Intersectoral Knowledge in AI and Urban Studies: A Framework for Transdisciplinary Research

TL;DR

This paper introduces a six-dimensional framework to evaluate and enhance transdisciplinary knowledge integration in AI and urban studies, addressing challenges in combining diverse epistemic perspectives for societal impact.

Contribution

It proposes a novel framework based on six dimensions to assess and improve the validity of transdisciplinary research in AI and city studies.

Findings

Dominance of critical realism and positivism in current research

Analytical methods and consequentialist approaches are most common

Less frequent but valuable perspectives include idealism and cultural valorization

Abstract

Transdisciplinary approaches are increasingly essential for addressing grand societal challenges, particularly in complex domains such as Artificial Intelligence (AI), urban planning, and social sciences. However, effectively validating and integrating knowledge across distinct epistemic and ontological perspectives poses significant difficulties. This article proposes a six-dimensional framework for assessing and strengthening transdisciplinary knowledge validity in AI and city studies, based on an extensive analysis of the most cited research (2014--2024). Specifically, the framework classifies research orientations according to ontological, epistemological, methodological, teleological, axiological, and valorization dimensions. Our findings show a predominance of perspectives aligned with critical realism (ontological), positivism (epistemological), analytical methods (methodological), consequentialism (teleological), epistemic values (axiological), and social/economic valorization. Less common stances, such as idealism, mixed methods, and cultural valorization, are also examined for their potential to enrich knowledge production. We highlight how early career researchers and transdisciplinary teams can leverage this framework to reconcile divergent disciplinary viewpoints and promote socially accountable outcomes.