Academic Discussions

Sustainable Urban Futures: Building for Wellbeing

By 2050, over 70% of the world's growing population will live in urban areas. While cities drive development and innovation, their rapid growth has also created environmental, economic, and social sustainability challenges. The built environment plays an essential role in addressing these challenges in cities and ensuring the sustainability of people and the planet. In this talk, Sarah Billington will share insights on the impact that buildings and their supply chains have on human wellbeing, and the inspiring collaborations that lead to innovative solutions.

About the Speaker

Sarah Billington is the Chair and UPS Foundation Professor of Civil & Environmental Engineering and a Senior Fellow in the Woods Institute for the Environment at Stanford University. She is an expert in sustainable, durable construction materials. Her current research focuses on the impact of building design and materials on human wellbeing with projects related to biophilic design, affordable housing, and ethical supply chains. The goal of her research program is to provide building occupants, designers, and owners with insight and tools to achieve built environments that meet their needs and to design interventions and adaptations that support human wellbeing over time while preserving privacy.

What Did the Global Year of Elections Mean for Democracy: 2024 in Perspective

The year 2024 saw more people voting in competitive, multiparty elections around the world than ever before in a single year. In several countries, democratic backsliding was reversed. In other countries, the results were more ambiguous or disappointing to pro-democracy forces. We will evaluate the results from around the world and assess the status of the global democratic recession.

About the Speaker

Larry Diamond is William L. Clayton Senior Fellow at the Hoover Institution, Mosbacher Senior Fellow in Global Democracy at the Freeman Spogli Institute for International Studies, and a Bass University Fellow in Undergraduate Education.

YOU ARE A CREATOR

Buckle up and get ready for a fast paced, mini d.school crash course on essential design tactics. We’ll highlight how doing and failing will lead to velocity and success in your work and life.

About the Speaker

Grace Hawthorne is an entrepreneur, artist, author and educator. She is the Founder/CEO of Paper Punk and Foldmade, and an Adjunct Professor at Stanford University's design institute (aka: the d.school) where she has taught courses on creativity, innovation and failure for over fifteen years and spearheaded a groundbreaking research project on creative capacity building published in Science and covered by Wired magazine. Previously, she founded ReadyMade, the culturally groundbreaking design magazine and co-authored the critically acclaimed book on reuse design, ReadyMade: How to Make Almost Everything (Random House/Potter). Her products can be found on the shelves of mass retailers and her artwork has been exhibited in several national museums including the Smithsonian Cooper-Hewitt Design Museum Triennial. Grace holds an MBA from the Anderson School at UCLA, MFA from UCLA’s School of Film and Television, and a BA in Visual Communication from UC Berkeley. Grace dedicates her life to making things and experiences that cultivate human creativity through the marriage of art + commerce. Her new book titled, Make Possibilities Happen: How to Transform Ideas into Reality is part of Stanford d.school’s design book series.

Human-Centered AI: From technical innovations to societal implications and applications

This panel discussion focused on human-centered AI, brings together interdisciplinary faculty members to discuss technological breakthroughs, real world applications and AI governance. 

A related talk: later today at 1:30pm in CEMEX, HAI Senior Fellow and Music/CS professor Ge Wang will be speaking about AI and creative expression, posing the question, "what do we (really) want from it all?"

