Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing
Published in EMNLP 2023 (Findings of the Association for Computational Linguistics), 2023
Recommended citation: Kaffee, L. A., Arora, A., Talat, Z., & Augenstein, I. (2023). Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing. Findings of the Association for Computational Linguistics: EMNLP 2023. https://arxiv.org/abs/2304.08315
Dual use, the intentional, harmful reuse of technology and scientific artefacts, is a problem yet to be well-defined within the context of Natural Language Processing (NLP). However, as NLP technologies continue to advance and become increasingly widespread in society, their inner workings have become increasingly opaque. Therefore, understanding dual use concerns and potential ways of limiting them is critical to minimising the potential harms of research and development. In this paper, we conduct a survey of NLP researchers and practitioners to understand the depth and their perspective of the problem as well as to assess existing available support. Based on the results of our survey, we offer a definition of dual use that is tailored to the needs of the NLP community. The survey revealed that a majority of researchers are concerned about the potential dual use of their research but only take limited action toward it. In light of the survey results, we discuss the current state and potential means for mitigating dual use in NLP and propose a checklist that can be integrated into existing conference ethics-frameworks, e.g., the ACL ethics checklist.