Women’s health advocates hope that artificial intelligence (AI) can advance our understanding of sex/gender health disparities, since medical research has historically focused on men. However, we lack deep insight into how AI techniques may either reify or destabilize human categories. This limits our understanding of how medical AI may impact conceptualizations of sex and gender, and by extension social equality, in and beyond medicine. To fill this gap, this project draws on feminist Science and Technology Studies to ask: how are categories and facts pertaining to sex and gender constructed and legitimized through the use of medical AI?

In both past and present societies certain groups of girls experience higher levels of mortality than boys, despite female’s pre-determined biologically survival advantage. Theoretical explanations argue that excess female mortality is caused by specific infectious diseases, gendered roles or gender discrimination. However, these theories lack thorough empirical testing. This project focuses on patterns and determinants of excess mortality among girls between 1 and 15 in Maastricht (1864-1930). The project uses individual-level data to examine what caused excess female mortality. Specific attention will be paid to the role of the family, especially that of parents and siblings.

Contemporary fathers want to spend more time with their children but take up parental leave and work part-time less than mothers. It seems like organizational leaders play a key role in these decisions but a theoretical framework and quantitative empirical assessment hereof is lacking. This project provides both. It investigates whether male managers and senior colleagues function as role models for other male employees when they take parental leave or reduce working hours after the birth of their child(ren). Multiple CBS sources with register-data are combined to construct a panel-dataset with employee-manager links in all Dutch SME organizations.

Over 41% of the Dutch population is overweight, a known risk factor for a range of debilitating conditions. Modifying behaviours associated with overweight, such as eating rate, or the speed at which people consume food, could reduce overweight and improve health. Eating rate is a basic determinant of appetite regulation, as people who eat more slowly feel sated earlier and eat less. Unfortunately without assistance, eating rate is difficult to modify due to its highly automatic nature. The current project examines the effectiveness of an innovative product, an augmented fork, to raise awareness of eating rate and help people eat more slowly. This product unobtrusively records behaviour and provides real-time haptic feedback on individual eating rates. Moreover, the fork is paired with applications to provide users with retrospective information about eating rate. We will test the effect of this persuasive technology on eating rate in the laboratory (Study 1) and over time at home (Study 2). The aim of these studies is to test both the short- and long-term effects of the intervention on eating rate and satiation, thus providing experimental evidence on the effectiveness of a persuasive technology to alter a habitual behaviour and support behaviour change. Our studies will lay a foundation for future research on the use of a persuasive technology in the domain of eating behaviour and inform prevention/intervention strategies in the context of overweight and obesity.

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