Leveraging the Jetson Nano AI Kit for Machine Learning in Quantifying Gender Bias in Image Captioning

Abstract

In an era where artificial intelligence intertwines with ethical concerns, this paper delves into the practical deployment of the Jetson Nano AI kit to assess gender bias in image captioning. As the AI landscape evolves, the Jetson Nano stands out as an effective tool for environments with limited resources, leveraging its edge computing capabilities to reshape AI research. The paper examines the foundational concepts of gender bias quantification and its real-world application using the Jetson Nano, highlighting its versatility in constrained environments. Throughout the exploration, the seamless integration of the Jetson Nano into machine learning processes is detailed, shedding light on crucial optimizations and adjustments. Challenges encountered are also analyzed, offering insights for researchers undertaking similar projects. Ultimately, the research underscores not just Jetson Nano's role in edge computing but also the imperative of confronting gender bias in AI-generated image descriptions. By melding ethical considerations with edge computing, this paper paves the way for a more balanced and effective AI future.

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