BIAS at the Applied Machine Learning Days AMLD 2024 in Lausanne, Switzerland

The Applied Machine Learning Days AMLD is a global platform that brings together experts and participants from over 40 countries across industry, academia, and government. The conference is composed of different tracks, addressing dedicated topics. In this year’s edition, members of the BIAS project organized a track around the topic Fairness and Bias in AI Applications for the Labor Market in collaboration with NLP expert Elena Nazarenko from Lucerne University of Applied Sciences.

The track was initiated by a short presentation of the BIAS project by Mascha Kurpicz-Briki, the leader of the technical work package. The objectives, the consortium, and overall idea of the bias project were presented to the audience.

Connecting to this introduction, Eduard Fosch-Villaronga from BIAS partner Leiden University illustrated how designing AI solutions profoundly impacts society and needs a sociotechnical participatory effort incorporating technical, social, economic, political, and legal considerations. He showcased how the different activities in Work Package 2 (Stakeholder involvement, needs assessment, co-creation) supported the BIAS project. For example, the literature review helped the project to look at previous efforts at a theoretical level. The mapping exercise and the expert interviews helped to understand the state of the art and the thinking of professionals working in these areas. Finally, the survey helped the project to map the worker and public attitudes and worries towards automation in the labour market. At the end of the presentation, Eduard encouraged the audience to join the BIAS National Labs.

The session was followed by a talk from Preethi Lahoti from Google Research, discussing AI Safety and Fairness in Large Language Models. As the last speaker of the first session, Alejandro Jesús Castañeira Rodriguez from the company Janzz.technology, presented the technical approaches behind their job matching software. After a well-deserved coffee break, Christoph Heitz from the Zurich University of Applied Sciences (ZHAW) navigated between philosophy and technical solutionism, discussing how to address the sociotechnical nature of fairness and bias in theory and practice. Cynthia Liem from the Delft University of Technology shared experiences and findings of interdisciplinary research collaborations bridging research in the field of AI and the labour market. Finally, two short talks from Jana Mareckova from the University of St. Gallen and Pencho Yordanov from the Adecco Group concluded the session.

Each talk was followed by a Q&A session, and the interested audience engaged actively with the speakers, enabling a rich discussion.

AMLD
Cookies Definitions

BIAS Project may use cookies to memorise the data you use when logging to BIAS website, gather statistics to optimise the functionality of the website and to carry out marketing campaings based on your interests.

They allow you to browse the website and use its applications as well as to access secure areas of the website. Without these cookies, the services you have requested cannot be provided.
These cookies are necessary to allow the main functionality of the website and they are activated automatically when you enter this website. They store user preferences for site usage so that you do not need to reconfigure the site each time you visit it.
These cookies direct advertising according to the interests of each user so as to direct advertising campaigns, taking into account the tastes of users, and they also limit the number of times you see the ad, helping to measure the effectiveness of advertising and the success of the website organisation.

Required cookies They allow you to browse the website and use its applications as well as to access secure areas of the website. Without these cookies, the services you have requested cannot be provided.

Functional Cookies These cookies are necessary to allow the main functionality of the website and they are activated automatically when you enter this website. They store user preferences for site usage so that you do not need to reconfigure the site each time you visit it.

Advertising Cookies These cookies direct advertising according to the interests of each user so as to direct advertising campaigns, taking into account the tastes of users, and they also limit the number of times you see the ad, helping to measure the effectiveness of advertising and the success of the website organisation.