The development of Connected Autonomous Vehicles (CAVs) has been very active across the automotive industry. This is due to the significant improvement of the performance of perception and decision-making systems in recent years thanks to a new wave of Artificial Intelligence (AI). Yet, a new set of risks is emerging with the advent of CAVs that are safety-critical systems.
In this talk, a brief history of AI will be presented with a focus on heyday and nadir. Then, a new AI technology, Deep Learning (DL) will be discussed to introduce recent AI challenges. AI systems can be compromised by simple tricks so that their decisions must be validated and explainable. The eXplainable AI (XAI) will be presented and its necessity will be discussed thereafter. Finally, machine decisionality will be discussed in the area of CAVs and embedded AI. AI will make complex risk mitigation decisions that are ultimately life and death consequences. This talk will conclude with a discussion about the challenges of AI decisions. Dr. Jaerock Kwon is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn. Dr. Kwon has three major research interests: (1) Artificial Intelligence and Machine Learning, (2) Autonomous Vehicles, Self-Driving Cars, Intelligent Robotics, and (3) Computational Neuroscience and Neuroanatomy. His development plan for a 3D tissue scanner with Internet-connected 3D virtual microscope has been supported by NSF in 2013 ~ 2017. This instrument will be an essential tool for large-scale automated histology. He received his Ph.D. in Computer Engineering in 2009 from Texas A&M University, College Station, Texas, USA. His M.S. and B.S in Electronic Communication Engineering from Hanyang University, Seoul, Korea. His research lab at the University of Michigan-Dearborn is the Bio-Inspired Machine Intelligence (BIMI) Laboratory. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx