The real-time city is real! As layers of networks and digital information blanket urban space, new approaches to studying the built environment are emerging. The way we describe and understand cities is being radically transformed — as are the tools we use to design them. The Senseable City Laboratory's mission—a research initiative at the Massachusetts Institute of Technology — is to anticipate these changes and study them from a critical point of view. This presentation will cover various SCL projects that showcase its engagement with societal issues to create better urban living. Learn more and add to your calendar.  Part of the Texas Smart Cities presentation series.

This study examines the documents circulated among biomedical equipment repair technicians in order to build a conceptual model that accounts for multi-layered temporality in technical healthcare professional communities. A metadata analysis informed by digital forensics and trace ethnography is employed to model the overlapping temporal, format-related, and annotation characteristics present in a corpus of repair manual files crowdsourced during collaborations between volunteer archivists and professional technicians. Based on the results of this analysis, James A. Hodges (Bullard Research Fellow, School of Information) presents findings that can assist in the development and implementation of information services and technologies for working biomedical repair technicians. Register now!  Part of Good Systems' Postdoc Interest Group.

April 22-23, 2021. Free and open to the public Streaming online This conference brings together diverse scholars whose work grapples with the challenges that climate change presents to the discipline of history. Participants will address precedents for this “unprecedented” crisis by uncovering and analyzing the historical roots and analogues of contemporary climate change across a wide range of eras and areas around the world. Can history offer an alternative to visions of the future that appear to be determined by prevailing climate models, and help provide us with new ways of understanding human agency?  Conference program, registration, and additional details forthcoming. Stay up to date on conference announcements by following the Institute for Historical Studies on Twitter and Facebook. Queries: cmeador@austin.utexas.edu.

This session of the Austin Forum will bring a panel of UT Austin faculty to share recent findings and lessons from developing fair and transparent AI technologies. In addition to being part of Good Systems, all of the faculty are also members of UT’s interdisciplinary Machine Learning Laboratory. Learn more and register. 

Featured Speakers

Matthew Lease, Associate Professor, The University of Texas at Austin, School of Information Maria De-Arteaga, Professor, The University of Texas at Austin, Information, Risk and Operation Management Department Joydeep Ghosh, Professor, The University of Texas at Austin, Department of Electrical and Computer Engineering, Chief Scientist, CognitiveScale Raymond J. Mooney, Professor, The University of Texas at Austin, Department of Computer Science Min Kyung Lee, Ph.D., Assistant Professor, The University of Texas at Austin, School of Information

Learn about Dell Technologies’ strategic vision for the future, including how AI will need to be developed over the next years to achieve their long-term goals. Dell’s decisions will help lay the groundwork for the future of the AI job market. Our conversation with company leaders also will help spur future collaborative opportunities between Dell Technologies and UT Good Systems. Presentation from Michael Shepherd (Distinguished Engineer, Dell Technologies) and Brons Larson (AI Strategy Lead, Dell Technologies).  Register now! Part of the Future of Work Research Presentation series.

Dhiraj Murthy (Professor, School of Journalism and Media) will share his COVID-related work: “Classifying COVID-19-related disinformation and misinformation using crowdsourcing and machine learning." Email goodsystems@austin.utexas.edu to request the meeting information.

Pecan Street works with advanced energy systems including smart inverters, energy storage, controlled electric vehicle charging, HVAC demand response and V2G system testing, as well as residential electrical system issues that are not being addressed by these technologies.  Scott Hinson is the CTO of Pecan Street Inc. Prior to joining Pecan Street he worked at a thin film CIGS solar module manufacturer where he led module packaging, performance, certification and reliability efforts. Additional efforts include work in the military, medical, consumer and oil industries developing power supplies, precision measurement equipment and inductive heating technologies.  Part of the Smart Cities Consortium.

Machine learning (ML) is increasingly being used to support decision-making in critical settings, where predictions have potentially grave implications over human lives. In this talk, Maria De-Arteaga (Assistant Professor, Information, Risk and Operations Management) will discuss the gap that exists between ML predictions and ML-informed decisions. The first part of the talk will highlight the role of humans-in-the-loop through a study of the adoption of an algorithmic tool used to assist child maltreatment hotline screening decisions. The second part of the talk will focus on the gap between the observed outcome that the algorithm optimizes for and the construct of interest to experts. Learn more and register now.  Part of the Ethics in AI Seminar Series hosted by The Institute for Foundations of Machine Learning.