---
title: "On the Thresholds of Knowledge"
authors:
  - "Douglas B. Lenat"
  - "Edward A. Feigenbaum"
doi: ""
url: "https://ijcai.org/proceedings/1987/240"
pdf: "https://ijcai.org/proceedings/1987/0240.pdf"
venue: "Proceedings of the Tenth International Joint Conference on Artificial Intelligence"
year: 1987
pages: "1173-1181"
track: "Panels and Invited Talks"
keywords:
---

# On the Thresholds of Knowledge

Douglas B. Lenat, Edward A. Feigenbaum

*Proceedings of the Tenth International Joint Conference on Artificial Intelligence*, pages 1173-1181.

## Abstract

We articulate the three major findings of AI to date: (1) The Knowledge Principle: if a program is to perform a complex task well, it must know a great deal about the world in which it operates. (2) A plausible extension of that principle, called the Breadth Hypothesis: there are two additional abilities necessary for intelligent behavior in unexpected situations: falling back on increasingly general knowledge, and analogizing to specific but far-flung knowledge. (3) AI as Empirical Inquiry: we must test our ideas experimentally, on large problems. Each of these three hypotheses proposes a particular threshold to cross, which leads to a qualitative change in emergent intelligence. Together, they determine a direction for future AI research.