Moral Dilemmas for Artificial Intelligence: a position paper on an application of Compositional Quantum Cognition

TL;DR

This paper advocates for a new approach to evaluating AI by incorporating compositional quantum cognition, aiming to better reflect human-like reasoning, decision-making, and knowledge transfer capabilities.

Contribution

It proposes a novel framework using quantum cognition and categorical compositional models to assess AI's complex, subjective, and emotionally influenced decision processes.

Findings

Introduces a compositional quantum cognition framework for AI evaluation

Highlights the importance of emotional and rational reasoning in AI

Suggests a concrete implementation using recent quantum cognition models

Abstract

Traditionally, the way one evaluates the performance of an Artificial Intelligence (AI) system is via a comparison to human performance in specific tasks, treating humans as a reference for high-level cognition. However, these comparisons leave out important features of human intelligence: the capability to transfer knowledge and make complex decisions based on emotional and rational reasoning. These decisions are influenced by current inferences as well as prior experiences, making the decision process strongly subjective and apparently biased. In this context, a definition of compositional intelligence is necessary to incorporate these features in future AI tests. Here, a concrete implementation of this will be suggested, using recent developments in quantum cognition, natural language and compositional meaning of sentences, thanks to categorical compositional models of meaning.