{"id":1096245,"date":"2024-10-23T03:21:19","date_gmt":"2024-10-23T10:21:19","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&#038;p=1096245"},"modified":"2024-11-13T01:25:24","modified_gmt":"2024-11-13T09:25:24","slug":"societal-ai-tab-workshop","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/societal-ai-tab-workshop\/","title":{"rendered":"2024 MSR Asia TAB Workshop: Shaping the Future with Societal AI"},"content":{"rendered":"\n\n\n\n\n<p>As AI continues to advance and its societal impact deepens, it presents both unprecedented opportunities for progress and significant challenges that require careful navigation. No longer merely a tool, AI is evolving into a companion to humans, reshaping the way we live and work, and calling for new frameworks to understand and govern its role. This workshop at MSR Asia TAB 2024 will bring together internal and external researchers to explore critical themes such as AI evaluation, value alignment, and its far-reaching influence on productivity, education, research, and employment. By fostering interdisciplinary collaboration, we aim to harness AI\u2019s potential while ensuring it serves the long-term interests of humanity.<\/p>\n\n\n\n<p>The goals of the workshop include, but are not limited to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Exchange Visions and Research updates of Societal AI: Bringing together Microsoft and academic partners to share and discuss the latest advancements in Societal AI.<\/li>\n\n\n\n<li>Engage in Strategic Discussions on Societal AI Insights: Delve into the core questions and concepts outlined in Societal AI, gathering critical feedback from thought leaders and partners to refine and enhance collective understanding and approach.<\/li>\n\n\n\n<li>Strengthen Collaboration and Partnerships: Deepen the engagement between MSR Asia team and both internal and external researchers through open dialogue, promoting collaboration to drive the innovation and application of Societal AI.<\/li>\n<\/ul>\n\n\n\n<p><strong>Organizing Committee<\/strong><\/p>\n\n\n\n<p>Xing Xie (Chair), Beibei Shi (Chair), Xiaoyuan Yi (Co-Chair), Fangzhao Wu (Co-Chair), Jianxun Lian (Co-Chair), Miran Lee, Binghao Huan<\/p>\n\n\n\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n\n\n<p><strong>Venue: Meeting Room San Li Tun, 4th Floor, Microsoft Building 2, No. 5 Danling Street, Haidian District, Beijing, China.<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-table\" style=\"margin-bottom:50px;\">\n\t<table class=\"has-fixed-layout\">\n\t\t<tbody>\n\t\t\t<tr>\n\t\t\t\t<th style=\"width:10%;\">Session<\/th>\n\t\t\t\t<th style=\"width:15%;\" colspan=\"2\">Time<\/th>\n\t\t\t\t<th style=\"width:45%;\">Title and Abstract<\/th>\n\t\t\t\t<th style=\"width:30%;\">Speakers<\/th>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Opening<\/td>\n\t\t\t\t<td>9:30-9:40<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td><\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Xing Xie (Host)<\/li>\n\t\t\t\t\t\t<li>Doug Burger, TF & CVP, MSR CORE<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Keynote Speech<\/td>\n\t\t\t\t<td>9:40-10:10<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Societal AI: Tackling AI Challenges with Social Science Insights<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Beibei Shi (Host)<\/li>\n\t\t\t\t\t\t<li>Xing Xie, Partner Research Manager, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Break and Group Photo<\/td>\n\t\t\t\t<td>10:10-10:30<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>All participants<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td rowspan=\"5\">Research Talks and Panel Discussion1<\/td>\n\t\t\t\t<td rowspan=\"5\">10:30-11:40<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>LLM-driven social science and generative agents<\/strong>\n\t\t\t\t\t<br>This session aims to discuss the synergy between cutting-edge AI technologies and the ever-evolving field of (computational) social science. As large language models (LLMs) continue to revolutionize data analysis, predictive models, and content generation, their potential to transform (computational) social science research and practice becomes increasingly promising. In particular, we will delve into the current status and challenges of LLM-based social simulation. Participants will gain insights into how LLMs can be used to model complex social phenomena, simulate human behavior, and generate realistic social interactions.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jianxun Lian (Chair)<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>10:30-10:40<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>AI to transform social science and vice versa: studies on economics and cultural understanding<\/strong>\n\t\t\t\t\t<br>Generative AI has been transforming different research disciplinaries ranging from computer science, natural science, to social science. How to leverage the advanced GenAI technology to assist the research on social science, particularly on factors that deeply influence everyone? In this talk, I will share our latest efforts in two areas: economics and cultural understanding. Specifically, the first efforts aims to adopt GenAI to simulate the competition dynamics in society, which tries to achieve accurate and profound simulations. In the second work, we study how to leverage the social theories to help GenAI models better adapt to different cultures, given that current models are predominantly trained on Western cultures. I hope that these works can shed light on better co-adaptation of social science and GenAI research in the future.\n\t\t\t\t\t\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jindong Wang, Senior Researcher, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>10:40-10:50<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>LLMob: An LLM Agent Framework for Personal Mobility Generation<\/strong>\n\t\t\t\t\t<br>This study introduces a novel approach using Large Language Models (LLMs) integrated into an agent framework for flexible and effective personal mobility generation. LLMs overcome the limitations of previous models by effectively processing semantic data and offering versatility in modeling various tasks. Our approach addresses three research questions: aligning LLMs with real-world urban mobility data, developing reliable activity generation strategies, and exploring LLM applications in urban mobility. The key technical contribution is a novel LLM agent framework that accounts for individual activity patterns and motivations, including a self-consistency approach to align LLMs with real-world activity data and a retrieval-augmented strategy for interpretable activity generation. We evaluate our LLM agent framework and compare it with state-of-the-art personal mobility generation approaches, demonstrating the effectiveness of our approach and its potential applications in urban mobility. Overall, this study marks the pioneering work of designing an LLM agent framework for activity generation based on real-world human activity data, offering a promising tool for urban mobility analysis.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Renhe Jiang, Lecturer, Center for Spatial Information Science, The University of Tokyo<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>10:50-11:00<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Designing Cognitive Theory-inspired LLM Agents for Efficient Human Behavior Simulation<\/strong>\n\t\t\t\t\t<br>The rapid advancement of Large Language Models (LLMs) has led to the emergence of human-like commonsense reasoning, sparking the development of numerous LLM agents. However, current LLM agents are often constrained by high computational costs. In this talk, I will introduce a cognitive theory-inspired framework that elicits the efficient reasoning in LLM agents. This framework harnesses the synergy between larger, cloud-based models and smaller, local models to improve reasoning efficiency and accuracy. By optimally assigning simpler tasks to smaller models and more complex tasks to larger models, we reduce computational overhead while maintaining high performance. Furthermore, I will present a human behavior simulation framework that can fully unleash the reasoning power of LLMs to mimic human cognitive process and generate realistic human behaviors. These works open up new possibilities to power social science research with low cost, reproducible experiments with Homo Silicus, i.e., computational human models driven by LLM agents.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Fengli Xu, Assistant Professor, Department of Electronic Engineering, Tsinghua University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t\t\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>11:00-11:40<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Group Discussion 1<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jianxun Lian (Chair)<\/li>\n\t\t\t\t\t\t<li>Fengli Xu, Assistant Professor, Department of Electronic Engineering, Tsinghua University<\/li>\n\t\t\t\t\t\t<li>Renhe Jiang, Lecturer, Center for Spatial Information Science, The University of Tokyo<\/li>\n\t\t\t\t\t\t<li>Jindong Wang, Senior Researcher, Microsoft Research Asia<\/li>\n\t\t\t\t\t\t<li>Muhua Huang, Master student, Computational Social Science, University of Chicago<\/li>\n\t\t\t\t\t\t<li>Linyi Yang, Assistant Professor, Westlake University<\/li>\n\t\t\t\t\t\t<li>Lichao Sun, Assistant Professor, Department of Computer Science and Engineering, Lehigh University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Lunch<\/td>\n\t\t\t\t<td>11:40-13:00<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td><\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>All participants\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td rowspan=\"7\">Research Talks and Panel Discussion 2<\/td>\n\t\t\t\t<td rowspan=\"7\">13:00-14:30<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Aligning AI towards Human Values and Social Equity<\/strong>\n\t\t\t\t\t<br>This session will explore the capabilities AI must develop, beyond task performance, to function as a companion to humans \u2014 focusing on its alignment align with human values\/ethics, cultural preferences, and achieving social equity. Drawing perspectives from computer science, social science, and philosophy, we will investigate how to assess AI\u2019s value orientations, implement effective alignment methods, and eliminate social biases to foster fairness. Participants will gain insights into the technical and philosophical foundations of AI alignment and fairness, learning how AI can be designed to promote equitable outcomes and be benevolent toward the society as a whole.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Xiaoyuan Yi (Chair)<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:00-13:10<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Building globally equitable generative AI<\/strong>\n\t\t\t\t\t<br>Whilst generative AI\u2019s ability to process and generate human-like content has opened up new possibilities, it is not equally useful for everyone; because of this its impact is unlikely to be evenly distributed globally. In this talk I will discuss recent research which has shown that, when it comes to Africa, not only does generative AI have a language problem, equally, if not more importantly, it has a knowledge problem. I will describe how we have designed a program of human-centred AI research to address these challenges and build globally equitable AI.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jacki O&#8217;Neill, Director of Microsoft Research Africa, Nairobi<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:10-13:20<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>When Alignment meets o1<\/strong>\n\t\t\t\t\t<br>This talk presents initial discussions on alignment research following the release of OpenAI\u2019s o1 model. (1) Challenge: Superalignment, where the unlocked potential of model capabilities reinforces the necessity of aligning superintelligence. (2) Opportunity: System2 Alignment, which suggests aligning the process rather than just the outcome, much like educating children by guiding the decision-making process, not just giving right-or-wrong answers.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jitao Sang, Professor, Beijing Jiaotong University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:20-13:30<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Dynamic Value Alignment: Enhancing User Autonomy Through Multi-agent, Moral Foundations Theoretical Framework<\/strong>\n\t\t\t\t\t<br>This talk presents an interdisciplinary project on value alignment in AI. First, I address key challenges such as context-sensitivity, moral complexity, equitable personalization, and user autonomy. Then, I draw on Moral Foundations Theory, Multi-Agent Design, and Evaluative AI frameworks to tackle these issues. By integrating Moral Foundations Theory, we capture the diversity of normative behaviors across cultures, while Multi-Agent Design enables flexible alignment with diverse value systems without extensive retraining. The Evaluative AI framework, unlike traditional recommendation models, provides balanced evidence for decision-making, ensuring interpretability and accountability. Throughout the presentation, I emphasize the importance of understanding human cognitive architecture, emotional influences, and human moral reasoning. The proposed solution highlights the crucial role of combining insights from philosophy, cognitive science, and computer science to create ethically aligned AI systems that are adaptable across diverse cultural and professional settings.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Linus Huang, Research Assistant Professor, Division of Humanities, HKUST\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:30-13:40<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Mapping out a human rights-based approach to AI: Contexutalizing principles through processes<\/strong><br>\nAt times it seems there are more frameworks describing ethical AI than grains of sand on the beach.  What distinguishes ours from the rest?  We will present our model, which we have been refining for the past three years in active dialogue with a number of generous contributors from various industries, disciplines, and backgrounds.  But we are even more keen to hear the feedback and reactions from this distinguished audience, so will list our contact information in advance.  Please generously share with us your insights and wisdom: ssonnenberg@snu.ac.kr \/ yonglim@snu.ac.kr. Since 2022, Seoul National University&#8217;s Artificial Intelligence Policy Initiative (SAPI) has been working with a prominent policy think tank in Geneva and a variety of diplomats, corporate executives, venture capitalists, technologists, ESG experts, scholars, and activists to develop what we are calling a &#8220;Human Rights Based Approach to New and Emerging Technologies&#8221;, or HRBA@Tech &#8211; 2022 framework (https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=4587332) \/ 2023 application to AI startups (https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=4880112).  