Browsing by Author "Trocin, Cristina"
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- Algorithmic evaluations in breast cancer: the case of Champalimaud FoundationPublication . Trocin, Cristina; Cardoso, Elsa; Mikalef, PatrickAlgorithmic evaluations are increasingly used to make decisions thanks to the perception of objective measures of quality and performance. However, little is known about how the current evaluation methods change with ML algorithms and with what consequences for the actors and organizations being evaluated. We conducted an exploratory case study in the breast unit of the Champalimaud Foundation in Lisbon. Gioia methodology guided the collection and analysis of semi-structured interviews and archival data. Our results show that besides generating visible and direct changes (e.g., extraction and quantification of relevant criteria with systematic approaches), algorithmic evaluations trigger indirect and less visible dynamics (e.g., adding a new dimension - aesthetic score – in the evaluation of research units), which have profound implications on how institutions operate and how resources are allocated based on the ranking lists. We contribute to digital undertow and institutional displacement and human ML collaborations by explaining the processes through which the new methods are used in medical communities and their less visible yet impactful consequences.
- GenAI for sustainable development: an inductive analysis of international organizationsPublication . Faria, Beatriz Manuel; Trocin, CristinaGenerative AI (GenAI) presents significant potential to address sustainability challenges. By offering solutions for resource efficiency, strategic decision-making, and aligning practices with sustainable development goals (SDGs), GenAI enables organizations to harmonize environmental preservation, economic growth, and societal values. Despite its promise, achieving sustainability with GenAI requires a holistic approach that considers its life cycle, including design, training, validation, implementation, and use, to address energy consumption and resource efficiency challenges. Existing research provides limited insight into the processes and strategies organizations use to integrate GenAI effectively for sustainable development. We bridge the gap by conducting an exploratory case study examining the influence of GenAI on sustainable development within international organizations. The findings aim to enhance understanding of GenAI’s dual role in driving sustainability efforts and ensuring its own sustainable implementation, contributing to environmentally and socially responsible organizational practices.