  The use of crowdworkers in NLP research is growing rapidly, in tandem with
the exponential increase in research production in machine learning and AI.
Ethical discussion regarding the use of crowdworkers within the NLP research
community is typically confined in scope to issues related to labor conditions
such as fair pay. We draw attention to the lack of ethical considerations
related to the various tasks performed by workers, including labeling,
evaluation, and production. We find that the Final Rule, the common ethical
framework used by researchers, did not anticipate the use of online
crowdsourcing platforms for data collection, resulting in gaps between the
spirit and practice of human-subjects ethics in NLP research. We enumerate
common scenarios where crowdworkers performing NLP tasks are at risk of harm.
We thus recommend that researchers evaluate these risks by considering the
three ethical principles set up by the Belmont Report. We also clarify some
common misconceptions regarding the Institutional Review Board (IRB)
application. We hope this paper will serve to reopen the discussion within our
community regarding the ethical use of crowdworkers.