Our model was conceived from the ground-up: learning from the experience of those who have been working to build trustworthy AI (and other emerging technologies).  We highlight 5 ways in which our model is different from the vast majority of existing frameworks, and speculate that this model can be useful for corporations seeking to develop AI that is not only safe, but also contributes to making our world a better place to live.  \n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Stephan Sonnenberg, Associate Professor, School of Law, Seoul National University<\/li>\n\t\t\t\t\t\t<li>Yong Lim, Associate Professor, School of Law, Seoul National University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:40-13:50<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>An Adaptive and Robust Evaluation Framework of LLM Values<\/strong>\n\t\t\t\t\t<br>Aligning LLMs with human values is essential for ethical AI deployment, yet it requires a comprehensive understanding of the value orientations embedded in these models. We focus on the generative evaluation paradigm to directly deciphers LLMs&#8217; values from their generated responses. This paradigm relies on reference-free value evaluators, however, two key challenges emerge: the evaluator should adapt to changing human value definitions, against their own bias (adaptability); and remain robust across varying value expressions and scenarios (generalizability). To handle these challenges, we introduce CLAVE, a novel framework that integrates two complementary LLMs: a large model to extract high-level value concepts from diverse responses, leveraging its extensive knowledge, and a small model fine-tuned on these concepts to adapt to human value annotations. This dual-model framework serve as an optimal balance of the two challenges. Based on the generative evaluation paradigm, we create a comprehensive value leaderboard that tests a diverse array of value systems across various LLMs, which also enables us to compare the alignment between the values of different countries and those of LLMs, thereby identifying the models that most closely align with specific cultural or even personalized values.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jing Yao, Researcher, Microsoft Research Asia\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:50-14:30<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Group Discussion 2<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Xiaoyuan Yi (Chair)\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Jacki O\u2019Neill, Director of Microsoft Research Africa, Nairobi\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Jitao Sang, Professor, Beijing Jiaotong University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Linus Huang, Research Assistant Professor, Division of Humanities, HKUST\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Stephan Sonnenberg, Associate Professor, School of Law, Seoul National University and Yong Lim, Associate Professor, School of Law, Seoul National University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Jing Yao, Researcher, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Break<\/td>\n\t\t\t\t<td>14:30-14:45<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td><\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>All participants\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td rowspan=\"6\">Research Talks and Panel Discussion 3<\/td>\n\t\t\t\t<td rowspan=\"6\">14:45-16:15<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>New Opportunities and Challenges from Generative AI for Society<\/strong>\n\t\t\t\t\t<br>Generative AI like ChatGPT has gained wide popularity and adoption. Like other historical disruptive technologies, its impact on society will be deep and complex. In this session, we discuss the opportunities and challenges brought by Generative AI to society, and how will human and society be reshaped by Generative AI.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Fangzhao Wu (Chair)<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>14:45-14:55<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>The social roots of AI assisted policymaking: evidence from survey experiment<\/strong>\n\t\t\t\t\t<br>Artificial intelligence (AI) is increasingly influential in public policy areas, including election forecasting and targeted service delivery. Previous studies have recognized AI algorithms as tools for policy-makers, examining their effects on government performance. However, the political implications of AI on public perception, particularly regarding AI-driven public services and government agency views, remain underexplored. This study uses a randomized experiment with a vignette design to investigate AI&#8217;s impact on political preferences through automated decision-making (ADM). Our findings reveal that ADM notably enhances public trust in policymaking, although this trust varies among individuals. Additionally, ADM significantly boosts people&#8217;s sense of internal political efficacy and their preference for scientifically informed policymaking.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Tianguang Meng, Professor, Department of Political Science, Tsinghua University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>14:55-15:05<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Disclosing use of AI in the generation of synthetic content: a regulatory perspective<\/strong>\n\t\t\t\t\t<br>Lawmakers around the world are introducing regulations requiring transparency in the use of AI across various contexts. The proposed Australian Guardrails for High-Risk AI framework also recommends that the use of AI in generating synthetic content should be disclosed. This presentation explores the challenges of establishing rules for when and how the use of generative AI should be disclosed in relation to synthetic content. It draws on a public survey we conducted to examine public opinions on when the use of generative AI should be disclosed, depending on the extent of its involvement in creating a particular piece of content.&nbsp;\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Rita Matulionyte, Associate Professor, Law School, Macquarie University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>15:05-15:15<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Regulatory Frameworks for Generative AI: Jurisdictional Perspectives<\/strong>\n\t\t\t\t\t<br>My talk will examine various jurisdictional approaches to addressing potential societal harms associated with generative AI, focusing on: (i) the U.S.\u2019s federal implementation of Executive Order 14110 and California SB-1047 (vetoed), (ii) China\u2019s Generative AI Interim Measures, AI Safety Governance Framework, and Scholar Draft of the AI Act, (iii) the EU\u2019s AI Act, and (iv) Korea\u2019s AI Bill and draft AI privacy frameworks. Key topics will include each jurisdiction\u2019s approach to issues such as (i) public safety and security, (ii) infringement harms (copyright and privacy), (iii) challenges associated with deepfake and other synthetic media, and (iv) other emerging concerns.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Sangchul Park, Associate Professor, School of Law, Seoul National University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>15:15-15:25<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Japan&#8217;s Approach to AI Governance &#8212; How to build an interoperable regulatory framework?<\/strong>\n\t\t\t\t\t<br>This presentation will provide an overview of Japan&#8217;s social and cultural landscape for promoting AI and the current regulatory frameworks supporting AI development. It will then examine global legal approaches to AI and the progress of international collaboration through the G7 Hiroshima AI Process, emphasizing key differences among G7 member states. This analysis aims to guide the audience in reconsidering the scope and feasibility of achieving an internationally interoperable regulatory framework for AI.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Hiroki Habuka (Online), Research Professor, Graduate School of Law, Kyoto University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>15:25-16:15<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Group Discussion 3<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Fangzhao Wu (Chair), Principle Researcher, Microsoft Research Asia\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Tianguang Meng, Professor, Department of Political Science, Tsinghua University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Rita Matulionyte, Associate Professor, Law School, Macquarie University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Sangchul Park, Associate Professor, School of Law, Seoul National University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>HirokiHabuka (Online), Research Professor, Graduate School of Law, Kyoto University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Closing<\/td>\n\t\t\t\t<td>16:15-16:20<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Beibei Shi, Senior Research PM, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t<\/tbody>\n\t<\/table>\n<\/figure>\n\n\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"346\" height=\"346\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/06\/Beibei-Shi.jpg\" alt=\"Beibei Shi\" class=\"wp-image-1046838 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/06\/Beibei-Shi.jpg 346w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/06\/Beibei-Shi-300x300.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/06\/Beibei-Shi-150x150.jpg 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/06\/Beibei-Shi-180x180.jpg 180w\" sizes=\"(max-width: 346px) 100vw, 346px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/besh\/\">Beibei Shi<\/a>, Senior Research PM, Microsoft Research Asia<\/strong><\/p>\n\n\n\n<p>Beibei Shi is senior research program manager at Microsoft Research Asia, taking the responsibility of MSR Asia Open Collaborative Research Program and StarTrack Program, as well as university relations between MSR Asia and universities in Central China, South China, China Hongkong and Taiwan. Besides, she takes the responsibility of the strategic cooperation between Microsoft Research Asia and the Ministry of Education of the People\u2019s Republic of China. She focuses on the research theme of Resilience and Trust, has successfully led several open collaborative research sub-themes establishment with related MSR Asia research team, such as AIER Platform, OpenNetLab, Computing for Carbon Negative and Responsible AI.<\/p>\n\n\n\n<p>Before joined MSR Asia, she joined IBM Research China Institute as a researcher in the cross field of environment and computer, after earned master\u2019s degree in environmental science school of China Agricultural University in 2019. Then, she joined the University Partnership Department of IBM China as a program manager. During that period, she participated to design and led to execute industry-academic cooperative research program \u201cgreen horizon plan\u201d, making very solid contribution to technology innovation of air pollution control.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"701\" height=\"701\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/02\/dburger-portrait2_web.jpg\" alt=\"Doug Burger wearing a suit and tie smiling at the camera\" class=\"wp-image-172238 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/dburger-portrait2_web.jpg 701w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/dburger-portrait2_web-150x150.jpg 150w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/dburger-portrait2_web-300x300.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/dburger-portrait2_web-180x180.jpg 180w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/dburger-portrait2_web-360x360.jpg 360w\" sizes=\"(max-width: 701px) 100vw, 701px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/dburger\/\">Doug Burger<\/a>, TF & CVP, MSR CORE<\/strong><\/p>\n\n\n\n<p>Doug Burger is one of the world\u2019s leading active researchers in computer architecture, with a broad set of important contributions to his credit. After receiving his PhD from University of Wisconsin in 1998, he joined UT Austin as a professor, receiving tenure in 2004 and becoming a full professor in 2008. His work on Explicit Data Graph Computing (EDGE) represents the fourth major class of instruction-set architectures (after CISC, RISC, and VLIW). At U. Texas, he co-led the project that conceived and built the TRIPS processor, an ambitious multicore ASIC and working EDGE system, which remains one of the most complex microprocessor prototypes ever built in academia. A number of Doug\u2019s research contributions, such as non-uniform cache architectures (NUCA caches), are now shipping in Intel, ARM, and IBM microprocessors. He has been recognized as an IEEE Fellow and ACM Fellow, and in 2006 received the ACM Maurice Wilkes Award for his early contributions to the field. He is the co-inventor of more than fifty U.S. patents, including six with Bill Gates.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"273\" height=\"273\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image018.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1096323 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image018.jpg 273w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image018-150x150.jpg 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image018-180x180.jpg 180w\" sizes=\"(max-width: 273px) 100vw, 273px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/fangzwu\/\">Fangzhao Wu<\/a>, Principle Researcher, Microsoft Research Asia<\/strong><\/p>\n\n\n\n<p>Fangzhao Wu is now a researcher at Social Computing group, Microsoft Research Asia. His research mainly focuses on responsible AI, especially LLM safety, privacy, copyright, and social impact.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"248\" height=\"248\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image005-6718919fb2718.