Case Study 2: Objectives and the Quest for AI

Abstract

This chapter provides a case study in how objectives can hold back progress in a particular field of scientific research. The field of artificial intelligence (AI) focuses on the ambitious aim of creating a human-level computer intelligence, an objective which is fascinating for the profound implications it entails if is ever achieved. Interestingly, viewing the dominant approaches to AI through the myth of the objective illustrates the insidious potential for objectives to deceive even scientific experts. In particular, AI research is guided by perceived progress towards the objective of human-level AI, and the criteria for publishing AI papers are themselves driven by performance and theoretical objectives. While on their surface these incentives seem to make sense, there’s no reason to suspect that the quest for AI is fundamentally different from other systems of innovation or achievement. Thus the chapter suggests non-objective criteria that might productively unseat traditional objective-based incentives in AI research.

The only principle that does not inhibit progress is: anything goes. Paul Feyerabend, Against Method