Claudia Maria Cutrupi is a PhD Candidate at the Department of Computer Science of the Norwegian University of Science
and Technology (NTNU) conducting her doctoral research on Gender Diversity and IT, specifically on
the designing of human-centered intervention that address the lack of diversity in Software Engineering. Send email
Javier Gomez is Associate Professor in the Department of Computer Engineering of the Universidad Autonoma de Madrid
(UAM), Madrid, Spain researching technologies to support people with special needs. Send email
Alicia Julia Wilson Takaoka is a postdoctoral researcher at Erasmus University Rotterdam focusing on AI, data, and
digitalization for an inclusive and fair energy transition. Send email
Past Workshops
Accepted Papers and Abstracts of the Inagural Workshop
A Preliminary Framework for Intersectionality in ML Pipelines
Machine learning (ML) has become a go-to solution for improving how we use, experience, and interact with technology (and the world around us). Unfortunately, studies have shown time and again that machine learning technologies may not be providing adequate support for the range of societal identities and experiences. Intersectionality is a sociological framework that provides a mechanism for the explicit consideration of complex social identities, with a focus on social justice and power. While the framework of intersectionality can support the development of technologies that acknowledge and support all members of society, over the years it has been adopted and adapted in ways that are not always true to its foundations, thereby weakening its potential for impact. To support the appropriate adoption and use of intersectionality for more equitable technological outcomes, we conducted a critical analysis of three existing efforts to incorporate intersectionality into machine learning methodologies. We report on the alignments and misalignments we discovered and how future efforts can properly make use of this socially-relevant framework in the development of their machine learning solutions. https://dl.acm.org/doi/abs/10.1145/3696630.3728692
AI for Empowering Women in AI
Women remain significantly underrepresented in computing and artificial intelligence (AI), facing barriers such as limited access to tools, training, and opportunities. As AI becomes increasingly integral to daily life, it has the potential to address these disparities and foster greater inclusion. Realizing this potential requires fair access, inclusive design, and strategies that actively promote confidence, participation, and representation. This study explores these dimensions, identifying pathways for AI to serve as a catalyst for change. The results show that there is still scarce research explicitly connected to AI artifacts designed for empowerment, but there is a growing recognition of its importance. The SLR also reveals various challenges and success factors related to the role of AI in fostering gender inclusivity and empowerment, which calls for further attention. As further work, the authors will conduct empirical research to validate the findings and gather new insights, while co-designing an artifact to empower women in AI. https://dl.acm.org/doi/abs/10.1145/3696630.3728693
Rethinking Entry Requirements for Gender Diversity in CS Education: A Case Study of Student Performance in an Introductory Programming Course
The gender distribution in computer science (CS) education remains uneven, with a persistent underrepresentation of women. One challenge in improving diversity is that many women choose non-technical tracks in high school, and therefore often lack the required mathematics qualifications for STEM educations.
The purpose of this study was to investigate gender differences in performance and challenges in an introductory programming course and examining the impact of prior experience. The course is part of a CS program with a balanced gender ratio and relatively low mathematical prerequisites compared to similar programs in Sweden, allowing students with backgrounds in social sciences, economics, or humanities to apply. Bringing in students from diverse academic backgrounds may offer valuable perspectives and contribute to a broader understanding of computer science.
The study was based on observations, a survey, and longitudinal statistics of student performance. Our analysis showed that women and men passed the course at equal rates, and struggled with similar learning barriers, regardless of their prior knowledge in mathematics. However, prior experience in programming may have played a role in grade differences, with men tending to achieve higher average grades. These findings raise interesting questions about whether lowering entry requirements, particularly in mathematics, could be a viable approach to improving gender balance in computer science education. https://dl.acm.org/doi/abs/10.1145/3696630.3728694
The Tech DEI Backlash - The Changing Landscape of Diversity, Equity, and Inclusion in Software Engineering
Not long ago, Diversity, Equity, and Inclusion (DEI) initiatives were a top priority for leading software companies. However, in a short period, a wave of backlash has led many firms to re-assess their DEI strategies. Responding to this DEI backlash is crucial in academic research, especially because, currently, little scholarly research has been done on it. In this paper, therefore, we have set forth the following research question (RQ): "How have leading software companies changed their DEI strategies in recent years?" Given the novelty of the RQ and, consequently, the lack of scholarly research on it, we are conducting a grey literature study, examining the current state of DEI initiatives in 10 leading software companies. Based on our analysis, we have classified companies into categories based on their shift in commitment to DEI. We can identify that companies are indeed responding to the backlash by rethinking their strategy, either by reducing, increasing, or renaming their DEI initiatives. In contrast, some companies keep on with their DEI strategy, at least so far, despite the challenging political climate. To illustrate these changes, we introduce the DEI Universe Map, a visual representation of software industry trends in DEI commitment and actions. https://dl.acm.org/doi/abs/10.1145/3696630.3728695
The Impact of Team Diversity in Agile Development Education
Software Engineering is mostly a male-dominated sector, where gender diversity is a key feature for improving equality of opportunities, productivity, and innovation. Other diversity aspects, including but not limited to nationality and ethnicity, are often understudied. In this work we aim to assess the impact of team diversity, focusing mainly on gender and nationality, in the context of an agile software development project-based course. We analyzed 51 teams over three academic years, measuring three different Diversity indexes -- regarding Gender, Nationality and their co-presence -- to examine how different aspects of diversity impact the quality of team project outcomes. Statistical analysis revealed a moderate, statistically significant correlation between gender diversity and project success, aligning with existing literature. Diversity in nationality showed a negative but negligible effect on project results, indicating that promoting these aspects does not harm students' performance. Analyzing their co-presence within a team, gender and nationality combined had a negative impact, likely due to increased communication barriers and differing cultural norms. This study underscores the importance of considering multiple diversity dimensions and their interactions in educational settings. Our findings, overall, show that promoting diversity in teams does not negatively impact their performance and achievement of educational goals. https://dl.acm.org/doi/abs/10.1145/3696630.3728696
