Abstract
Women are underrepresented in many spheres of our societies, including research. A common excuse for exclusively male line-ups is that suitable women could not be found. One way of promoting visibility of women in industry and academia is to explicitly provide solutions to find them. Expert Connect is a publicly searchable database of Australia’s researchers that now includes FindHer, a filter to find women experts in any field of research. In this industry paper, we evaluate Natural Language Processing and Computer Vision technologies for gender determination within the aim of automating gender profile tagging for FindHer. We found current off-the-shelf tools are highly effective in detecting gender from names and photos. Nevertheless, a humanin-the-loop approach should be preferred to a fully automatic one, since ethical concerns might arise.
| Original language | English |
|---|---|
| Journal | Proceedings of the Australasian Language Technology Workshop |
| Volume | 17 |
| Publication status | Published - 2019 |
| Event | 17th Annual Workshop of the Australasian Language Technology Association, ALTA 2019 - Sydney, Australia Duration: 4 Dec 2019 → 6 Dec 2019 |
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