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Clàudia Figueras Julián

About me

I am a doctoral student at Stockholm University (Sweden) 's Department of Computer and Systems Sciences (DSV) at Stockholm University (Sweden). My research focuses on the practical implementation of AI ethics. Specifically, I investigate how AI practitioners interpret and address ethical issues in their everyday work practices. By exploring diverse perspectives, I aim to shed light on the challenges faced and the strategies practitioners employ in this domain. My work is at the intersection of technology ethics, CSCW, critical data studies, and STS.

In my qualitative research, I have conducted semi-structured, in-depth interviews with various expert stakeholders, and I am open to utilizing additional methods such as focus groups, workshops, and observations to gain deeper insights. Through my work, I strive to uncover new perspectives and contribute to the evolving field of AI ethics.

Prior to pursuing my PhD, I earned an MSc in Health Informatics from Karolinska Institutet and Stockholm University, as well as a BSc in Human Biology from Universitat Pompeu Fabra. These interdisciplinary educational experiences have equipped me with a strong foundation in both technical and human-centred approaches.

Before embarking on my doctoral studies, I worked as a data scientist and data analyst in the public and private sectors. This practical experience has given me a valuable understanding of real-world AI implementation and the ethical challenges in these contexts.

I am passionate about bridging the gap between theory and practice in AI ethics and aim to contribute to the development of ethical frameworks and guidelines that can positively shape AI-driven technologies.

Research projects

Publications

A selection from Stockholm University publication database

  • Exploring tensions in Responsible AI in practice. An Interview Study on AI practices in and for Swedish Public Organizations

    2022. Clàudia Figueras Julián, Harko Henricus Verhagen, Teresa Cerratto-Pargman. Scandinavian Journal of Information Systems 34 (2), 199-232

    Article

    The increasing use of Artificial Intelligence (AI) systems has sparked discussions regarding developing ethically responsible technology. Consequently, various organizations have released high-level AI ethics frameworks to assist in AI design. However, we still know too little about how AI ethics principles are perceived and work in practice, especially in public organizations. This study examines how AI practitioners perceive ethical issues in their work concerning AI design and how they interpret and put them into practice. We conducted an empirical study consisting of semi-structured qualitative interviews with AI practitioners working in or for public organizations. Taking the lens provided by the “In-Action Ethics” framework and previous studies on ethical tensions, we analyzed practitioners’ interpretations of AI ethics principles and their application in practice. We found tensions between practitioners’ interpretation of ethical principles in their work and ‘ethos tensions.’ In this vein, we argue that understanding the different tensions that can occur in practice and how they are tackled is key to studying ethics in practice. Understanding how AI practitioners perceive and apply ethical principles is necessary for practical ethics to contribute toward an empirically grounded, Responsible AI.

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  • Trustworthy AI for the People?

    2021. Clàudia Figueras Julián, Harko Henricus Verhagen, Teresa Ceratto Pargman. AIES '21, 269-270

    Conference

    While AI systems become more pervasive, their social impact is increasingly hard to measure. To help mitigate possible risks and guide practitioners into a more responsible design, diverse organizations have released AI ethics frameworks. However, it remains unclear how ethical issues are dealt with in the everyday practices of AI developers. To this end, we have carried an exploratory empirical study interviewing AI developers working for Swedish public organizations to understand how ethics are enacted in practice. Our analysis found that several AI ethics issues are not consistently tackled, and AI systems are not fully recognized as part of a broader sociotechnical system.

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