Artificial Intelligence (AI) is increasingly deployed in the labor market to recruit, train, and engage employees or monitor for infractions that can lead to disciplinary proceedings. One type of AI is Natural Language Processing (NLP) based tools that can analyze text to make inferences or decisions. However, NLP-based systems face the implicit biases of the models they are based upon that they learn. Such bias can be already encoded in the data used for machine learning training, which contains our society's stereotypes, and thus be reflected inside the models and the decision-making.

This can lead to partial decisions that run contrary to the European Pillar of Social Rights goals concerning work and employment and the United Nations' Sustainable Development Goals.

Despite a strong desire in Europe to ensure equality in employment, most studies of European labor markets have concluded that there is discrimination across many factors, such as gender, nationality, or sexual orientation. Therefore, addressing how AI used in the labor market contributes to or can help mitigate this discrimination is very important. That is the primary concern of the BIAS project.

Funded by the European Union. The Associated Partner Bern University of Applied Sciences has received funding from the Swiss State Secretariat for Education, Research and lnnovation (SERI).