Cristina Somcutean

The well-documented issues around social bias and the negative environmental impact of ubiquitous machine learning-based artificial intelligence (AI) systems now more than ever motivate critical engagement with the potential dangers of this technology, as well as the conceptualization of research with the goal of reducing harm to marginalized groups and the environment. Previous scholarship has demonstrated how the design of ML models to be used in AI technology is not a neutral endeavor and that ML practitioners must make value judgments at various stages in this process. This thesis asks how it is that ML research can retain a veil of objectivity and how we can conceptualize ML research to facilitate the reduction of harm to marginalized groups and the environment by taking this dynamic into account. From a hybrid queer theory and feminist philosophy of science perspective, I will defend the thesis that due to the current commitment to deep learning (DL) models, a center/margin dichotomy has developed on the terrain of values in ML research, making paradigmatic values that guide decisions in the ML pipeline seem particularly neutral, objective, and apolitical. By problematizing this center/margin dichotomy both through critical analysis and conceptual engineering, we can start imagining ML research beyond the potentially harmful DL paradigm.

Evolutionary psychology (EP) theorizes that contemporary women and men differ psychologically, particularly in mating and sexuality. It is further argued that EP research on gender-specific psychological differences is compatible with feminist perspectives. This paper analyzes if integrating EP scholarship on gender differences into feminist scholarship is possible by investigating EP’s core scientific commitments. I will argue that EP’s theories, hypotheses, and empirical findings that pertain to the study of gender do not align with its core values based on Longino’s feminist theoretical virtues as outlined in the 1996 article “Cognitive and Non-Cognitive Values in Science: Rethinking the Dichotomy.” I employ feminist theoretical virtues as tools for revealing how certain theories, models, and hypotheses rely upon, promote contentious norms, and suppress gender. I will defend the thesis that EP theories, hypotheses, and empirical findings are often empirically inadequate, androcentric, and ontologically too homogeneous. Further, EP employs single-factor control models, has no straightforward practical application, and might even be politically dangerous. These characteristics challenge a successful integration of EP into feminism.