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096293 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image005-6718919fb2718.png 248w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image005-6718919fb2718-150x150.png 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image005-6718919fb2718-180x180.png 180w\" sizes=\"(max-width: 248px) 100vw, 248px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=http%3A%2F%2Fweb.ee.tsinghua.edu.cn%2Fxufengli%2Fen%2Findex.htm&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281235119%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=pVdYlw7pMDFh5%2BMM45c4J2QAfNVy2SiYgtleCAXE0gc%3D&reserved=0\">Fengli Xu<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Assistant Professor, Department of Electronic Engineering, Tsinghua University<\/strong><\/p>\n\n\n\n<p>Dr. Fengli Xu is a tenure-track Assistant Professor at the Department of Electronic Engineering in Tsinghua University. Prior to current position, he was a postdoc researcher at the University of Chicago and Hong Kong University of Science and Technology. His research interests lie in the interdisciplinary area of Artificial Intelligence, LLM Agents, Social Computing and Network Science. His recent research focuses on designing novel agentic workflows to fully exploit the opportunities offered by the advent of behavioral big data and Large Language Models, pushing forward the boundary of agentic AI and computational social science. Dr. Xu\u2019s works have been published in several high-profile interdisciplinary journals&#8212;PNAS, Nature Human Behaviour, Nature Communications, and Nature Computational Science, and 40+ top data science conferences and journals, e.g., NeurIPS, WWW, KDD, etc. His research was recognized by selective academic awards, including CAAI AI Excellent Young Scientist Award, CAAI rising star in social computing, MSRA Fellowship, ACM Sigspatial China Doctoral Dissertation Award, etc. Dr. Xu has served as the (senior) PC Member of WWW, AAAI, WSDM and IJCAI and co-organize IC2S2 2022 as Datathon director.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"819\" height=\"1024\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-819x1024.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1103253 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-819x1024.jpg 819w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-240x300.jpg 240w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-768x960.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-1228x1536.jpg 1228w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-1638x2048.jpg 1638w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-144x180.jpg 144w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo.jpg 1833w\" sizes=\"(max-width: 819px) 100vw, 819px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.csis.org%2Fpeople%2Fhiroki-habuka&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281527994%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=tc9WVKB2xEU%2BBf5F9im9D3ON5gX9ZjAQtbCgzJLc7SU%3D&reserved=0\">Hiroki Habuka<span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (Online), Research Professor, Graduate School of Law, Kyoto University<\/strong><\/p>\n\n\n\n<p>Hiroki Habuka is a Research Professor at the Graduate School of Law, Kyoto University, and the CEO of Smart Governance. He specializes in agile governance, a multi-stakeholder and distributed governance model that integrates regulation, corporate governance, and system risk management, particularly in the field of AI and data. He also serves as the representative director of the AI Governance Association, which is the largest non-profit organization in Japan focused on the responsible development and implementation of AI. He also consults for leading companies, guiding the implementation of effective digital governance practices. In 2020, the World Economic Forum&#8217;s Global Future Councils on Agile Governance and Apolitical named him one of the World\u2019s 50 Most Influential People Revolutionising Government (Agile 50). Hiroki holds a Master\u2019s degree in Law (LL.M., Fulbright Fellow) from Stanford Law School, a Juris Doctor from the University of Tokyo Law School, and is qualified to practice law in Japan and New York State. He is the author of a book &#8220;Introduction to AI Governance: From Risk Management to Social Design.&#8221; (2023)<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"360\" height=\"360\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image011.png\" alt=\"a woman smiling for the camera\" class=\"wp-image-1096308 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image011.png 360w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image011-300x300.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image011-150x150.png 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image011-180x180.png 180w\" sizes=\"(max-width: 360px) 100vw, 360px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jaoneil\/\">Jacki O&#8217;Neill<\/a>, Director of Microsoft Research Africa, Nairobi<\/strong><\/p>\n\n\n\n<p>Dr Jacki O\u2019Neill is the founding Director of Microsoft Research Africa (formerly MARI). She is passionate about designing technologies which enhance, rather than remove, agency and create sustainable futures. She brings this passion to Microsoft Research Africa where she is building a multi-disciplinary team, combining research, engineering and design to solve local problems globally. An ethnographer by trade, in her research career so far she has focused on technologies for work \u2013 with the aim of making work better; and technologies for societal impact, with the aim of supporting underserved communities. The inspiration for MARI came out of this desire to create technologies to enhance work and society globally. Before leading the MARI, she was a Principal Researcher in the Technology for Emerging Markets (TEM) area at Microsoft Research India. She has led major research projects in the future of work from new labour platforms to workplace AI and chat; digital currencies and financial inclusion; and Global Healthcare. She has ~50 peer-reviewed articles, two innovation awards and 16 patents (from new interaction mechanisms to crowd-sourcing). . She has served on the program and organising committees of major conferences such as CHI, CSCW, ICTD and ECSCW for many years.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"745\" height=\"745\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image003-671891a4538c6.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096296 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image003-671891a4538c6.png 745w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image003-671891a4538c6-300x300.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image003-671891a4538c6-150x150.png 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image003-671891a4538c6-180x180.png 180w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image003-671891a4538c6-360x360.png 360w\" sizes=\"(max-width: 745px) 100vw, 745px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jialia\/\">Jianxun Lian<\/a>, Senior Researcher, Microsoft Research Asia<\/strong><\/p>\n\n\n\n<p>Jianxun Lian is now a senior researcher at Microsoft Research Asia. His research interests include Humanoid AI, LLM-based Agent, and Recommendation Systems. He has published some academic papers on top international conferences such as KDD, IJCAI, and WWW. He serves as a program committee member for several conferences such as KDD, SIGIR, WWW, AAAI, and IJCAI.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"358\" height=\"358\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image012.png\" alt=\"a person posing for the camera\" class=\"wp-image-1096311 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image012.png 358w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image012-300x300.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image012-150x150.png 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image012-180x180.png 180w\" sizes=\"(max-width: 358px) 100vw, 358px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jingyao\/\">Jing Yao<\/a>, Researcher, Microsoft Research Asia<\/strong><\/p>\n\n\n\n<p>Jing Yao is now a researcher at Social Computing Group in Microsoft Research Asia. She received her M.S. degree in Computer Science from Renmin University of China in 2022, and a B.S. degree in Computer Science from Renmin University of China in 2019. She joined MSRA in July 2022. Her research interests include responsible AI, large language model alignment, trustworthy recommendation and information retrieval. She has published some academic papers on top-tier international conferences such as Neurips, SIGIR, WWW, NAACL, CIKM. She serves as a program committee member for several conferences such as ACL, ICLR and SIGIR.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"226\" height=\"226\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/startrack-jindong-wang.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1096299 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/startrack-jindong-wang.jpg 226w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/startrack-jindong-wang-150x150.jpg 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/startrack-jindong-wang-180x180.jpg 180w\" sizes=\"(max-width: 226px) 100vw, 226px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jindwang\/\">Jindong Wang<\/a>, Senior Researcher, Microsoft Research Asia<\/strong><\/p>\n\n\n\n<p>Dr. Jindong Wang currently works at Microsoft Research Asia as a Senior Researcher. He obtained his Ph.D from University of Chinese Academy of Sciences in 2019 with the excellent PhD thesis award. His research interest includes machine learning, large language models, and AI for social science. He has published over 50 papers with 14000+ citations at leading conferences and journals such as ICML, ICLR, NeurIPS, TPAMI, IJCV etc. His research is reported by Forbes, MIT Technology Review, and other international media. He was selected by Stanford University as one of the World\u2019s Top 2% Scientists and one of the AI Most Influential Scholars by AMiner. He has several Google scholar highly cited papers, Huggingface featured papers, and paperdigest most influential papers. He serves as the associate editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), guest editor for ACM Transactions on Intelligent Systems and Technology (TIST), area chair for NeurIPS, ICLR, KDD, ACMMM, and ACML, senior program committee member of IJCAI and AAAI. He leads several impactful open-source projects, including transferlearning, PromptBench, torchSSL, USB, personalizedFL, and robustlearn, which received over 16K stars on Github. He published a book Introduction to Transfer Learning. He gave tutorials at IJCAI\u201922, WSDM\u201923, KDD\u201923, and AAAI\u201924.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"126\" height=\"166\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image014.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096314 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/faculty.bjtu.edu.cn\/9129\/\">Jitao Sang<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Professor, Beijing Jiaotong University<\/strong><\/p>\n\n\n\n<p>Jitao Sang, professor at Beijing Jiaotong University. His research interests include multimodal analysis, trustworthy AI and alignment, AI Agent.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"145\" height=\"144\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Lichao-Sun.png\" alt=\"a person posing for a camera\" class=\"wp-image-1103208 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong>Lichao Sun, Assistant Professor, Department of Computer Science and Engineering, Lehigh University<\/strong><\/p>\n\n\n\n<p>Dr. Lichao Sun is an Assistant Professor in the Department of Computer Science and Engineering at Lehigh University and an Adjunct Professor at the Mayo Clinic. He earned his Ph.D. in Computer Science from the University of Illinois, Chicago, in 2020, under the supervision of Prof. Philip S. Yu, following his M.S. and B.S. degrees from the University of Nebraska-Lincoln. Dr. Sun has authored over 100 publications in top-tier venues such as Nature Medicine, NeurIPS, ICML, ICLR, S&P, and KDD. He is the recipient of several prestigious awards, including 2024 Microsoft Accelerate Foundation Models Research Award, 2024 OpenAI Researcher Award, and NSF CRII Award.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"508\" height=\"508\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image015.png\" alt=\"a person wearing a suit and tie smiling at the camera\" class=\"wp-image-1096317 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image015.png 508w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image015-300x300.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image015-150x150.png 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image015-180x180.png 180w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image015-360x360.png 360w\" sizes=\"(max-width: 508px) 100vw, 508px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.sof.arts.hku.hk%2Flinushuang&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281385477%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=X2uoEEyptv38oonQxLc4Sc%2BkIXVGU8GCHsr0RUB4EFQ%3D&reserved=0\">Linus Huang<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Research Assistant Professor, Division of Humanities, HKUST<\/strong><\/p>\n\n\n\n<p>Linus Huang is a Research Assistant Professor at the Division of Humanities and Centre for AI Research, Hong Kong University of Science and Technology, and a StarTrack Scholar at Microsoft Research Asia. His interdisciplinary research focuses on AI ethics, philosophy of cognitive science, and embodied cognition. His work tackles issues of reducing algorithmic bias, aligning AI with human values, and understanding human intelligence. Currently, he leads the funded project Engineering Equity, which explores AI&#8217;s potential to mitigate implicit bias in HKUST.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"145\" height=\"148\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/\u56fe\u50cf.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1103235 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong>Linyi Yang, Assistant Professor, Westlake University<\/strong><\/p>\n\n\n\n<p>Linyi Yang is currently working at Westlake University as a Research Assistant Professor. He graduated with a Ph.D. from University College Dublin in 2021, under the supervision of Professor Barry Smyth (the Member of the Royal Irish Academy and the fellow of European Coordinating Committee on AI). His research interests lie in LLMs, causal inference, and explainable artificial intelligence. He has been the only recipient of the Postdoc Representative at Westlake University in 2023, the only recipient of Outstanding Self-financed Chinese Students Abroad Scholarship (Category B) in Ireland awarded by the NSFC in 2022, and was a nominee for the Best Paper at CCIS in 2018. He has published over 40 articles in prestigious international conferences and journals, including 13 co-leading publications, with 9 in CCF-A and 4 in CCF-B venues, and received more than 3,000 citations.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"96\" height=\"96\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/\u56fe\u72471.png\" alt=\"Miran\" class=\"wp-image-1097394 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong>Miran Lee, Outreach Director, MSR Accelerator Korea<\/strong><\/p>\n\n\n\n<p>Miran Lee is a Director of Microsoft Research Outreach Group at Microsoft Research responsible for academic collaboration in Korea and the Asia-Pacific region.