelligence (SAI). SAI is defined as intelligence that can learn to exceed humans at anything important that we can do, and that can fill in the skill gaps where humans are incapable. We then lay out how SAI can help hone a discussion around AI that was blurred by an overloaded definition of AGI, and extrapolate the implications of using it as a guide for the future.