Recent progress in Artificial Intelligence (AI) and Natural Language Processing (NLP) has greatly increased their presence in everyday consumer products in the last decade. Common examples include virtual assistants, recommendation systems, and personal healthcare management systems, among others. Advancements in these fields have historically been driven by the goal of improving model performance as measured by accuracy, but recently the NLP research community has started incorporating additional constraints to make sure models are fair and privacy-preserving. However, these constraints are not often considered together, which is important since there are critical questions at the intersection of these constraints such as the tension between simultaneously meeting privacy objectives and fairness objectives, which requires knowledge about the demographics a user belongs to. In this workshop, we aim to bring together these distinct yet closely related topics.
We invite papers which focus on developing models that are “explainable, fair, privacy-preserving, causal, and robust” (Trustworthy ML Initiative). Topics of interest include (but are not limited to):
All submissions will be double-blind peer reviewed (with author names and affiliations removed) by the program committee and judged by their relevance to the workshop themes. Submitted manuscripts must be 8 pages long for full papers, and 4 pages long for short papers. Both full and short papers can have unlimited pages for references and appendices. Please note that at least one of the authors of each accepted paper must register for the workshop and present the paper. Template files can be found here: https://www.overleaf.com/latex/templates/naacl-hlt-2021-latex-template/kvjhhyjsvmxf.
We also ask authors to include a broader impact and ethical concerns statement, following guidelines from the main conference.
NAACL workshops are traditionally archival. To allow dual submission of work, we are also including a non-archival track. If accepted, these submissions will still participate and present their work in the workshop. A reference to the paper will be hosted on the workshop website (if desired), but will not be included in the official proceedings. Please submit through softconf but indicate that this is a cross submission at the bottom of the submission form. You can also skip this step and inform us of your non-archival preference after the reviews.
We will follow NAACL’s anonymity policy, and require full anonymity until time of acceptance (April 15, 2021).
To be announced!
For questions, please contact us at firstname.lastname@example.org