Don't Forget Imagination!

TL;DR

This paper emphasizes the importance of cognitive imagination in human reasoning and advocates for its integration into AI, proposing semantic models as a promising approach to simulate this faculty.

Contribution

It introduces semantic models as a novel, probabilistic causal framework to simulate cognitive imagination in AI systems.

Findings

Semantic models ensure consistency of imaginary contexts.

They enable manipulation of holistic, coherent systems of facts.

Semantic models can learn similarly to neural networks.

Abstract

Cognitive imagination is a type of imagination that plays a key role in human thinking. It is not a ``picture-in-the-head'' imagination. It is a faculty to mentally visualize coherent and holistic systems of concepts and causal links that serve as semantic contexts for reasoning, decision making and prediction. Our position is that the role of cognitive imagination is still greatly underestimated, and this creates numerous problems and diminishes the current capabilities of AI. For instance, when reasoning, humans rely on imaginary contexts to retrieve background info. They also constantly return to the context for semantic verification that their reasoning is still reasonable. Thus, reasoning without imagination is blind. This paper is a call for greater attention to cognitive imagination as the next promising breakthrough in artificial intelligence. As an instrument for simulating cognitive imagination, we propose semantic models -- a new approach to mathematical models that can learn, like neural networks, and are based on probabilistic causal relationships. Semantic models can simulate cognitive imagination because they ensure the consistency of imaginary contexts and implement a glass-box approach that allows the context to be manipulated as a holistic and coherent system of interrelated facts glued together with causal relations.