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Call for Papers from the Netherlands Association for Gender Studies and Feminist Anthropology

–International Conference: Ethnographies of Gender and Technology–
Leiden University

The Fifth International Conference of LOVA will focus on gender and (digital) technology. The idea that technology is neutral persists, even after decades of activism exposing male
bias in technologies. This is also becoming clear in emerging technologies, such as artificial intelligence (AI), blockchain, cryptocurrency, Internet of Things (IoT), and facial recognition. For example, Virtual Personal Assistants (such as Siri, Bixby, Alexa) will give gendered answers. AI’s ‘diversity crisis’ has particularly serious consequences for young black men as intransparent algorithms are used to make judgments about job applicants and criminal defendants. Blockchain and cryptocurrencies are predominantly white male industries, and IoT is associated with serious implications for victims and survivors of domestic and sexual violence and abuse as these technologies expand the risks for stalking and surveillance. Furthermore, most commercial facial recognition software contains major flaws when used to identify dark-skinned women. On the other hand, new technologies may also open up new and creative ways to decrease existing inequalities and offer opportunities, such as in women’s health care and queer engagement, but for that we need to make sure that existing biases are not programmed into our new technologies, systems, and infrastructures. The conference aims to critically examine the relationship between gender and technology from perspectives of intersectionality, cyborg theory, assemblage theory and others. How do gender, race and class intersect in emerging technologies? How does technology reshape feminisms through new mediations, articulations and modes of engagements (e.g. Insta Feminism, xenofeminism, call-out/’cancel’ culture etc.). Which methods can help expose bias in new technologies? What role can ethnographers play in uncovering bias, but also in correcting bias?