הצטרפו גם בזום

Abstract: 

From the industrial revolution to the ongoing Fourth Industrial Revolution driven by AI, technological advancements have continually reshaped society and industry. These advancements are changing the ways we interact with each other (social), with our environment and with our resources (economy). The main driving forces of these revolutions are the technological breakthroughs (from machines, through electricity and Internet up to AI), which are followed by periods of human adaptation, as societies adjust to the transformative changes these innovations introduce. What if we could shape these human-AI interactions as seamless synergies that are  mutually enriching and naturally aligned for both sides (instead of, current unilateral interactions, where the human side adjusts to the technology)?
This topic is particularly important nowadays since we are already facing a shift from experts and well-trained professionals interacting with technology (i.e., AI tools and solutions) to a broad spectrum of human users (from experts, through decision makers, to laymen). On one hand, these AI solutions can improve humans’ lives (in domains such as medical, transportation, finance and education). On the other hand, humans need to effectively and critically use these digital technologies to gain those benefits.
In this talk,  I will present our research on explainable AI algorithms for AI agents making decisions under uncertainty while interacting with humans in a variety of domains (transportation, manufacturing and disaster management). 

Bio:

Claudia V. Goldman is an Associate Professor of Data Science at the Hebrew University Business School. She earned her B.Sc. in Computer Science (1991) and her M.Sc. and Ph.D. in Artificial Intelligence (1993, 1999; recipient of the Eshkol Scholarship) from the Hebrew University. During her postdoctoral fellowship at Bar Ilan University (1999-2001), she studied strategic agent behaviors in competitive environments. She, then, specialized in decentralized control of multiagent systems as a senior postdoctoral fellow at the University of Massachusetts Amherst (2002-2004, raising AFOSR funding). Prior to joining academia, Prof. Goldman spent 18 years in industrial AI research, serving as a member of the CTO staff and team leader in the Samsung Technical Center for Research (Israel) and as a staff researcher in General Motors Technical Center (Israel). She joined the Hebrew University faculty in 2024, where she established the Explainable AI for Good Lab. Her research focuses on trustworthy human-AI interactions and the development of effective and efficient AI systems, particularly through explainable AI algorithms for decision making under uncertainty in high stakes domains with significant societal and environmental implications.

Prof. Goldman has published extensively in the Artificial Intelligence literature (87 peer reviewed articles) covering her research on explainable AI, adaptive systems, multi-agent systems, coordination and decentralized control. She holds 67 patents (21 granted and 46 filed). Prof. Goldman serves on program committees and as a referee for the main Artificial Intelligence conferences (AAAI, IJCAI, AAMAS, ECAI) and relevant journals (Artificial Intelligence, JAIR, and JAAMAS). Prof. Goldman is a member of the Association for the Advancement of Artificial Intelligence and the Israeli Association for Artificial Intelligence.