Moral Dilemmas for Artificial Intelligence: a position paper on an application of Compositional Quantum Cognition
This is an incremental step in AI evaluation, aiming to address the gap in current methods that ignore subjective and biased human decision processes.
The paper tackles the problem of evaluating AI systems by proposing a new framework that incorporates human-like emotional and rational reasoning, using compositional quantum cognition to model complex decision-making.
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.