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High School Student Researcher Tarun’s Paper on Analyzing the Racial Bias of ChatGPT-4 Accepted at the FLLM 2024

High School Student Researcher Tarun's Paper On Analyzing The Racial Bias Of Chatgpt 4 Accepted At The Fllm 2024

Tarun Mahesh is a student at Hillsborough High School in the United States. He has already achieved notable success in academics and research. In particular, he has demonstrated a strong interest in science, technology, engineering, and mathematics (STEM).

Science Olympiad Success

Tarun has earned impressive results in Science Olympiad competitions. At the MIT Invitational, he placed 28th out of 76 participants in the Bridge event. Earlier, during eighth grade, he secured second place in the Machines event at the state competition. These achievements reflect his dedication to scientific problem-solving.

Research Experience in Science and Technology

Beyond competitions, Tarun has gained practical research experience. At the Brain Imaging and Computation Lab, he explored machine learning techniques for disease prediction. His work focused on heart disease and Alzheimer’s disease, with the aim of supporting research into early detection and patient outcomes.

Tarun also works as a web developer for the Ramamurthi Lab at Lehigh University. There, he uses HTML, CSS, and JavaScript to build a user-friendly website. The platform helps showcase the lab’s members and their research achievements.

Research on Racial Bias in ChatGPT-4

Tarun reached another milestone when his paper, “Analyzing the Racial Bias of ChatGPT-4,” was accepted for presentation at the 2nd International Conference on Foundation and Large Language Models (FLLM 2024), sponsored by IEEE.

The conference took place in Dubai from November 26–29, 2024. It explored developments in foundation models and large language models, including ChatGPT. Topics included prompt engineering, AI sustainability, model architectures, and the social impact of AI.

At CCIR Academy, Tarun examined how racial and gender biases appear in ChatGPT-4’s responses. His research uses a method to quantify these biases and visualise patterns of disparity. Furthermore, the study investigates possible causes of these patterns and explores ways to reduce bias. This work contributes to ongoing discussions about fairness and responsible AI development.

Congratulations to Tarun on this outstanding achievement!

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