On 13 March 2024, Carlotta Rigotti, postodc researcher at eLaw, and Alexandre Puttick, postdoc researcher at Bern University of Applied Sciences, remotely presented the working paper 'Towards mitigating diversity bias of AI in recruitment and selection' via value sensitive design at the ACM Symposium on Computer Science and Law hosted in Boston. The working paper was also co-authored by Eduard Fosch-Villaronga and Masha Kurpicz-Briki.
The ACM Symposium on Computer Science and Law stands as a premier platform fostering cross-disciplinary discourse where computer science intersects with legal studies. Historically, computer scientists have often viewed law as a set of rigid rules. Conversely, legislators and policymakers have frequently proposed broad, loosely defined regulations, assuming that the tech industry could address any technical challenges arising from compliance. The essence of 'computer science and law' therefore lies in transcending these narrow disciplinary perspectives and embracing interdisciplinary and collaborative approaches to research and development.
In this context, Carlotta and Alex's presentation started from their previous research within the BIAS project. They highlighted a crucial issue: while the European Union considers access to employment as a fundamental element for ensuring equal opportunities, the existing legal framework for equal treatment in employment and occupation falls short in addressing the diversity bias emerging from the growing use of AI applications in the labor market.
This gap in anti-discrimination law led to the exploration of value-sensitive design, a methodology aligning technological design with human values, particularly focusing on the fundamental right to non-discrimination as outlined in Article 21 of the Charter of Fundamental Rights. The presentation showcased a proof of concept for AI-driven recruitment tools that provide clear justifications rooted in EU law. This approach aims to support human decision-making, enhance fairness, and ensure transparency in AI-based hiring processes.
If you're eager to learn more, be sure to stay tuned for additional findings leading up to the final publication.