Unveiling Prejudices in Educational Milieus: Exploring the Impact of Minimalist Synthetic ChatGPT

Potential Abstract:
This research article investigates the impact of minimalist synthetic ChatGPT on uncovering prejudices in educational milieus. As artificial intelligence (AI) technologies continue to play an increasingly influential role in education, it becomes crucial to understand their potential to reveal and address biases. Through a mixed-methods approach, this study examines how the use of a minimalist synthetic ChatGPT, a language model developed by OpenAI, can shed light on hidden prejudices within educational contexts.

The research design consists of two phases. In the first phase, a large corpus of educational texts and online discussions is collected and preprocessed to train the ChatGPT model. The model is then fine-tuned using a set of carefully constructed scenarios to simulate various educational interactions. The second phase involves deploying the trained ChatGPT model in real-world educational settings, where it interacts with teachers, students, and other stakeholders. The interactions are analyzed to identify instances of potential prejudices and biases, both explicit and implicit, in the responses generated by the ChatGPT.

The results of this study contribute to our understanding of how AI technologies can serve as tools for uncovering prejudices in educational contexts. By utilizing a minimalist synthetic ChatGPT, we are able to explore biases that may be overlooked in traditional approaches. Furthermore, we offer insights into the potential benefits and limitations of deploying AI systems in educational settings, particularly in terms of promoting equity, inclusivity, and addressing biases.

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