Toward a human–AI task tensor: a taxonomy for organizing work in the age of generative AI

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Authors: Anil Rajnikant Doshi, Alastair P. Moore
Cited by: 0

Abstract

We introduce a framework for understanding the impact of generative AI on human work, which we call the human-AI task tensor. A tensor is a structured framework that organizes tasks along multiple interdependent dimensions. Our human-AI task tensor introduces a systematic approach to studying how humans and AI interact to perform tasks, and has eight dimensions: task definition, AI integration, interaction modality, audit requirement, output definition, decision-making authority, AI structure, and human persona. After describing the eight dimensions of the tensor, we provide illustrative frameworks (derived from projections of the tensor) and a human-AI task canvas that provide analytical tractability and practical insight for organizational decision-making. We demonstrate how the human-AI task tensor can be used to organize emerging and future research on generative AI. We propose that the human-AI task tensor offers a starting point for understanding how work will be performed with the emergence of generative AI.

Fields of Study & Subjects

Ethics and Social Impacts of AI Personal Information Management and User Behavior Explainable Artificial Intelligence (XAI)

Publication details

Journal / source
Edward Elgar Publishing eBooks
Pages
124–142
Publication date
17 March 2026
Language
EN
Document type
Book chapter