On April 28, Hannah Devinney presented a talk on Gender Bias in Natural Language Processing at AI Sweden’s Swedish NLP Webinar series, which focuses on NLP development in Sweden and/or about the Swedish language.
The talk focuses on gendered aspects of “bias”: exploring what it is, how it manifests in NLP, the harms it causes, and what we as NLPers can do to combat these harms. Their presentation was followed by an engaging discussion on the nature and future of “unbiased” NLP. We hope that this talk will lead to increased awareness in the AI community of the importance of intersectional and inclusive models of gender for mitigating bias.
A recording of the talk can be found in the video embedded below.
AI-driven advertising is often presented as one of the main successes of deep learning, after heavy investments in machine learning algorithms that discover and exploit patterns in consumer behaviour. In a new project financed the Marcus and Marianne Wallenberg Foundation, researchers from Umeå University, Malmö University, Stockholm School of Economics, and the University of Gothenburg collaborate to understand the implications for citizens and society linked to different types of targeting methods used in online advertising.
In December 2020, WASP launched a new research arena to place Media AI at the centre of a multidisciplinary ecosystem of scientific fields and industry segments. The arena is a recognition of the value of media AI in process automation, for example, in the facilitation of remote control in forestry, in the creation of virtual verification environments for autonomous machinery and in the generation of non-playable characters in gaming.
On Monday the 29th of September, Hannah Devinney presented the EQUITBL project at the AI for Good Breakthrough Days main stage event. The project is one of three winners in the Breakthrough Days’ Gender Equity Track.
This interdisciplinary project explores ways of combining qualitative and quantitative methods in order to explore and understand how bias and stereotypes manifest themselves in large text collections, such as those commonly used to train machine learning models in language technology. We also develop tools for mitigating the detrimental effects bias, stereotyping, and underrepresentation can have when the ML models are integrated into AI systems used for decision making.
The project members are:
Hannah Devinney, Computing Science, Centre for Gender Studies, and LPCN, Umeå University
Henrik Björklund, Computing Science and LPCN, Umeå University
Jenny Björklund, Centre for Gender Research, Uppsala University
In the afternoon of March 20, a number of LPCN members had a workshop together with Humlab on the topic of text analysis. We all presented how we use or plan to use text analysis in our work. Happily, we managed to identify a number of immediate collaboration opportunities and also discussed the possibilities for building a joint text analysis infrastructure. As an additional benefit, the LPCN family grew substantially! The workshop concluded with a very nice after work session.
Professor Thomas Hellström’s research deals with teaching robots to act and to communicate. One of his projects deals with developing methods for intention recognition from verbal utterances. Here’s a video about Thomas Hellström and his research.
LPCN members Michele Persiani and Maitreyee Tewari also participated and presented at ‘Robots for Assisted Living Workshop’ in IROS-2018. Maitreyee’s research focuses on building and implementing hybrid (machine learning and formal grammars) dialogue models for communication between robots and humans, While Michele builds deep learning based models for intention recognition from natural language. They presented their on-going research to one of the workshops and below are glimpses of the same.
PhD students Michele Persiani and Maitreyee Tewari recently participated in the organization of The 1st PhD International Conference on Safe and Social Robotics (SSR-2018) http://www.socrates-project.eu/sesoro-2018/ in Madrid Spain. The conference was a collaboration between two H2020 Projects SECURE and SOCRATES.
On Wednesday, LPCN’s Anna Jonsson visited a group of young and fantastic women all enrolled in Teknikprogrammet at Dragonskolan. The mission was to recruit as many (future) PhD students as possible. The first step was to tell them what a PhD student is and does; the second step was to get them interested in choosing a computer science programme at the University after finishing high school. Sadly, Anna immediately scared them off by introducing formal grammars (as usual). At least the attendants got a great deal of fika for the trouble from the awsome woman (also named Anna) who organises these tech-for-girls meetings. Better luck with the recruitment next time!