Fairness and Intersectional Non-Discrimination in Human Recommendation (FINDHR)

Algorithmic hiring is the usage of tools based on Artificial intelligence (AI) for finding and selecting job candidates. As other applications of AI, it is vulnerable to perpetuate discrimination. Considering technological, legal, and ethical aspects, the EU-funded FINDHR project was aimed to facilitate the prevention, detection, and management of discrimination in algorithmic hiring and closely related areas involving human recommendation.

New to FINDHR? The project’s main results are summarized in the Toolkits.

We also developed a Training Course on Anti-Discrimination in Algorithmic Hiring.

We engaged with job seekers from minority backgrounds to understand their perceptions and needs of algorithmic hiring. The results of these participatory research actions are summarized in our report on The Hidden Costs of AI Screening.

We produced a series of guidelines for companies developing algorithmic recruiting systems:

Software Development Guide for companies developing recruitment systems
Equality Monitoring Protocol for continuous post-marketing monitoring
Impact Assessment and Auditing Framework for algorithmic auditors
Recommendations and Best Practices for Standardization in Algorithmic Hiring

Specifically for developers, we released the following materials:

If you are a job seeker, we recommend you read:

Reshape Your CV for AI Screening Tools

Researchers and communicators may also be interested in the following:

FINDHR was a member of an AI Fairness cluster, which includes the European projects AEQUITAS, BIAS, and MAMMOTH, all funded by the Horizon Europe program. This cluster plays a key role in the European Commission’s strategy to promote trustworthy AI, with a focus on developing and implementing AI technologies that are human-centric, sustainable, secure, inclusive, and reliable. For more details and information about our events, click here.