Wisdom for the Crowd: Discoursive Power in Annotation Instructions for Computer Vision

• URL: http://arxiv.org/abs/2105.10990v1
• Date: Sun, 23 May 2021 18:20:39 GMT
• Title: Wisdom for the Crowd: Discoursive Power in Annotation Instructions for Computer Vision
• Authors: Milagros Miceli and Julian Posada
• Abstract summary: This paper focuses on the experiences of Argentinian and Venezuelan data annotators. Our findings indicate that annotation instructions reflect worldviews imposed on workers and, through their labor, on datasets. This configuration presents a form of commodified labor that perpetuates power asymmetries while reinforcing social inequalities.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Developers of computer vision algorithms outsource some of the labor involved in annotating training data through business process outsourcing companies and crowdsourcing platforms. Many data annotators are situated in the Global South and are considered independent contractors. This paper focuses on the experiences of Argentinian and Venezuelan annotation workers. Through qualitative methods, we explore the discourses encoded in the task instructions that these workers follow to annotate computer vision datasets. Our preliminary findings indicate that annotation instructions reflect worldviews imposed on workers and, through their labor, on datasets. Moreover, we observe that for-profit goals drive task instructions and that managers and algorithms make sure annotations are done according to requesters' commands. This configuration presents a form of commodified labor that perpetuates power asymmetries while reinforcing social inequalities and is compelled to reproduce them into datasets and, subsequently, in computer vision systems.

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