<\/p>\n\n\n\n<p>Lee joined Microsoft Research Asia in 2005 as a university relations manager to build long-term and mutually beneficial relations with academia. She is based in Korea, where she engages with leading research universities, research institutes, and relevant government agencies. She establishes strategies and directions, identifies business opportunities, designs various programs and projects, and manages the budget. She works with students, researchers, faculty members, and university administrators to build strong partnerships, and works closely with the research groups at Microsoft Research, focusing on research collaboration, curriculum development, talent fostering, and academic exchanges. She has successfully run many global and regional programs such as Gaming & Graphics, Web-Scale NLP, Machine Translation, eHealth, SORA (Software Radio), Kinect, and Microsoft Azure for Research. She\u2019s currently leading 2 themes, \u2018Discovery\u2019 and \u2019 Health and Life Science\u2019 as a member of global v-team.<\/p>\n\n\n\n<p>Before her current role, Miran Lee co-founded Smart Systems, which specializes in IT outsourcing services in Illinois, United States. As CEO of Smart Systems, she successfully led the business with more than 100 percent annual growth. From 1993 to 2002, she worked at British Telecom Korea in various positions ranging from systems engineer to account director to vice president. Lee also worked at Samsung SDS, where she was responsible for International VAN (Value Added Network) businesses and led the International VAN business team. She started her business career as a system developer at General Electric Information Services, where she developed email, EDI, and in-house applications.<\/p>\n\n\n\n<p>Miran Lee was an adjunct professor in the Telecommunication Department at Anyang University for two years (2001\u20132002).<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"133\" height=\"133\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Muhua-Huang.png\" alt=\"a person posing for a camera\" class=\"wp-image-1103214 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong>Muhua Huang, Master student, Computational Social Science, University of Chicago<\/strong><\/p>\n\n\n\n<p>Muhua Huang is a master\u2019s student in Computational Social Science at the University of Chicago, with a BA in Computer Science and Psychology from the University of British Columbia. She previously interned at MSRA Social Computing group. Her research spans human-centered AI, computational social science, and psychometrics. Currently, her work focuses on using LLM agents to simulate human personality, cognition, behavior, and social interactions.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image008-6718922431819.png\" alt=\"a man wearing a suit and tie\" class=\"wp-image-1096305 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.renhejiang.com%2F&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281285080%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=%2BvUBQefI%2BdEo2%2FpLp5KNcXYC%2Bz%2Fu7MQQpU64pE7dQqw%3D&reserved=0\">Renhe Jiang<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Lecturer, Center for Spatial Information Science, The University of Tokyo<\/strong><\/p>\n\n\n\n<p>Renhe Jiang is a lecturer at Center for Spatial Information Science, The University of Tokyo. He received his B.E. degree in Software Engineering from Dalian University of Technology in 2012, M.S. degree in Information Science from Nagoya University in 2015, and Ph.D. degree in Civil Engineering from The University of Tokyo in 2019. From 2019 to 2022, he was an assistant professor at Information Technology Center, The University of Tokyo. His research interests include AI, spatiotemporal data mining, time series forecasting, human mobility modeling, and graph learning.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"213\" height=\"213\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image021.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096329 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image021.png 213w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image021-150x150.png 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image021-180x180.png 180w\" sizes=\"(max-width: 213px) 100vw, 213px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fresearchers.mq.edu.au%2Fen%2Fpersons%2Frita-matulionyte&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281478440%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=0xcx5V0DDwgEz4HFQVSUS0WNQ912E%2F9ASK4sVabeZeU%3D&reserved=0\">Rita Matulionyte<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Associate Professor, Law School, Macquarie University<\/strong><\/p>\n\n\n\n<p>Rita is an international expert in technology and intellectual property law, with a recent focus on legal regulation and governance of Artificial Intelligence technologies. She acquired her PhD degree from Albert Ludwig University of Freiburg\/Max Planck Institute for Intellectual Property and Competition Law (Germany, suma cum lauda) in 2010. Since then she researched and lectured in universities in Japan, Germany, Lithuania, and Australia. To date, she published over 60 peer-reviewed articles and book chapters, as well as a monograph on Applicable Law to Copyright Infringement: A Comparison of ALI and CLIP Principles. Rita is regularly invited to present in conferences in Europe, South and North America, and Asia, and has prepared reports for the European Commission, European Patent Office, and the governments of Australia, South Korea and Lithuania.<\/p>\n\n\n\n<p>Rita has led projects on &#8216;Government Use of Face Recognition Technologies: Legal Challenges and Solutions&#8217; (Lithuanian Research Council grant) and &#8216;Towards Explainable AI in Healthare&#8217; (Macquarie University Research Acceleration Scheme), and was an investigator at the NSW Ombudsman project &#8216;Mapping Automated Decision Making Tools in Administrative Decision Making in NSW&#8217; (led by Prof Kimberlee Weatherall). Previously she was a recipient of a research grant by the Japanese Society for the Promotion of Science for her project on &#8216;The Law Applicable to Copyright&#8217;.<\/p>\n\n\n\n<p>She is a Lead of the Emerging Technologies Workstream at the Australian Society for Computers and Law (AUSCL), a member of Australia Standards, Committee IT-043, a Lead of the Explainable AI research stream at the Centre for Applied Artificial Intelligence at Macquarie University, an affiliate of ARC Centre of Excellence for Automated Decision Making, a member of Macquarie University Agency and Ethics Research Centre and the Intellectual Property Association of Australia and New Zealand (IPSANZ).<\/p>\n\n\n\n<p>Rita is willing to supervise student projects in the areas of technology and intellectual property law, especially in the area of AI and law.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"120\" height=\"153\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image022.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096332 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Flaw.snu.ac.kr%2Fpage_en%2Fprofessor.php%3Fwr_id%3D199&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281503645%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=x8nZI%2FNnE3wWQpGGYtSzPkdrqFRtZHG%2Ff5FDpw9b1oQ%3D&reserved=0\">Sangchul Park<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Associate Professor, School of Law, Seoul National University<\/strong><\/p>\n\n\n\n<p>Sangchul Park is an associate professor at Seoul National University School of Law. He completed his doctoral degree (JSD) at the University of Chicago and his undergraduate studies at Seoul National University. His main research area is the legal oversight of AI applications and the application of ML and NLP to legal studies. At the law school, he is teaching AI & law and information & telecommunications law. Prior to beginning his academic career, he spent more than 13 years in private practice specializing in technology, media, and telecommunications.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"120\" height=\"148\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/thumb-2469288056_sTi5yAgr_ss_120x.jpg\" alt=\"a man smiling for the camera\" class=\"wp-image-1096410 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/law.snu.ac.kr\/page_en\/professor.php?wr_id=185\">Stephan Sonnenberg<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Associate Professor, School of Law, Seoul National University<\/strong><\/p>\n\n\n\n<p>Stephan SONNENBERG is an Associate Professor at Seoul National University&#8217;s School of Law. Prior to teaching in Korea, Stephan has taught in Bhutan and at Stanford and Harvard Law Schools in the United States. His academic focus is on social entrepreneurship, human rights, conflict management, and international development studies. He studied Law at Harvard Law School and earned a degree in international affairs at the Fletcher School at Tufts University.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"146\" height=\"146\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image020.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096326 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.dps.tsinghua.edu.cn%2Fpsen%2Finfo%2F1014%2F1051.htm&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281455046%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=D9yO6ITaGIkqgCFXr%2FhrX9T0Q%2FGFN6y8%2BJ%2FDdioIMD4%3D&reserved=0\">Tianguang Meng<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Professor, Department of Political Science, Tsinghua University<\/strong><\/p>\n\n\n\n<p>Tianguang Meng is a full professor in the Department of Political Science at the School of Social Sciences in Tsinghua University, the director of The Research Center on Data and Governance, and the executive director of Tsinghua Computational Social Science Institute. His research interest includes government responsiveness, politics of information and politics of Digital Governance in China. His articles have been published in Comparative Political Studies, Governance, World development, and Comparative Politics. He earned the B.A. and Ph.D. degrees in political science from Peking University. Previously, He was a visiting scholar in Harvard University and University of California, San Diego.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"300\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/xiaoyuan-yi-1.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1096302 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/xiaoyuan-yi-1.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/xiaoyuan-yi-1-150x150.jpg 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/xiaoyuan-yi-1-180x180.jpg 180w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/xiaoyuanyi\/\">Xiaoyuan Yi<\/a>, Senior Researcher, Microsoft Research Asia<\/strong><\/p>\n\n\n\n<p>Xiaoyuan Yi, Senior Researcher at Microsoft Research Asia. He obtained his bachelor\u2019s and doctorate degrees in computer science from Tsinghua University. He mainly engages in natural language generation (NLG) and Societal AI research, and published 30+ papers in top-tier AI conference such as ICLR, NeurIPS, ACL, EMNLP and AAAI. He has won honors such as the Tsinghua University Supreme Scholarship, the Xinhua Net The 10 Most Influential People on the Internet, the Best Paper Award and the Best System Demonstration Award of the Chinese Conference on Computational Linguistics, Rising Star Award of IJCAI Young Elite Symposium, Outstanding Doctoral Dissertation Award by China Computer Federation (CCF), Rising Stars in Social Computing by The Chinese Association for Artificial Intelligence (CAAI) and so on.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"360\" height=\"360\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image001.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096257 size-full\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image001.png 360w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image001-300x300.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image001-150x150.png 150w, https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image001-180x180.png 180w\" sizes=\"(max-width: 360px) 100vw, 360px\" \/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/xingx\/\">Xing Xie<\/a>, Partner Research Manager, Microsoft Research Asia<\/strong><\/p>\n\n\n\n<p>Dr. Xing Xie is a partner research manager at Microsoft Research Asia. He received his B.S. and Ph.D. in Computer Science from the University of Science and Technology of China in 1996 and 2001, respectively. Since joining Microsoft Research Asia in July 2001, Dr. Xie has focused on data mining, social computing, and responsible AI. His work has been recognized with several prestigious awards, including the IEEE MDM 2023 Test-of-Time Award, ACM SIGKDD 2022 Test-of-Time Award, ACM SIGKDD China 2021 Test-of-Time Award, ACM SIGSPATIAL 2020 10-Year Impact Award Honorable Mention, and ACM SIGSPATIAL 2019 10-Year Impact Award. He has delivered keynote speeches at notable conferences such as MDM 2019, ASONAM 2017, and W2GIS 2011. Dr. Xie serves on the editorial boards of ACM Transactions on Recommender Systems, ACM Transactions on Social Computing, ACM Transactions on Intelligent Systems and Technology, and CCF Transactions on Pervasive Computing and Interaction. He served as program co-chair of ACM Ubicomp 2011, PCC 2012, UIC 2015, SMP 2017, ACM SIGSPATIAL 2021, ACM SIGSPATIAL 2022, IEEE MDM 2022, PAKDD 2024, and IEEE BigData 2025. Dr. Xie is a Fellow of the ACM, IEEE, and China Computer Federation.<\/p>\n<\/div><\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-media-text has-vertical-margin-small  has-vertical-padding-none  is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\" data-bi-an=\"media-text\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"120\" height=\"120\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image017.png\" alt=\"a person posing for the camera\" class=\"wp-image-1096320 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\" data-bi-an=\"media-text\">\n<p><strong><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Flaw.snu.ac.kr%2Fpage_en%2Fprofessor.php%3Fwr_id%3D110&data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281408670%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=I%2B9vqwc%2Bhmo2N0Q6%2FND7roojDPmpEqEUwhpOf9A3DoU%3D&reserved=0\">Yong Lim<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Associate Professor, School of Law, Seoul National University<\/strong><\/p>\n\n\n\n<p>Yong Lim is an Associate Professor at Seoul National University (\u201cSNU\u201d), School of Law, where he also served as Associate Dean of Student Affairs until 2020. He is the co-founder and director of SNU AI Policy Initiative (\u201cSAPI\u201d). SAPI is one of the labs currently spearheading a project at SNU\u2019s Center for Trustworthy AI to establish normative and technical standards for AI. His areas of specialty include competition law, consumer protection, privacy and data governance. Yong graduated from Seoul National University, College of Law, and obtained his S.J.D. at Harvard Law School. Prior to joining academia, Yong practiced law at Kim & Chang in Seoul, Korea. Yong was a Bok International Professor at Penn Carey Law in 2023.