Innateness, AlphaZero, and Artificial Intelligence

TL;DR

This paper critiques the claims of AlphaZero's training without innate knowledge, emphasizing the importance of innateness in AI development and proposing future directions for integrating innate features.

Contribution

It challenges the overstated claims of AlphaZero's innate capabilities and advocates for increased focus on innateness in artificial intelligence research.

Findings

AlphaZero's training claims are overstated.

Innateness plays a crucial role in AI development.

Proposes new directions for innate features in AI.

Abstract

The concept of innateness is rarely discussed in the context of artificial intelligence. When it is discussed, or hinted at, it is often the context of trying to reduce the amount of innate machinery in a given system. In this paper, I consider as a test case a recent series of papers by Silver et al (Silver et al., 2017a) on AlphaGo and its successors that have been presented as an argument that a "even in the most challenging of domains: it is possible to train to superhuman level, without human examples or guidance", "starting tabula rasa." I argue that these claims are overstated, for multiple reasons. I close by arguing that artificial intelligence needs greater attention to innateness, and I point to some proposals about what that innateness might look like.