Women in Big Data
In Switzerland, fewer than half of all STEM subject (life sciences, technology, engineering, and math) students are women. It is important to have an open and broader discussion on building, advancing, and maintaining careers for women in STEM fields and other disciplines that rely on technology and maths. The present cross cutting activity intends to analyse the position of women in the field of big data technologies together with all projects of NRP 75.
Portrait (completed research project)
In the recent decade, a variety of public and private initiatives have addressed the uneven gender distribution with regard to jobs remotely technical. Some focus on offering particular training and mentoring for girls and young female adults so that they are more likely to enter and stay in jobs with technological and mathematical affinities. Yet research also indicates that male dominated and inflexible work cultures refrain women from entering and staying. Media reports also indicate discrimination in pay and promotion as well as sexual harassment in tech firms. The cross cutting activity wanted to promote an open and broader discussion on building, advancing, and maintaining careers for women in fields that rely on technology and math.
In Switzerland, fewer than half of all STEM subject students are women. This holds for all levels of university training and is particularly pronounced in computer and information sciences, math, and engineering. Across the globe, women account for less than a third of those employed in scientific research and development; women are less likely to enter and more likely to leave tech-intensive business roles.
The objective of the cross cutting activity was to provide a networking forum to connect women in industry and academia, to learn about career challenges and solutions from each other, to discuss how to excel in Big Data challenges, to collaborate across different disciplines, and to further advance and explore careers in the digital era.
Only a minority of NRP 75 projects are led by women. “Women in Big Data” allows strengthening women in the field and to advance their research and careers. Issues of structural inequality and discrimination unite women’s experiences across all disciplines. This initiative offered a forum to identify patterns, discuss strategies as well as promote each other in exciting and inspiring research. For instance, it also addressed how gender biases enter big data research and its applications.
The tangible outcome of this cross cutting activity is the platform www.wibd.ch that supports women in big data research. It started with an international workshop (June 2018, Zurich) which was followed by other, smaller events with a more narrow focus, as for example thematic roundtables with career development foci.
Three annual workshops and a series of student-organised events have been planned in the original proposal. Due to the outbreak of COVID-19 in 2020, adaptations were necessary as follows: Two instead of three international workshops have been organised, one in 2019 (70 participants) and one in 2022 (56 participants). Five student-organised events took place on the topics “AI and Cities”, “Coding, Career, Community”, “Big Data in Communication Science”, “Ethical, Social and Legal Challenges of Big Data”, and “Algorithms in the Making”. One student event was cancelled due to the pandemic. To compensate, five online training courses have been organised on the topics “Taking the Lead in Conversations”, “Medien Schreibwerkstatt für Forschende”, “Technical Writing workshop”, “Taming the Inner Critic” and “Negotiation Techniques”.
In addition to the networking and knowledge transferring events, research and scientific activities around gender issue in big data were started by investigating how different gender gain influence in the social media by mining through the big data of the Instagram, which was collected by a collaborator at University of Columbia. The structure properties behind the unbalanced gender influence in modern social networks were characterised and gender-aware seeding algorithms were designed with which information spread on social media can reach certain gender target ratio. The work resulted in two research papers.
Initiative of Women in Big Data (WiBD)