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Ethics for NLP – natural language processing

Research group
Active research
Project period
2023 - ongoing
Project owner
Department of Philosophy, Linguistics and Theory of Science

Short description

We are an interest group on ethics in research and teaching in natural language processing. Topics that we have addressed are biases in training data, biases in computational models, personal integrity (anonymisation and pseudonymisation of data), intellectual property rights, using language technology tools to detect non-ethical language use, utilising language technology in under-resourced domains and communities (e.g. minority languages), legal aspects of using language technology, philosophical questions, and others.

We are an open community and encourage exchange of experiences and ideas in our teaching and research.

Coordinators

We are three coordinators in Sweden:

Hannah Devinney, Umeå University
Link to Hannah's contact information

Simon Dobnik, University of Gothenburg – contact person for general questions
Link to Simon's contact information

Beáta Megyesi, Stockholm University
Link to Beáta's contact information

Activities and events

In 2023 the group received funding from the council of vice-chancellors of Gothenburg, Lund, Stockholm, Umeå and Uppsala universities (SLUGU), with additional financial support of Department of Philosophy, Linguistics and Theory of Science (FLoV), University of Gothenburg, to organise a workshop – Ethics for NLP – to be held in Gothenburg on 23 January 2024.
External link to the workshop

Purpose and aims

AI tasks related to modelling human language and that focus on decision making (such as identification of patient diagnoses and driving) have developed substantially over the last several years. In many areas it has been claimed that AI learning from data alone has achieved human-like performance, sometimes even better, but due to the nature of these models it is very hard to inspect directly what such models have learned. Instead, we can only observe their performance, which might be biased in one or more ways, and which has societal and environmental implications.

Language technology (also known as computational linguistics or natural language processing) is an interdisciplinary field between linguistics, psychology, cognitive science and computer science that deals with building computational models which can behave as if they understand natural language. Due to the aforementioned developments, a need has been identified by developers, researchers and teachers of language technology that ethical issues related to data collection, training and usage of such models in various real-life applications should also be addressed. We should equip ourselves as researchers, teachers and students with understanding about the impacts of using such technology or to promote ethically-aware research and utilisation.

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