<\/p>\n<\/div><\/div>\n\n\n","protected":false},"excerpt":{"rendered":"<p>As AI continues to advance and its societal impact deepens, it presents both unprecedented opportunities for progress and significant challenges that require careful navigation. No longer merely a tool, AI is evolving into a companion to humans, reshaping the way we live and work, and calling for new frameworks to understand and govern its role. [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":true,"_classifai_error":"","msr_startdate":"2024-11-14","msr_enddate":"2024-11-14","msr_location":"Beijing, China","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"","msr_event_link_redirect":false,"msr_event_time":"","msr_hide_region":false,"msr_private_event":false,"footnotes":""},"research-area":[13559],"msr-region":[197903],"msr-event-type":[197944],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-1096245","msr-event","type-msr-event","status-publish","hentry","msr-research-area-social-sciences","msr-region-asia-pacific","msr-event-type-hosted-by-microsoft","msr-locale-en_us"],"msr_about":"<!-- wp:msr\/event-details {\"title\":\"2024 MSR Asia TAB Workshop: Shaping the Future with Societal AI\"} \/-->\n\n<!-- wp:msr\/content-tabs -->\n<!-- wp:msr\/content-tab -->\n<!-- wp:paragraph {\"placeholder\":\"Add Event Overview content\u2026\"} -->\n<p>As AI continues to advance and its societal impact deepens, it presents both unprecedented opportunities for progress and significant challenges that require careful navigation. No longer merely a tool, AI is evolving into a companion to humans, reshaping the way we live and work, and calling for new frameworks to understand and govern its role. This workshop at MSR Asia TAB 2024 will bring together internal and external researchers to explore critical themes such as AI evaluation, value alignment, and its far-reaching influence on productivity, education, research, and employment. By fostering interdisciplinary collaboration, we aim to harness AI\u2019s potential while ensuring it serves the long-term interests of humanity.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>The goals of the workshop include, but are not limited to:<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:list -->\n<ul class=\"wp-block-list\"><!-- wp:list-item -->\n<li>Exchange Visions and Research updates of Societal AI: Bringing together Microsoft and academic partners to share and discuss the latest advancements in Societal AI.<\/li>\n<!-- \/wp:list-item -->\n\n<!-- wp:list-item -->\n<li>Engage in Strategic Discussions on Societal AI Insights: Delve into the core questions and concepts outlined in Societal AI, gathering critical feedback from thought leaders and partners to refine and enhance collective understanding and approach.<\/li>\n<!-- \/wp:list-item -->\n\n<!-- wp:list-item -->\n<li>Strengthen Collaboration and Partnerships: Deepen the engagement between MSR Asia team and both internal and external researchers through open dialogue, promoting collaboration to drive the innovation and application of Societal AI.<\/li>\n<!-- \/wp:list-item --><\/ul>\n<!-- \/wp:list -->\n\n<!-- wp:paragraph -->\n<p><strong>Organizing Committee<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Xing Xie (Chair), Beibei Shi (Chair), Xiaoyuan Yi (Co-Chair), Fangzhao Wu (Co-Chair), Jianxun Lian (Co-Chair), Miran Lee, Binghao Huan<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:spacer {\"height\":\"50px\"} -->\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<!-- \/wp:spacer -->\n<!-- \/wp:msr\/content-tab -->\n\n<!-- wp:msr\/content-tab {\"title\":\"Agenda\"} -->\n<!-- wp:paragraph {\"placeholder\":\"Write content\u2026\"} -->\n<p><strong>Venue: Meeting Room San Li Tun, 4th Floor, Microsoft Building 2, No. 5 Danling Street, Haidian District, Beijing, China.<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:html -->\n<figure class=\"wp-block-table\" style=\"margin-bottom:50px;\">\n\t<table class=\"has-fixed-layout\">\n\t\t<tbody>\n\t\t\t<tr>\n\t\t\t\t<th style=\"width:10%;\">Session<\/th>\n\t\t\t\t<th style=\"width:15%;\" colspan=\"2\">Time<\/th>\n\t\t\t\t<th style=\"width:45%;\">Title and Abstract<\/th>\n\t\t\t\t<th style=\"width:30%;\">Speakers<\/th>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Opening<\/td>\n\t\t\t\t<td>9:30-9:40<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td><\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Xing Xie (Host)<\/li>\n\t\t\t\t\t\t<li>Doug Burger, TF &amp; CVP, MSR CORE<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Keynote Speech<\/td>\n\t\t\t\t<td>9:40-10:10<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Societal AI: Tackling AI Challenges with Social Science Insights<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Beibei Shi (Host)<\/li>\n\t\t\t\t\t\t<li>Xing Xie, Partner Research Manager, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Break and Group Photo<\/td>\n\t\t\t\t<td>10:10-10:30<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>All participants<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td rowspan=\"5\">Research Talks and Panel Discussion1<\/td>\n\t\t\t\t<td rowspan=\"5\">10:30-11:40<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>LLM-driven social science and generative agents<\/strong>\n\t\t\t\t\t<br>This session aims to discuss the synergy between cutting-edge AI technologies and the ever-evolving field of (computational) social science. As large language models (LLMs) continue to revolutionize data analysis, predictive models, and content generation, their potential to transform (computational) social science research and practice becomes increasingly promising. In particular, we will delve into the current status and challenges of LLM-based social simulation. Participants will gain insights into how LLMs can be used to model complex social phenomena, simulate human behavior, and generate realistic social interactions.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jianxun Lian (Chair)<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>10:30-10:40<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>AI to transform social science and vice versa: studies on economics and cultural understanding<\/strong>\n\t\t\t\t\t<br>Generative AI has been transforming different research disciplinaries ranging from computer science, natural science, to social science. How to leverage the advanced GenAI technology to assist the research on social science, particularly on factors that deeply influence everyone? In this talk, I will share our latest efforts in two areas: economics and cultural understanding. Specifically, the first efforts aims to adopt GenAI to simulate the competition dynamics in society, which tries to achieve accurate and profound simulations. In the second work, we study how to leverage the social theories to help GenAI models better adapt to different cultures, given that current models are predominantly trained on Western cultures. I hope that these works can shed light on better co-adaptation of social science and GenAI research in the future.\n\t\t\t\t\t\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jindong Wang, Senior Researcher, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>10:40-10:50<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>LLMob: An LLM Agent Framework for Personal Mobility Generation<\/strong>\n\t\t\t\t\t<br>This study introduces a novel approach using Large Language Models (LLMs) integrated into an agent framework for flexible and effective personal mobility generation. LLMs overcome the limitations of previous models by effectively processing semantic data and offering versatility in modeling various tasks. Our approach addresses three research questions: aligning LLMs with real-world urban mobility data, developing reliable activity generation strategies, and exploring LLM applications in urban mobility. The key technical contribution is a novel LLM agent framework that accounts for individual activity patterns and motivations, including a self-consistency approach to align LLMs with real-world activity data and a retrieval-augmented strategy for interpretable activity generation. We evaluate our LLM agent framework and compare it with state-of-the-art personal mobility generation approaches, demonstrating the effectiveness of our approach and its potential applications in urban mobility. Overall, this study marks the pioneering work of designing an LLM agent framework for activity generation based on real-world human activity data, offering a promising tool for urban mobility analysis.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Renhe Jiang, Lecturer, Center for Spatial Information Science, The University of Tokyo<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>10:50-11:00<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Designing Cognitive Theory-inspired LLM Agents for Efficient Human Behavior Simulation<\/strong>\n\t\t\t\t\t<br>The rapid advancement of Large Language Models (LLMs) has led to the emergence of human-like commonsense reasoning, sparking the development of numerous LLM agents. However, current LLM agents are often constrained by high computational costs. In this talk, I will introduce a cognitive theory-inspired framework that elicits the efficient reasoning in LLM agents. This framework harnesses the synergy between larger, cloud-based models and smaller, local models to improve reasoning efficiency and accuracy. By optimally assigning simpler tasks to smaller models and more complex tasks to larger models, we reduce computational overhead while maintaining high performance. Furthermore, I will present a human behavior simulation framework that can fully unleash the reasoning power of LLMs to mimic human cognitive process and generate realistic human behaviors. These works open up new possibilities to power social science research with low cost, reproducible experiments with Homo Silicus, i.e., computational human models driven by LLM agents.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Fengli Xu, Assistant Professor, Department of Electronic Engineering, Tsinghua University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t\t\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>11:00-11:40<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Group Discussion 1<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jianxun Lian (Chair)<\/li>\n\t\t\t\t\t\t<li>Fengli Xu, Assistant Professor, Department of Electronic Engineering, Tsinghua University<\/li>\n\t\t\t\t\t\t<li>Renhe Jiang, Lecturer, Center for Spatial Information Science, The University of Tokyo<\/li>\n\t\t\t\t\t\t<li>Jindong Wang, Senior Researcher, Microsoft Research Asia<\/li>\n\t\t\t\t\t\t<li>Muhua Huang, Master student, Computational Social Science, University of Chicago<\/li>\n\t\t\t\t\t\t<li>Linyi Yang, Assistant Professor, Westlake University<\/li>\n\t\t\t\t\t\t<li>Lichao Sun, Assistant Professor, Department of Computer Science and Engineering, Lehigh University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Lunch<\/td>\n\t\t\t\t<td>11:40-13:00<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td><\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>All participants\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td rowspan=\"7\">Research Talks and Panel Discussion 2<\/td>\n\t\t\t\t<td rowspan=\"7\">13:00-14:30<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Aligning AI towards Human Values and Social Equity<\/strong>\n\t\t\t\t\t<br>This session will explore the capabilities AI must develop, beyond task performance, to function as a companion to humans \u2014 focusing on its alignment align with human values\/ethics, cultural preferences, and achieving social equity. Drawing perspectives from computer science, social science, and philosophy, we will investigate how to assess AI\u2019s value orientations, implement effective alignment methods, and eliminate social biases to foster fairness. Participants will gain insights into the technical and philosophical foundations of AI alignment and fairness, learning how AI can be designed to promote equitable outcomes and be benevolent toward the society as a whole.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Xiaoyuan Yi (Chair)<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:00-13:10<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Building globally equitable generative AI<\/strong>\n\t\t\t\t\t<br>Whilst generative AI\u2019s ability to process and generate human-like content has opened up new possibilities, it is not equally useful for everyone; because of this its impact is unlikely to be evenly distributed globally. In this talk I will discuss recent research which has shown that, when it comes to Africa, not only does generative AI have a language problem, equally, if not more importantly, it has a knowledge problem. I will describe how we have designed a program of human-centred AI research to address these challenges and build globally equitable AI.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jacki O'Neill, Director of Microsoft Research Africa, Nairobi<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:10-13:20<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>When Alignment meets o1<\/strong>\n\t\t\t\t\t<br>This talk presents initial discussions on alignment research following the release of OpenAI\u2019s o1 model. (1) Challenge: Superalignment, where the unlocked potential of model capabilities reinforces the necessity of aligning superintelligence. (2) Opportunity: System2 Alignment, which suggests aligning the process rather than just the outcome, much like educating children by guiding the decision-making process, not just giving right-or-wrong answers.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jitao Sang, Professor, Beijing Jiaotong University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:20-13:30<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Dynamic Value Alignment: Enhancing User Autonomy Through Multi-agent, Moral Foundations Theoretical Framework<\/strong>\n\t\t\t\t\t<br>This talk presents an interdisciplinary project on value alignment in AI. First, I address key challenges such as context-sensitivity, moral complexity, equitable personalization, and user autonomy. Then, I draw on Moral Foundations Theory, Multi-Agent Design, and Evaluative AI frameworks to tackle these issues. By integrating Moral Foundations Theory, we capture the diversity of normative behaviors across cultures, while Multi-Agent Design enables flexible alignment with diverse value systems without extensive retraining. The Evaluative AI framework, unlike traditional recommendation models, provides balanced evidence for decision-making, ensuring interpretability and accountability. Throughout the presentation, I emphasize the importance of understanding human cognitive architecture, emotional influences, and human moral reasoning. The proposed solution highlights the crucial role of combining insights from philosophy, cognitive science, and computer science to create ethically aligned AI systems that are adaptable across diverse cultural and professional settings.