Ethical Language: Analyzing Reactions to Biopolitical Scenarios in Terms of Unfairness

Abstract

Biopolitics, a concept popularized by 20th-century French philosopher Michel Foucault, refers to the control and regulation of human bodies by political entities. This study contrasts responses to four biopolitical scenarios—including health, citizenship rights, military supplies allocation, and targeted advertising—with four non-biopolitical counterparts. The research involves participant-based studies on twenty male high-school students from St. Mark’s School of Texas, twenty Gen X female Caucasians in Texas, and three generative artificial intelligence models: ChatGPT, Gemini, and Llama. The findings show that both human participants and AI models perceive biopolitical scenarios as more unjust than non-biopolitical scenarios. However, targeted advertising is viewed similarly to its non-biopolitical counterpart, likely due to its institutionalization in consumer culture. These results suggest that modern AI models respond to biopolitical control in ways comparable to two unique human populations. More studies may be needed for further generalizability, however, due to the relatively small sample sizes and consolidation of poll respondents in Texas. This research overall offers valuable insights into AI decision-making processes and provides a linguistic framework for policy planners seeking public support.