Dull, Dirty, Dangerous: Understanding the Past, Present, and Future of a Key Motivation for Robotics

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Authors: Nozomi Nakajima, Pedro Reynolds-Cuéllar, Caitrin Lynch, Kate Darling
Cited by: 0

Abstract

In robotics, the concept of "dull, dirty, and dangerous" (DDD) work has been used to motivate where robots might be useful. In this paper, we conduct an empirical analysis of robotics publications between 1980 and 2024 that mention DDD, and find that only 2.7% of publications define DDD and 8.7% of publications provide concrete examples of tasks or jobs that are DDD. We then review the social science literature on "dull," "dirty," and "dangerous" work to provide definitions and guidance on how to conceptualize DDD for robotics. Finally, we propose a framework that helps the robotics community consider the job context for our technology, encouraging a more informed perspective on how robotics may impact human labor.

Fields of Study & Subjects

Robotics and Automated Systems Robot Manipulation and Learning Ethics and Social Impacts of AI

Publication details

Journal / source
arXiv (Cornell University)
Publication date
4 February 2026
Document type
Preprint