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Linus Huang, Research Assistant Professor, Division of Humanities, HKUST\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:30-13:40<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Mapping out a human rights-based approach to AI: Contexutalizing principles through processes<\/strong><br>\nAt times it seems there are more frameworks describing ethical AI than grains of sand on the beach.  What distinguishes ours from the rest?  We will present our model, which we have been refining for the past three years in active dialogue with a number of generous contributors from various industries, disciplines, and backgrounds.  But we are even more keen to hear the feedback and reactions from this distinguished audience, so will list our contact information in advance.  Please generously share with us your insights and wisdom: ssonnenberg@snu.ac.kr \/ yonglim@snu.ac.kr. Since 2022, Seoul National University's Artificial Intelligence Policy Initiative (SAPI) has been working with a prominent policy think tank in Geneva and a variety of diplomats, corporate executives, venture capitalists, technologists, ESG experts, scholars, and activists to develop what we are calling a \"Human Rights Based Approach to New and Emerging Technologies\", or HRBA@Tech - 2022 framework (https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=4587332) \/ 2023 application to AI startups (https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=4880112).  Our model was conceived from the ground-up: learning from the experience of those who have been working to build trustworthy AI (and other emerging technologies).  We highlight 5 ways in which our model is different from the vast majority of existing frameworks, and speculate that this model can be useful for corporations seeking to develop AI that is not only safe, but also contributes to making our world a better place to live.  \n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Stephan Sonnenberg, Associate Professor, School of Law, Seoul National University<\/li>\n\t\t\t\t\t\t<li>Yong Lim, Associate Professor, School of Law, Seoul National University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:40-13:50<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>An Adaptive and Robust Evaluation Framework of LLM Values<\/strong>\n\t\t\t\t\t<br>Aligning LLMs with human values is essential for ethical AI deployment, yet it requires a comprehensive understanding of the value orientations embedded in these models. We focus on the generative evaluation paradigm to directly deciphers LLMs' values from their generated responses. This paradigm relies on reference-free value evaluators, however, two key challenges emerge: the evaluator should adapt to changing human value definitions, against their own bias (adaptability); and remain robust across varying value expressions and scenarios (generalizability). To handle these challenges, we introduce CLAVE, a novel framework that integrates two complementary LLMs: a large model to extract high-level value concepts from diverse responses, leveraging its extensive knowledge, and a small model fine-tuned on these concepts to adapt to human value annotations. This dual-model framework serve as an optimal balance of the two challenges. Based on the generative evaluation paradigm, we create a comprehensive value leaderboard that tests a diverse array of value systems across various LLMs, which also enables us to compare the alignment between the values of different countries and those of LLMs, thereby identifying the models that most closely align with specific cultural or even personalized values.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Jing Yao, Researcher, Microsoft Research Asia\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>13:50-14:30<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Group Discussion 2<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Xiaoyuan Yi (Chair)\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Jacki O\u2019Neill, Director of Microsoft Research Africa, Nairobi\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Jitao Sang, Professor, Beijing Jiaotong University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Linus Huang, Research Assistant Professor, Division of Humanities, HKUST\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Stephan Sonnenberg, Associate Professor, School of Law, Seoul National University and Yong Lim, Associate Professor, School of Law, Seoul National University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Jing Yao, Researcher, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Break<\/td>\n\t\t\t\t<td>14:30-14:45<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td><\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>All participants\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td rowspan=\"6\">Research Talks and Panel Discussion 3<\/td>\n\t\t\t\t<td rowspan=\"6\">14:45-16:15<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>New Opportunities and Challenges from Generative AI for Society<\/strong>\n\t\t\t\t\t<br>Generative AI like ChatGPT has gained wide popularity and adoption. Like other historical disruptive technologies, its impact on society will be deep and complex. In this session, we discuss the opportunities and challenges brought by Generative AI to society, and how will human and society be reshaped by Generative AI.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Fangzhao Wu (Chair)<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>14:45-14:55<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>The social roots of AI assisted policymaking: evidence from survey experiment<\/strong>\n\t\t\t\t\t<br>Artificial intelligence (AI) is increasingly influential in public policy areas, including election forecasting and targeted service delivery. Previous studies have recognized AI algorithms as tools for policy-makers, examining their effects on government performance. However, the political implications of AI on public perception, particularly regarding AI-driven public services and government agency views, remain underexplored. This study uses a randomized experiment with a vignette design to investigate AI's impact on political preferences through automated decision-making (ADM). Our findings reveal that ADM notably enhances public trust in policymaking, although this trust varies among individuals. Additionally, ADM significantly boosts people's sense of internal political efficacy and their preference for scientifically informed policymaking.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Tianguang Meng, Professor, Department of Political Science, Tsinghua University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>14:55-15:05<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Disclosing use of AI in the generation of synthetic content: a regulatory perspective<\/strong>\n\t\t\t\t\t<br>Lawmakers around the world are introducing regulations requiring transparency in the use of AI across various contexts. The proposed Australian Guardrails for High-Risk AI framework also recommends that the use of AI in generating synthetic content should be disclosed. This presentation explores the challenges of establishing rules for when and how the use of generative AI should be disclosed in relation to synthetic content. It draws on a public survey we conducted to examine public opinions on when the use of generative AI should be disclosed, depending on the extent of its involvement in creating a particular piece of content.&nbsp;\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Rita Matulionyte, Associate Professor, Law School, Macquarie University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>15:05-15:15<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Regulatory Frameworks for Generative AI: Jurisdictional Perspectives<\/strong>\n\t\t\t\t\t<br>My talk will examine various jurisdictional approaches to addressing potential societal harms associated with generative AI, focusing on: (i) the U.S.\u2019s federal implementation of Executive Order 14110 and California SB-1047 (vetoed), (ii) China\u2019s Generative AI Interim Measures, AI Safety Governance Framework, and Scholar Draft of the AI Act, (iii) the EU\u2019s AI Act, and (iv) Korea\u2019s AI Bill and draft AI privacy frameworks. Key topics will include each jurisdiction\u2019s approach to issues such as (i) public safety and security, (ii) infringement harms (copyright and privacy), (iii) challenges associated with deepfake and other synthetic media, and (iv) other emerging concerns.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Sangchul Park, Associate Professor, School of Law, Seoul National University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>15:15-15:25<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Japan's Approach to AI Governance -- How to build an interoperable regulatory framework?<\/strong>\n\t\t\t\t\t<br>This presentation will provide an overview of Japan's social and cultural landscape for promoting AI and the current regulatory frameworks supporting AI development. It will then examine global legal approaches to AI and the progress of international collaboration through the G7 Hiroshima AI Process, emphasizing key differences among G7 member states. This analysis aims to guide the audience in reconsidering the scope and feasibility of achieving an internationally interoperable regulatory framework for AI.\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Hiroki Habuka (Online), Research Professor, Graduate School of Law, Kyoto University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>15:25-16:15<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<strong>Group Discussion 3<\/strong>\n\t\t\t\t<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Fangzhao Wu (Chair), Principle Researcher, Microsoft Research Asia\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Tianguang Meng, Professor, Department of Political Science, Tsinghua University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Rita Matulionyte, Associate Professor, Law School, Macquarie University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>Sangchul Park, Associate Professor, School of Law, Seoul National University\n\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<li>HirokiHabuka (Online), Research Professor, Graduate School of Law, Kyoto University<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t\t<tr>\n\t\t\t\t<td>Closing<\/td>\n\t\t\t\t<td>16:15-16:20<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>&nbsp;<\/td>\n\t\t\t\t<td>\n\t\t\t\t\t<ul style=\"padding-left:16px;\">\n\t\t\t\t\t\t<li>Beibei Shi, Senior Research PM, Microsoft Research Asia<\/li>\n\t\t\t\t\t<\/ul>\n\t\t\t\t<\/td>\n\t\t\t<\/tr>\n\t\t<\/tbody>\n\t<\/table>\n<\/figure>\n<!-- \/wp:html -->\n<!-- \/wp:msr\/content-tab -->\n\n<!-- wp:msr\/content-tab {\"title\":\"Speakers\"} -->\n<!-- wp:media-text {\"mediaId\":1046838,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/event\/2024-msra-startrack-seminars-june-edition\/beibei-shi-2\/\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/06\/Beibei-Shi.jpg\" alt=\"Beibei Shi\" class=\"wp-image-1046838 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/besh\/\">Beibei Shi<\/a>, Senior Research PM, Microsoft Research Asia<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Beibei Shi is senior research program manager at Microsoft Research Asia, taking the responsibility of MSR Asia Open Collaborative Research Program and StarTrack Program, as well as university relations between MSR Asia and universities in Central China, South China, China Hongkong and Taiwan. Besides, she takes the responsibility of the strategic cooperation between Microsoft Research Asia and the Ministry of Education of the People\u2019s Republic of China. She focuses on the research theme of Resilience and Trust, has successfully led several open collaborative research sub-themes establishment with related MSR Asia research team, such as AIER Platform, OpenNetLab, Computing for Carbon Negative and Responsible AI.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Before joined MSR Asia, she joined IBM Research China Institute as a researcher in the cross field of environment and computer, after earned master\u2019s degree in environmental science school of China Agricultural University in 2019. Then, she joined the University Partnership Department of IBM China as a program manager. During that period, she participated to design and led to execute industry-academic cooperative research program \u201cgreen horizon plan\u201d, making very solid contribution to technology innovation of air pollution control.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":172238,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/portrait2_web-jpg\/\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/02\/dburger-portrait2_web.jpg\" alt=\"Doug Burger wearing a suit and tie smiling at the camera\" class=\"wp-image-172238 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/dburger\/\">Doug Burger<\/a>, TF &amp; CVP, MSR CORE<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Doug Burger is one of the world\u2019s leading active researchers in computer architecture, with a broad set of important contributions to his credit. After receiving his PhD from University of Wisconsin in 1998, he joined UT Austin as a professor, receiving tenure in 2004 and becoming a full professor in 2008. His work on Explicit Data Graph Computing (EDGE) represents the fourth major class of instruction-set architectures (after CISC, RISC, and VLIW). At U. Texas, he co-led the project that conceived and built the TRIPS processor, an ambitious multicore ASIC and working EDGE system, which remains one of the most complex microprocessor prototypes ever built in academia. A number of Doug\u2019s research contributions, such as non-uniform cache architectures (NUCA caches), are now shipping in Intel, ARM, and IBM microprocessors. He has been recognized as an IEEE Fellow and ACM Fellow, and in 2006 received the ACM Maurice Wilkes Award for his early contributions to the field. He is the co-inventor of more than fifty U.S. patents, including six with Bill Gates.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096323,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096323\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image018.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1096323 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/fangzwu\/\">Fangzhao Wu<\/a>, Principle Researcher, Microsoft Research Asia<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Fangzhao Wu is now a researcher at Social Computing group, Microsoft Research Asia. His research mainly focuses on responsible AI, especially LLM safety, privacy, copyright, and social impact.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096293,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096293\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image005-6718919fb2718.