Filtering by
- All Subjects: ethics
- Creators: Schnebly, Risa Aria
The goal of this research project was to examine how different messaging techniques, and especially expressions of emotionality surrounding the loss and recovery of biodiversity, can differently influence public attitudes about conservation and the environment. This question was explored using the case of de-extinction, an emerging and controversial conservation technology. De-extinction claims to “resurrect” extinct species, challenging widely held notions of extinction as permanent. Yet seeing extinction as reversible may shift how people feel about biodiversity loss and our moral responsibility to stop it.
In the United States, most people are assigned both a biological sex and gender at birth based on their chromosomes and reproductive organs. However, there is an important distinction between biological sex and gender. Biological sex, such as male, female, or intersex, commonly refers to physical characteristics. Gender refers to the socially constructed roles, behaviors, and actions people take on, usually in relation to expectations of masculinity or femininity. As of 2022, there is disagreement over the relation between sex and gender. People’s biological sex and gender greatly influence the way they understand themselves, as well as how others treat them and how they interact with society. Moreover, some people’s gender differs from what they were assigned at birth, and they face discrimination, harassment, and violence. Evolving understandings of gender and sex in the US have created more ways for people to live and express their gender identities.
This thesis seeks to investigate the use of Artificial Intelligence when reviewing STEM job applications and the human biases that are present in AI system training datasets. Further, it proposes to gender neutralize training dataset terms to evaluate job applications based on merit and qualifications, promoting the inclusivity of women in STEM jobs and seeking to eliminate job application system bias from a Utilitarian perspective.