In close collaboration with higher education institutions and other partners, the SNSF strives to create the best possible conditions for the development and global interconnectedness of Swiss research. It pays particular attention to the promotion of early-career researchers. In addition, it accepts evaluation mandates to help ensure that large third-party-funded research initiatives deliver the highest scientific quality.
This project develops a participatory design approach for the selection of statistical fairness definitions for machine-learning led applications in the insurance context, with a focus on ethical deliberation within the business context and application of fairness-constrained optimization techniques to concrete products. The project involves collaborations with industry stakeholders in particular data consulting (Zetamind AG) and ethics consulting (Ethix), and in insurances (Axa and Mobiliar).
January 2021 - March 2023
The code is aimed at companies and organizations that offer services or products based on data. Its purpose is to systematically address the ethical issues that arise in the creation or use of such products and services. To this end, concrete recommendations are made, based on three ethical and three procedural values and structured by the four main steps of the data life cycle. The Code is available in German, English, French, and Italian and can be downloaded below. License: CC BY 4.0
Download the code (in English, German, French, and Italian).
September 2019 - December 2019