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096293 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=http%3A%2F%2Fweb.ee.tsinghua.edu.cn%2Fxufengli%2Fen%2Findex.htm&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281235119%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=pVdYlw7pMDFh5%2BMM45c4J2QAfNVy2SiYgtleCAXE0gc%3D&amp;reserved=0\">Fengli Xu<\/a>, Assistant Professor, Department of Electronic Engineering, Tsinghua University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Dr. Fengli Xu is a tenure-track Assistant Professor at the Department of Electronic Engineering in Tsinghua University. Prior to current position, he was a postdoc researcher at the University of Chicago and Hong Kong University of Science and Technology. His research interests lie in the interdisciplinary area of Artificial Intelligence, LLM Agents, Social Computing and Network Science. His recent research focuses on designing novel agentic workflows to fully exploit the opportunities offered by the advent of behavioral big data and Large Language Models, pushing forward the boundary of agentic AI and computational social science. Dr. Xu\u2019s works have been published in several high-profile interdisciplinary journals---PNAS, Nature Human Behaviour, Nature Communications, and Nature Computational Science, and 40+ top data science conferences and journals, e.g., NeurIPS, WWW, KDD, etc. His research was recognized by selective academic awards, including CAAI AI Excellent Young Scientist Award, CAAI rising star in social computing, MSRA Fellowship, ACM Sigspatial China Doctoral Dissertation Award, etc. Dr. Xu has served as the (senior) PC Member of WWW, AAAI, WSDM and IJCAI and co-organize IC2S2 2022 as Datathon director.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1103253,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/event\/societal-ai-tab-workshop\/hiroki-habuka_photo\/\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Hiroki-Habuka_photo-819x1024.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1103253 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.csis.org%2Fpeople%2Fhiroki-habuka&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281527994%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=tc9WVKB2xEU%2BBf5F9im9D3ON5gX9ZjAQtbCgzJLc7SU%3D&amp;reserved=0\">Hiroki Habuka<\/a> (Online), Research Professor, Graduate School of Law, Kyoto University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Hiroki Habuka is a Research Professor at the Graduate School of Law, Kyoto University, and the CEO of Smart Governance. He specializes in agile governance, a multi-stakeholder and distributed governance model that integrates regulation, corporate governance, and system risk management, particularly in the field of AI and data. He also serves as the representative director of the AI Governance Association, which is the largest non-profit organization in Japan focused on the responsible development and implementation of AI. He also consults for leading companies, guiding the implementation of effective digital governance practices. In 2020, the World Economic Forum's Global Future Councils on Agile Governance and Apolitical named him one of the World\u2019s 50 Most Influential People Revolutionising Government (Agile 50). Hiroki holds a Master\u2019s degree in Law (LL.M., Fulbright Fellow) from Stanford Law School, a Juris Doctor from the University of Tokyo Law School, and is qualified to practice law in Japan and New York State. He is the author of a book \"Introduction to AI Governance: From Risk Management to Social Design.\" (2023)<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096308,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096308\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image011.png\" alt=\"a woman smiling for the camera\" class=\"wp-image-1096308 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jaoneil\/\">Jacki O'Neill<\/a>, Director of Microsoft Research Africa, Nairobi<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Dr Jacki O\u2019Neill is the founding Director of Microsoft Research Africa (formerly MARI). She is passionate about designing technologies which enhance, rather than remove, agency and create sustainable futures. She brings this passion to Microsoft Research Africa where she is building a multi-disciplinary team, combining research, engineering and design to solve local problems globally. An ethnographer by trade, in her research career so far she has focused on technologies for work \u2013 with the aim of making work better; and technologies for societal impact, with the aim of supporting underserved communities. The inspiration for MARI came out of this desire to create technologies to enhance work and society globally. Before leading the MARI, she was a Principal Researcher in the Technology for Emerging Markets (TEM) area at Microsoft Research India. She has led major research projects in the future of work from new labour platforms to workplace AI and chat; digital currencies and financial inclusion; and Global Healthcare. She has ~50 peer-reviewed articles, two innovation awards and 16 patents (from new interaction mechanisms to crowd-sourcing). . She has served on the program and organising committees of major conferences such as CHI, CSCW, ICTD and ECSCW for many years.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096296,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096296\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image003-671891a4538c6.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096296 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jialia\/\">Jianxun Lian<\/a>, Senior Researcher, Microsoft Research Asia<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Jianxun Lian is now a senior researcher at Microsoft Research Asia. His research interests include Humanoid AI, LLM-based Agent, and Recommendation Systems. He has published some academic papers on top international conferences such as KDD, IJCAI, and WWW. He serves as a program committee member for several conferences such as KDD, SIGIR, WWW, AAAI, and IJCAI.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096311,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096311\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image012.png\" alt=\"a person posing for the camera\" class=\"wp-image-1096311 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jingyao\/\">Jing Yao<\/a>, Researcher, Microsoft Research Asia<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Jing Yao is now a researcher at Social Computing Group in Microsoft Research Asia. She received her M.S. degree in Computer Science from Renmin University of China in 2022, and a B.S. degree in Computer Science from Renmin University of China in 2019. She joined MSRA in July 2022. Her research interests include responsible AI, large language model alignment, trustworthy recommendation and information retrieval. She has published some academic papers on top-tier international conferences such as Neurips, SIGIR, WWW, NAACL, CIKM. She serves as a program committee member for several conferences such as ACL, ICLR and SIGIR.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096299,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096299\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/startrack-jindong-wang.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1096299 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/jindwang\/\">Jindong Wang<\/a>, Senior Researcher, Microsoft Research Asia<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Dr. Jindong Wang currently works at Microsoft Research Asia as a Senior Researcher. He obtained his Ph.D from University of Chinese Academy of Sciences in 2019 with the excellent PhD thesis award. His research interest includes machine learning, large language models, and AI for social science. He has published over 50 papers with 14000+ citations at leading conferences and journals such as ICML, ICLR, NeurIPS, TPAMI, IJCV etc. His research is reported by Forbes, MIT Technology Review, and other international media. He was selected by Stanford University as one of the World\u2019s Top 2% Scientists and one of the AI Most Influential Scholars by AMiner. He has several Google scholar highly cited papers, Huggingface featured papers, and paperdigest most influential papers. He serves as the associate editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), guest editor for ACM Transactions on Intelligent Systems and Technology (TIST), area chair for NeurIPS, ICLR, KDD, ACMMM, and ACML, senior program committee member of IJCAI and AAAI. He leads several impactful open-source projects, including transferlearning, PromptBench, torchSSL, USB, personalizedFL, and robustlearn, which received over 16K stars on Github. He published a book Introduction to Transfer Learning. He gave tutorials at IJCAI\u201922, WSDM\u201923, KDD\u201923, and AAAI\u201924.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096314,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096314\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image014.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096314 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/faculty.bjtu.edu.cn\/9129\/\">Jitao Sang<\/a>, Professor, Beijing Jiaotong University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Jitao Sang, professor at Beijing Jiaotong University. His research interests include multimodal analysis, trustworthy AI and alignment, AI Agent.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1103208,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/event\/societal-ai-tab-workshop\/lichao-sun\/\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Lichao-Sun.png\" alt=\"a person posing for a camera\" class=\"wp-image-1103208 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong>Lichao Sun, Assistant Professor, Department of Computer Science and Engineering, Lehigh University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Dr. Lichao Sun is an Assistant Professor in the Department of Computer Science and Engineering at Lehigh University and an Adjunct Professor at the Mayo Clinic. He earned his Ph.D. in Computer Science from the University of Illinois, Chicago, in 2020, under the supervision of Prof. Philip S. Yu, following his M.S. and B.S. degrees from the University of Nebraska-Lincoln. Dr. Sun has authored over 100 publications in top-tier venues such as Nature Medicine, NeurIPS, ICML, ICLR, S&amp;P, and KDD. He is the recipient of several prestigious awards, including 2024 Microsoft Accelerate Foundation Models Research Award, 2024 OpenAI Researcher Award, and NSF CRII Award.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096317,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096317\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image015.png\" alt=\"a person wearing a suit and tie smiling at the camera\" class=\"wp-image-1096317 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.sof.arts.hku.hk%2Flinushuang&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281385477%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=X2uoEEyptv38oonQxLc4Sc%2BkIXVGU8GCHsr0RUB4EFQ%3D&amp;reserved=0\">Linus Huang<\/a>, Research Assistant Professor, Division of Humanities, HKUST<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Linus Huang is a Research Assistant Professor at the Division of Humanities and Centre for AI Research, Hong Kong University of Science and Technology, and a StarTrack Scholar at Microsoft Research Asia. His interdisciplinary research focuses on AI ethics, philosophy of cognitive science, and embodied cognition. His work tackles issues of reducing algorithmic bias, aligning AI with human values, and understanding human intelligence. Currently, he leads the funded project Engineering Equity, which explores AI's potential to mitigate implicit bias in HKUST.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1103235,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/event\/societal-ai-tab-workshop\/%e5%9b%be%e5%83%8f\/\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/\u56fe\u50cf.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1103235 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong>Linyi Yang, Assistant Professor, Westlake University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Linyi Yang is currently working at Westlake University as a Research Assistant Professor. He graduated with a Ph.D. from University College Dublin in 2021, under the supervision of Professor Barry Smyth (the Member of the Royal Irish Academy and the fellow of European Coordinating Committee on AI). His research interests lie in LLMs, causal inference, and explainable artificial intelligence. He has been the only recipient of the Postdoc Representative at Westlake University in 2023, the only recipient of Outstanding Self-financed Chinese Students Abroad Scholarship (Category B) in Ireland awarded by the NSFC in 2022, and was a nominee for the Best Paper at CCIS in 2018. He has published over 40 articles in prestigious international conferences and journals, including 13 co-leading publications, with 9 in CCF-A and 4 in CCF-B venues, and received more than 3,000 citations.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1097394,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/event\/societal-ai-tab-workshop\/%e5%9b%be%e7%89%871-7\/\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/\u56fe\u72471.png\" alt=\"Miran\" class=\"wp-image-1097394 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong>Miran Lee, Outreach Director, MSR Accelerator Korea<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Miran Lee is a Director of Microsoft Research Outreach Group at Microsoft Research responsible for academic collaboration in Korea and the Asia-Pacific region.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Lee joined Microsoft Research Asia in 2005 as a university relations manager to build long-term and mutually beneficial relations with academia. She is based in Korea, where she engages with leading research universities, research institutes, and relevant government agencies. She establishes strategies and directions, identifies business opportunities, designs various programs and projects, and manages the budget. She works with students, researchers, faculty members, and university administrators to build strong partnerships, and works closely with the research groups at Microsoft Research, focusing on research collaboration, curriculum development, talent fostering, and academic exchanges. She has successfully run many global and regional programs such as Gaming &amp; Graphics, Web-Scale NLP, Machine Translation, eHealth, SORA (Software Radio), Kinect, and Microsoft Azure for Research. She\u2019s currently leading 2 themes, \u2018Discovery\u2019 and \u2019 Health and Life Science\u2019 as a member of global v-team.