Empowering Human Decision-Making in AI Models: The Path to Trust and Transparency

Empowering Human Decision-Making in AI Models: The Path to Trust and Transparency

—The Science and Human Development Lecture Series Organized by TSP was Successfully Held

This lecture is co-hosted by TSP and the School of Software, Nanjing University of Information Science and Technology on 16 ,February 2023 online. Ramprasaath R.Selvarju, a senior researcher from Salesforce, and Dr. Yudong Zhang, Professor of the School of Computing and Mathematical Sciences, University of Leicester, were invited by the host to share cutting-edge knowledge of computer science.

Welcome to the full video: https://www.youtube.com/watch?v=FeBPaoqFZaM

Ramprasaath R. Selvaraju is a senior machine learning scientist at Artera AI working on multiple intersecting areas including machine learning, computer vision and language, interpretable AI, and medical AI. It focuses on building algorithms, providing explanations for decisions made by the deep Web, building user trust, integrating domain knowledge into AI, and correcting unnecessary biases learned from deep AI models.

Dr. Yudong Zhang is Chair Professor, the School of Computing and Mathematical Sciences, University of Leicester, UK. Research interests include deep learning and medical image analysis. 2014-2018 Elsevier China Highly Cited Scientist (Computer Science). 2019, 2021 and 2022 Clarivate Avicorp Cited Scientist. He was selected as one of the World's Top 2% scientists by Stanford University from 2020 to 2022. Received Emerald Citation of Excellence 2017, Information Fusion 2022 Best Paper Award and other awards.

The lecture ranged from explaining decisions from deep networks through Grad-CAM, Leveraging explanations to Unbias models, and Enabling human beings knowledge transfer through explanations and What's ahead for explainable-AI,and in the following interactive session, participants had a positive interaction and exchange with Ramprasaath.All participants expressed that they had a more comprehensive understanding of the field of AI and benefited a lot. They will take this lecture as an opportunity to further study relevant knowledge, to learn deeply and thoroughly.