Exploring the ethical considerations of using Chat GPT in university education

This study investigates the moral dilemmas that arise with incorporating Chat GPT into higher education, with a focus on the situation in Latinoamerican institutions of higher learning. The study surveyed 220 people via online questionnaire to learn more about their experiences with and motivations for using AI-powered conversational agents. An overview of the demographics of the participants was provided through descriptive statistics. This investigation of the subject at hand lays the groundwork for further research. It also reveals the hidden meanings of the observed phenomena, and it suggests possible solutions to the problems that have been uncovered. This research looks at how AI systems and chatbots can supplement human knowledge and judgment, as well as their potential drawbacks. The results showed that participants thought Chat GPT integration was moderately accessible and had moderately positive social attitudes. They understood the value and responsibility of Chat GPT in creating individualized educational opportunities. Participants stressed the necessity for explicit institutional standards regarding privacy and data security. Gender, age, sense of accessibility, social attitude, opinions, and personal experience, privacy and data security, institutional guidelines, and individualized learning were also found to affect participants' reliance on AI through regression analysis. The findings shed light on how the integration of Chat GPT into Latinoamerican higher education is complicated by factors such as individual beliefs, cultural norms, and ethical problems. The busy schedules of students may be accommodated and the resources they need to succeed can be made available thanks to this adaptability. In addition, natural language processing models can offer students instantaneous help via text chat, voice, or video. To fully grasp the ethical consequences and lead the creation of responsible implementation techniques, the research proposes that additional qualitative investigations, longitudinal studies, and comparative research across diverse contexts is required. Closing these knowledge gaps will help move the conversational AI field forward in ways that are ethical and beneficial to the classroom.