Abstract
Modern-day technology is a product of decades of evolution. Over time as new technologies and concepts emerged, so did new terminology to describe and discuss them. While the landscape of individuals who develop technology has diversified over the years, the terminology has become a normalized part of modern software development and computing jargon. Despite organizations such as the ACM raising awareness of the potential harm certain terms can do and companies like Github working to change the systemic use of harmful terms in computing, it is still not clear what the landscape of harmful terminology in computing really is and how we can support the detection and correction of harmful terminology in computing artifacts. To this end, we conducted a literature review of existing work and efforts at curating, detecting, and removing harmful terminology. Building on these prior efforts, we implemented a proof-of-concept tool that detects and replaces harmful computing-related terminology in documents. Given the shortage of datasets on harmful terminology in computing, we will expand on this work in the future by exploring the potential for Natural Language Processing models to detect potentially harmful terms and phrases.
How to Cite:
, H., , A. & , B.,
(2022) “Harmful Terms in Computing: Detection and Correction”,
Journal of Student-Scientists' Research 4.
doi: https://doi.org/10.13021/jssr2022.3431
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