This conference runs from Thursday, Nov. 19 - Friday, Nov. 20. Machine learning and artificial intelligence algorithms promise many benefits such as overcoming human limitations and biases in decision-making and productivity. However, deployment of machine learning algorithms has shown that these algorithms may amplify existing biases in society, create new biases, increase privacy and cybersecurity risks, and pose novel ethical dilemmas. The conference will explore how society and organizations can maximize the benefits and minimize the risks of these algorithms. Learn more and register.

The Good Systems Disinformation Network invites you to hear a presentation from Yan Leng (McCombs School of Business) and Ying Ding (School of Information). They will present on their findings that shed light on the distinct characteristics of misinformation and its cultural, social, and political implications, during the COVID-19 pandemic. Their study also offers insights into combating misinformation in China and across the world at large. Register now. 

Tune in at 4 p.m. on Friday, Nov. 13 to hear Good Systems Founding Chair Ken Fleischmann's panel discuss how they approached creating scalable coursework and syllabi, how they can foster collaboration with other educators at their own schools and externally, and how they continually evolve an evolving practice. See the whole schedule and learn more.

In this talk, we present an ongoing collaboration with the City of Austin on assessing pedestrian road usage. The project uses high performance computing resources at TACC and artificial intelligence to analyze traffic cameras owned by the City of Austin. We explore qualitative and quantitative metrics to describe pedestrian activity and corresponding changes, which may be used to prioritize the deployment of pedestrian safety solutions, or evaluate their performance. Please email goodsystems@austin.utexas.edu to receive the meeting link.  Presentation hosted by the Smart Cities Consortium.

For more than a century and a half it has been widely-believed that the physics of diffraction imposes certain fundamental limits on the resolution of an optical system. However our understanding of what exactly can and cannot be resolved has never risen above heuristic arguments which, even worse, appear contradictory. In this work we remedy this gap by studying the diffraction limit as a statistical inverse problem and, based on connections to provable algorithms for learning mixture models, we rigorously prove upper and lower bounds on how many photons we need (and how precisely we need to record their locations) to resolve closely-spaced point sources. Moreover we show the emergence of a phase transition, which helps explain why the diffraction limit can be broken in some domains but not in others. This is based on joint work with Sitan Chen. Join us via this Zoom webinar: https://us02web.zoom.us/j/85064165756  

As part of the Planet Texas 2050 Fall Research Showcase Series, join us to hear talks on: “Texas Metro Observatory (TMO)” [Team: Katherine Lieberknecht (project lead – Architecture), Patrick Bixler (LBJ School of Public Affairs), Juliana Felkner (Architecture), Fernanda Leite (CAEE), Michael Oden (Architecture), Steven Richter (Architecture); and Nicole Joslin and Marla Torrado (CPW)] “Texas Futures Virtual Reality Experience” [Team: Fernanda Leite (project lead – CAEE), Megan (MJ) Johns (Arts & Entertainment Technologies), and Andrew Solis (TACC)] “Hurricane-Resilient Healthcare Infrastructure Modeling with Integrated Flood Prediction and Stochastic Logistics Optimization” [Team: Erhan Kutanoglu (Mechanical Engineering), Zong-Liang Yang (JGS), and John Hasenbein (Mechanical Engineering)] Register now.

This project developed an AI system that can measure the health effects of neighborhood environments in ten major US cities using citizen crowd-sourced data. The research team mapped the computed health risk scores at the census tract-level for all selected municipalities and also built an interactive website that allows users to understand how changes to their neighborhoods can affect their health. Register now.  Presentation hosted by the Smart Cities Consortium.

The Good Systems Disinformation Network invites you to hear a presentation from Josephine Lukito (School of Journalism and Media).  She will walk through how some of the most well-known and popular IRA accounts grew their followership, focusing specifically on engagement with partisan-aligned verified accounts and news media contributed to more followers for IRA accounts. This work builds upon her previous research regarding cross-platform disinformation spread (see CJR piece and Quartz piece). Register here.