AGI and Reflexivity

TL;DR

This paper explores the concept of reflexivity in intelligent systems, proposing a topological framework that links reflexivity and deliberation, and suggests ways to evaluate AI based on these properties.

Contribution

It introduces a topological property of processes that underpins reflexivity in AI, connecting it to consciousness and deliberation, and proposes a new evaluation approach.

Findings

Reflexivity requires recurrence in process topology.

Topological properties influence the emergence of deliberation.

A framework for evaluating intelligent systems based on reflexivity and deliberation.

Abstract

We define a property of intelligent systems, which we call Reflexivity. In human beings, it is one aspect of consciousness, and an element of deliberation. We propose a conjecture, that this property is conditioned by a topological property of the processes which implement this reflexivity. These processes may be symbolic, or non symbolic e.g. connexionnist. An architecture which implements reflexivity may be based on the interaction of one or several modules of deep learning, which may be specialized or not, and interconnected in a relevant way. A necessary condition of reflexivity is the existence of recurrence in its processes, we will examine in which cases this condition may be sufficient. We will then examine how this topology and this property make possible the expression of a second property, the deliberation. In a final paragraph, we propose an evaluation of intelligent systems, based on the fulfillment of all or some of these properties.