My doctoral dissertation explores the shortcomings of AI Judges, that is, when artificial intelligence is used to generate the legal verdicts of cases. Due to blackboxing and proprietary rights, it is not possible for a researcher to study how AI Judge models and other automated technologies are being built by states or private tech companies. To bypass this issue, I started building a prototype AI Judge model to have a hands-on approach, allowing for a more immersive means to understand the possibilities and limitations of code/coding. My NYU Digital Humanities project – “Prototyping as Ethnography” – is a paper that bridges the methods of Digital Humanities and Anthropology to conceptualize how ethnography can be broadened to include prototyping. The goal of this project was not to create the “perfect” AI Judge model, but rather having an immersive and hands-on approach to engaging with programming language and learn how code “behaves.” My method is connected to anthropologists Rabinow and Bennet’s work on how participant observation can include researchers conducting their own experiments in the laboratory. I also draw from Galloway’s method of ‘algorithmic reenactment’ which promotes re-enacting code from archives and Hartman’s ‘critical fabulation’ which proposes that researchers might have to fill in the gaps of archives by imagining what might have happened when there is no way to know otherwise. The goal is to map new ways of diversity in critical thinking, rupturing methodological and theoretical boundaries to locate and analyze findings.

---