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Seminar on “Shedding Light on the Black Box: The Role of Explainability in Machine Learning”
Seminar on “Shedding Light on the Black Box: The Role of Explainability in Machine Learning”
On April 29th, 2024, the Department of Computer Science and Engineering of the Bangladesh Army University of Science and Technology (BAUST), Saidpur, hosted a seminar titled “Shedding Light on the Black Box: The Role of Explainability in Machine Learning” at Dr. Wazed Mia Seminar Hall.
The keynote speaker was Saumendu Roy (Saumo), who is a Ph.D. fellow from the SR and ISE Lab at the University of Saskatchewan, Canada. Saumendu Roy emphasised the challenges posed by opaque machine learning models and highlighted the importance of transparency in critical domains. Attendees engaged in discussions on methodologies to promote model interpretability, including interpretable model architectures and feature importance analysis. The seminar concluded with a call to prioritise explainability in AI research, emphasising its role in fostering trust, regulatory compliance, and ethical AI development. Through collaborative efforts, stakeholders aim to demystify the black box and cultivate transparent and interpretable AI systems aligned with societal values.
The event at BAUST served as a pivotal moment in advancing understanding and promoting accountability in machine learning research and practice.
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