Conceptualization and Framework of Hybrid Intelligence Systems

TL;DR

This paper defines hybrid intelligence systems, presents a framework for understanding human-AI integration, and emphasizes the importance of human factors throughout the AI system lifecycle.

Contribution

It provides a clear conceptualization and framework for hybrid intelligence systems, linking them to related concepts and highlighting their pervasive nature.

Findings

Proposes a precise definition of hybrid intelligence systems.

Introduces a framework based on coupling and directive authority.

Argues all AI systems are inherently hybrid intelligence systems.

Abstract

As artificial intelligence (AI) systems are getting ubiquitous within our society, issues related to its fairness, accountability, and transparency are increasing rapidly. As a result, researchers are integrating humans with AI systems to build robust and reliable hybrid intelligence systems. However, a proper conceptualization of these systems does not underpin this rapid growth. This article provides a precise definition of hybrid intelligence systems as well as explains its relation with other similar concepts through our proposed framework and examples from contemporary literature. The framework breakdowns the relationship between a human and a machine in terms of the degree of coupling and the directive authority of each party. Finally, we argue that all AI systems are hybrid intelligence systems, so human factors need to be examined at every stage of such systems' lifecycle.