The talk will aim to provide a holistic view of the fundamental advancements required to make artificial intelligence both accessible and impactful in various domains. It will highlight the significance of robust AI systems that prioritise augmentation over automation, particularly in emerging economies. Emphasis will be placed on designing AI with "explainability by design," a framework that ensures interpretability and transparency from inception, which not only builds trust but also enhances the robustness of AI models against adversarial attacks. Additionally, the talk will explore the role of AI in augmenting human capabilities, bridging skill gaps, and sustaining employment in evolving economic landscapes.
Adil Khan is a Professor and a Researcher in machine learning. With a robust background in machine learning, deep learning, and representation learning, he is passionately dedicated to both pedagogy and innovative research in the realm of artificial intelligence. His research journey started in South Korea, in 2006, where he concentrated on human activity recognition through wearable sensors. His groundbreaking discoveries were published in reputable journals and employed by leading technology firms for their healthcare applications. Over his career, he has undertaken more than ten research projects and has published in excess of 90 research articles, making significant contributions to the field of artificial Intelligence. His expertise and experience are not limited to a single geographic location. His academic career has spanned various prestigious universities in South Korea, Denmark, Russia, the United Arab Emirates, Switzerland, and the U.K.