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

TL;DR

This paper analyzes the use of the 'dull, dirty, dangerous' motivation in robotics literature from 1980 to 2024, reviews social science insights, and proposes a framework for understanding robotics' impact on human labor.

Contribution

It provides an empirical analysis of DDD mentions in robotics publications, reviews interdisciplinary perspectives, and introduces a framework for contextualizing robotics' societal impact.

Findings

Only 2.7% of publications define DDD.

8.7% of publications give concrete DDD examples.

The proposed framework aids understanding of robotics' labor implications.

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.