Ethical by Design: Ethics Best Practices for Natural Language Processing

Natural Language Processing (NLP) systems analyze and/or generate human language, typically on users' behalf. One natural and necessary question that needs to be addressed in this context, both in research projects and in production settings, is the question how ethical the work is, both regarding the process and its outcome. Towards this end, we articulate a set of issues, propose a set of best practices, notably a process featuring an ethics review board, and sketch how they could be meaningfully applied. Our main argument is that ethical outcomes ought to be achieved by design, i.e. by following a process aligned by ethical values. We also offer some response options for those facing ethics issues. While a number of previous works exist that discuss ethical issues, in particular around big data and machine learning, to the authors' knowledge this is the first account of NLP and ethics from the perspective of a principled process.

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