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Before her current role, Miran Lee co-founded Smart Systems, which specializes in IT outsourcing services in Illinois, United States. As CEO of Smart Systems, she successfully led the business with more than 100 percent annual growth. From 1993 to 2002, she worked at British Telecom Korea in various positions ranging from systems engineer to account director to vice president. Lee also worked at Samsung SDS, where she was responsible for International VAN (Value Added Network) businesses and led the International VAN business team. She started her business career as a system developer at General Electric Information Services, where she developed email, EDI, and in-house applications.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Miran Lee was an adjunct professor in the Telecommunication Department at Anyang University for two years (2001\u20132002).<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1103214,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/event\/societal-ai-tab-workshop\/muhua-huang\/\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/Muhua-Huang.png\" alt=\"a person posing for a camera\" class=\"wp-image-1103214 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong>Muhua Huang, Master student, Computational Social Science, University of Chicago<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Muhua Huang is a master\u2019s student in Computational Social Science at the University of Chicago, with a BA in Computer Science and Psychology from the University of British Columbia. She previously interned at MSRA Social Computing group. Her research spans human-centered AI, computational social science, and psychometrics. Currently, her work focuses on using LLM agents to simulate human personality, cognition, behavior, and social interactions.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096305,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096305\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image008-6718922431819.png\" alt=\"a man wearing a suit and tie\" class=\"wp-image-1096305 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.renhejiang.com%2F&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281285080%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=%2BvUBQefI%2BdEo2%2FpLp5KNcXYC%2Bz%2Fu7MQQpU64pE7dQqw%3D&amp;reserved=0\">Renhe Jiang<\/a>, Lecturer, Center for Spatial Information Science, The University of Tokyo<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Renhe Jiang is a lecturer at Center for Spatial Information Science, The University of Tokyo. He received his B.E. degree in Software Engineering from Dalian University of Technology in 2012, M.S. degree in Information Science from Nagoya University in 2015, and Ph.D. degree in Civil Engineering from The University of Tokyo in 2019. From 2019 to 2022, he was an assistant professor at Information Technology Center, The University of Tokyo. His research interests include AI, spatiotemporal data mining, time series forecasting, human mobility modeling, and graph learning.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096329,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096329\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image021.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096329 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fresearchers.mq.edu.au%2Fen%2Fpersons%2Frita-matulionyte&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281478440%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=0xcx5V0DDwgEz4HFQVSUS0WNQ912E%2F9ASK4sVabeZeU%3D&amp;reserved=0\">Rita Matulionyte<\/a>, Associate Professor, Law School, Macquarie University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Rita is an international expert in technology and intellectual property law, with a recent focus on legal regulation and governance of Artificial Intelligence technologies. She acquired her PhD degree from Albert Ludwig University of Freiburg\/Max Planck Institute for Intellectual Property and Competition Law (Germany, suma cum lauda) in 2010. Since then she researched and lectured in universities in Japan, Germany, Lithuania, and Australia. To date, she published over 60 peer-reviewed articles and book chapters, as well as a monograph on Applicable Law to Copyright Infringement: A Comparison of ALI and CLIP Principles. Rita is regularly invited to present in conferences in Europe, South and North America, and Asia, and has prepared reports for the European Commission, European Patent Office, and the governments of Australia, South Korea and Lithuania.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Rita has led projects on 'Government Use of Face Recognition Technologies: Legal Challenges and Solutions' (Lithuanian Research Council grant) and 'Towards Explainable AI in Healthare' (Macquarie University Research Acceleration Scheme), and was an investigator at the NSW Ombudsman project 'Mapping Automated Decision Making Tools in Administrative Decision Making in NSW' (led by Prof Kimberlee Weatherall). Previously she was a recipient of a research grant by the Japanese Society for the Promotion of Science for her project on 'The Law Applicable to Copyright'.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>She is a Lead of the Emerging Technologies Workstream at the Australian Society for Computers and Law (AUSCL), a member of Australia Standards, Committee IT-043, a Lead of the Explainable AI research stream at the Centre for Applied Artificial Intelligence at Macquarie University, an affiliate of ARC Centre of Excellence for Automated Decision Making, a member of Macquarie University Agency and Ethics Research Centre and the Intellectual Property Association of Australia and New Zealand (IPSANZ).<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Rita is willing to supervise student projects in the areas of technology and intellectual property law, especially in the area of AI and law.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096332,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096332\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image022.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096332 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Flaw.snu.ac.kr%2Fpage_en%2Fprofessor.php%3Fwr_id%3D199&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281503645%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=x8nZI%2FNnE3wWQpGGYtSzPkdrqFRtZHG%2Ff5FDpw9b1oQ%3D&amp;reserved=0\">Sangchul Park<\/a>, Associate Professor, School of Law, Seoul National University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Sangchul Park is an associate professor at Seoul National University School of Law. He completed his doctoral degree (JSD) at the University of Chicago and his undergraduate studies at Seoul National University. His main research area is the legal oversight of AI applications and the application of ML and NLP to legal studies. At the law school, he is teaching AI &amp; law and information &amp; telecommunications law. Prior to beginning his academic career, he spent more than 13 years in private practice specializing in technology, media, and telecommunications.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096410,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096410\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/thumb-2469288056_sTi5yAgr_ss_120x.jpg\" alt=\"a man smiling for the camera\" class=\"wp-image-1096410 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/law.snu.ac.kr\/page_en\/professor.php?wr_id=185\">Stephan Sonnenberg<\/a>, Associate Professor, School of Law, Seoul National University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Stephan SONNENBERG is an Associate Professor at Seoul National University's School of Law. Prior to teaching in Korea, Stephan has taught in Bhutan and at Stanford and Harvard Law Schools in the United States. His academic focus is on social entrepreneurship, human rights, conflict management, and international development studies. He studied Law at Harvard Law School and earned a degree in international affairs at the Fletcher School at Tufts University.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096326,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096326\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image020.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096326 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fwww.dps.tsinghua.edu.cn%2Fpsen%2Finfo%2F1014%2F1051.htm&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281455046%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=D9yO6ITaGIkqgCFXr%2FhrX9T0Q%2FGFN6y8%2BJ%2FDdioIMD4%3D&amp;reserved=0\">Tianguang Meng<\/a>, Professor, Department of Political Science, Tsinghua University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Tianguang Meng is a full professor in the Department of Political Science at the School of Social Sciences in Tsinghua University, the director of The Research Center on Data and Governance, and the executive director of Tsinghua Computational Social Science Institute. His research interest includes government responsiveness, politics of information and politics of Digital Governance in China. His articles have been published in Comparative Political Studies, Governance, World development, and Comparative Politics. He earned the B.A. and Ph.D. degrees in political science from Peking University. Previously, He was a visiting scholar in Harvard University and University of California, San Diego.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096302,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096302\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/xiaoyuan-yi-1.jpg\" alt=\"a person posing for a camera\" class=\"wp-image-1096302 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/xiaoyuanyi\/\">Xiaoyuan Yi<\/a>, Senior Researcher, Microsoft Research Asia<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Xiaoyuan Yi, Senior Researcher at Microsoft Research Asia. He obtained his bachelor\u2019s and doctorate degrees in computer science from Tsinghua University. He mainly engages in natural language generation (NLG) and Societal AI research, and published 30+ papers in top-tier AI conference such as ICLR, NeurIPS, ACL, EMNLP and AAAI. He has won honors such as the Tsinghua University Supreme Scholarship, the Xinhua Net The 10 Most Influential People on the Internet, the Best Paper Award and the Best System Demonstration Award of the Chinese Conference on Computational Linguistics, Rising Star Award of IJCAI Young Elite Symposium, Outstanding Doctoral Dissertation Award by China Computer Federation (CCF), Rising Stars in Social Computing by The Chinese Association for Artificial Intelligence (CAAI) and so on.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096257,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096257\",\"mediaType\":\"image\",\"mediaWidth\":15,\"imageFill\":false,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image001.png\" alt=\"a person posing for a camera\" class=\"wp-image-1096257 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/xingx\/\">Xing Xie<\/a>, Partner Research Manager, Microsoft Research Asia<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Dr. Xing Xie is a partner research manager at Microsoft Research Asia. He received his B.S. and Ph.D. in Computer Science from the University of Science and Technology of China in 1996 and 2001, respectively. Since joining Microsoft Research Asia in July 2001, Dr. Xie has focused on data mining, social computing, and responsible AI. His work has been recognized with several prestigious awards, including the IEEE MDM 2023 Test-of-Time Award, ACM SIGKDD 2022 Test-of-Time Award, ACM SIGKDD China 2021 Test-of-Time Award, ACM SIGSPATIAL 2020 10-Year Impact Award Honorable Mention, and ACM SIGSPATIAL 2019 10-Year Impact Award. He has delivered keynote speeches at notable conferences such as MDM 2019, ASONAM 2017, and W2GIS 2011. Dr. Xie serves on the editorial boards of ACM Transactions on Recommender Systems, ACM Transactions on Social Computing, ACM Transactions on Intelligent Systems and Technology, and CCF Transactions on Pervasive Computing and Interaction. He served as program co-chair of ACM Ubicomp 2011, PCC 2012, UIC 2015, SMP 2017, ACM SIGSPATIAL 2021, ACM SIGSPATIAL 2022, IEEE MDM 2022, PAKDD 2024, and IEEE BigData 2025. Dr. Xie is a Fellow of the ACM, IEEE, and China Computer Federation.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n\n<!-- wp:separator -->\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:media-text {\"mediaId\":1096320,\"mediaLink\":\"https:\/\/www.microsoft.com\/en-us\/research\/?attachment_id=1096320\",\"mediaType\":\"image\",\"mediaWidth\":15,\"backgroundColor\":\"\"} -->\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:15% auto\"><figure class=\"wp-block-media-text__media\"><img src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2024\/10\/image017.png\" alt=\"a person posing for the camera\" class=\"wp-image-1096320 size-full\"\/><\/figure><div class=\"wp-block-media-text__content\"><!-- wp:paragraph {\"placeholder\":\"Content\u2026\"} -->\n<p><strong><a href=\"https:\/\/nam06.safelinks.protection.outlook.com\/?url=https%3A%2F%2Flaw.snu.ac.kr%2Fpage_en%2Fprofessor.php%3Fwr_id%3D110&amp;data=05%7C02%7Cv-bhuan%40microsoft.com%7C63923368599d4d2c746308dcee7049fe%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638647413281408670%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=I%2B9vqwc%2Bhmo2N0Q6%2FND7roojDPmpEqEUwhpOf9A3DoU%3D&amp;reserved=0\">Yong Lim<\/a>, Associate Professor, School of Law, Seoul National University<\/strong><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Yong Lim is an Associate Professor at Seoul National University (\u201cSNU\u201d), School of Law, where he also served as Associate Dean of Student Affairs until 2020. He is the co-founder and director of SNU AI Policy Initiative (\u201cSAPI\u201d). SAPI is one of the labs currently spearheading a project at SNU\u2019s Center for Trustworthy AI to establish normative and technical standards for AI. His areas of specialty include competition law, consumer protection, privacy and data governance. Yong graduated from Seoul National University, College of Law, and obtained his S.J.D. at Harvard Law School. Prior to joining academia, Yong practiced law at Kim &amp; Chang in Seoul, Korea. Yong was a Bok International Professor at Penn Carey Law in 2023.<\/p>\n<!-- \/wp:paragraph --><\/div><\/div>\n<!-- \/wp:media-text -->\n<!-- \/wp:msr\/content-tab -->\n<!-- \/wp:msr\/content-tabs -->","tab-content":[],"msr_startdate":"2024-11-14","msr_enddate":"2024-11-14","msr_event_time":"","msr_location":"Beijing, China","msr_event_link":"","msr_event_recording_link":"","msr_startdate_formatted":"November 14, 2024","msr_register_text":"Watch now","msr_cta_link":"","msr_cta_text":"","msr_cta_bi_name":"","featured_image_thumbnail":null,"event_excerpt":"As AI continues to advance and its societal impact deepens, it presents both unprecedented opportunities for progress and significant challenges that require careful navigation. No longer merely a tool, AI is evolving into a companion to humans, reshaping the way we live and work, and calling for new frameworks to understand and govern its role. 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