About the Panelists

• Emily Alsentzer: Emily Alsentzer is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science at Stanford University. The core goal of her research is to augment clinical decision making and broaden access to high quality healthcare through the use of machine learning (ML) and natural language processing. She leverages heterogeneous clinical data, such as electronic health records and genomic data, to provide actionable insights to clinicians, researchers, and patients and develop new methods to infuse biomedical knowledge found in knowledge graphs and text into machine learning algorithms. Her work is motivated by the question: how can we design trustworthy machine learning methods that excel in settings with limited annotated data and can be deployed safely and effectively into clinical workflows? Previously, she was a postdoctoral fellow at Brigham and Women’s Hospital and Harvard Medical School (HMS) where she worked to deploy ML models within the Mass General Brigham healthcare system. She received her PhD from the Health Science & Technology (HST) program at MIT & HMS, co-advised by Zak Kohane and Pete Szolovits. During her PhD, she created ClinicalBERT, a language model trained on electronic health records that has millions of downloads on HuggingFace, and developed SHEPHERD, a graph neural network approach for the diagnosis of patients with rare genetic diseases in the Undiagnosed Disease Network.
• Neel Guha: Neel is a JD-PhD student in Computer Science at Stanford University. He is part of the Hazy Research Lab, Stanford Center for Research on Foundation Models, and RegLab. He graduated with a MS in Machine Learning from Carnegie Mellon University ('19) and a BS (with Honors) in Computer Science from Stanford University ('18). He is supported by the Stanford Interdisciplinary Graduate Fellowship (SIGF) and the HAI Graduate Fellowship. Neel's research lies at the intersection of artificial intelligence/machine learning (AI/ML) and law. His work explores four questions: (1) How can ML advance our understanding of the law and legal institutions? (2) How should we govern AI? (3) What types of legal reasoning can large language models (LLMs) perform? (4) How can LLM performance be improved without labeled data or human supervision?
• Christopher Manning: Christopher Manning is the inaugural Thomas M. Siebel Professor in Machine Learning in the Departments of Linguistics and Computer Science at Stanford University, Director of the Stanford Artificial Intelligence Laboratory (SAIL), and an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). From 2010, Manning pioneered Natural Language Understanding and Inference using Deep Learning, with impactful research on sentiment analysis, paraphrase detection, the GloVe model of word vectors, attention, neural machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, and summarization, work for which he has received two ACL Test of Time Awards and the IEEE John von Neumann Medal (2024). He earlier led the development of empirical, probabilistic approaches to NLP, computational linguistics, and language understanding, defining and building theories and systems for Natural Language Inference, syntactic parsing, machine translation, and multilingual language processing. In NLP education, Manning coauthored foundational textbooks on statistical approaches to NLP and information retrieval and his online CS224N Natural Language Processing with Deep Learning course videos have been watched by hundreds of thousands. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). Manning has a B.A. (Hons) from The Australian National University, a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023.
• Elena Cryst (Moderator): Elena Cryst is the Director of Policy and Society at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) where she leads the the organization's efforts to bring Stanford's cutting-edge AI research to policymakers worldwide. She also builds collaborations with civil society, philanthropy, and social impact leaders to understand how to better understand the concerns and passions of these communities with the development of these technologies. Elena has previously served in director roles at both the Stanford Institute for Economic Policy Research and the Freeman Spogli Institute for International Studies, including at that institute's Cyber Policy Center, Center for International Security and Cooperation, and Center on Democracy, Development and the Rule of Law. She is passionate about brining informed, cutting-edge, empirical research into the public dialogue. Elena received her BA with honors in International Relations and MA in Latin American Studies, both from Stanford University, and her MBA from the University of California, Berkeley Haas School of Business.

Era of Noise: From Fake News to Future of Journalism

Reading the daily news was once a basic task. However, a fragmented media landscape of outlets that abide by different journalistic standards has ushered in an unprecedented era of noise. After spending nearly two decades reporting on foreign affairs for national and international news outlets, Janine Zacharia has spent the past 13 years teaching Stanford students how to report, write, and understand the news. Today, she not only has to encourage them to read the news, she needs to teach them how to do so—the advent of artificial intelligence makes this even more urgent. Join her in learning journalism fundamentals, and explore ways we can both restore respect for credible fact-based news.

About the Speaker

Janine Zacharia, a former journalist for the Washington Post, Bloomberg, Reuters and other news outlets, is the Carlos Kelly McClatchy Lecturer in Stanford's Department of Communication and a winner of the 2020-21 Dean’s Award for Distinguished Teaching in the School of Humanities and Sciences. She is the author of several playbooks including, How to Report Responsibly on Hacks and Disinformation, and Polarization and the Press: 12 Ways to Restore Respect for Your Reporting.

Artful Design & Artificial Intelligence: What Do We (Really) Want from It All?

How do we (want to) live and work with artificial intelligence? How might we artfully design tools and systems that balance machine automation and human interaction? And perhaps the most basic question of all, what do we (really) want from AI? In this presentation, we will engage with these questions through an artful tool-building lens, considering factors such as human creativity, education, and how we might want to live with our technology. As a case study, we will draw from the teaching of "Music and AI", a critical-making course at Stanford, and explore the power of human creativity in using AI not as an "oracle", but as a tool for creative expression.

About the Speaker

Ge Wang is an Associate Professor at Stanford University’s Center for Computer Research in Music and Acoustics (CCRMA). He researches the artful design of tools, toys, games, musical instruments, programming languages, expressive VR experiences, and interactive AI systems with humans in the loop. Ge is the architect of the ChucK audio programming language, the director of the Stanford Laptop Orchestra and the Stanford VR Design Lab. He is the Co-founder of Smule and the designer of the Ocarina and Magic Piano apps for mobile phones. He is a Senior Fellow and a Faculty Associate Director of Stanford Human-Centered AI Institute (Stanford HAI). A 2016 Guggenheim Fellow, Ge is the author of /Artful Design: Technology in Search of the Sublime/, a photo comic book about how we shape technology -- and how technology shapes us.