WHEN STIGMATIZATION AND SOCIODEMOGRAPHICS CHALLENGE ARTIFICIAL INTELLIGENCE IMPLEMENTATION

The undeniable enticement of Artificial Intelligence (AI) goes across every aspect of daily basis, and education is no exception. The obstacles remain present due to the sociodemographic factors, and eventually, they touch the preconceived judgments teachers have. This research is aimed at investigating how stigmatization and sociodemographics of students in choosing the best AI for students. This research was conducted using qualitative research, i.e., interviews of twelve teachers who were selected based on the curated criteria and thematic analysis. The findings suggest that teachers stigmatize students according to the sociodemographic factors, consisting of gender, age, ethnicity, proficiency, economic level, previous education, and financial aid. Teachers take their consideration of choosing AI based on the sociodemographic. As a result, it greatly helps students in achieving learning outcomes. The findings agree with the notion that AI implementation should be adjusted to the students’ needs, though in this case, it involves stigmatization as an initial step. Therefore, for future researchers, it will be necessary to understand the indication of stigmatization in the implementation of AI, especially in settings that encompass multiple backgrounds.