Coexisting with AI
Artificial intelligence is a system that can correctly interpret data, learn from it, and then use what it has learned to adapt in order to achieve specific goals autonomously. It improves our everyday lives, but not without risk.
AI is changing the way we do everything because it’s everywhere — from dating apps to the most advanced military weapons systems. AI does many things faster and better than humans can alone, but there are ethical and societal implications to consider.
How can we ensure that AI is beneficial — not detrimental — to humanity? What unintended consequences are we overlooking by developing technology that can be manipulated and misused?
Our goal is to better understand what changes new technologies will bring, predict how those changes will unfold, and mitigate the harms or unintended consequences they could cause while still leveraging the benefits AI provides.
To do that, our team brings students and researchers together from more than two dozen schools and units on The University of Texas at Austin campus to investigate how to define, evaluate, and build a “Good System.”
It is ethically irresponsible to focus only on what AI can do. We believe it is equally important to ask what it should (and should not) do.
Leveraging Our Interdisciplinary Research Expertise
Our team is working to establish a framework for evaluating, developing, implementing, and regulating AI-based technologies so they reflect human values at their core. Some featured research areas include:
Critical Surveillance Inquiry
We work with scholars and organizations to curate conversations and exhibitions that help people understand the social and ethical implications of surveillance.
We support an interdisciplinary faculty research community that makes monthly research presentations, and sponsor special programming to advance the understanding of dis- and misinformation.
Fair and Transparent AI
We work to create fair and transparent AI technologies that people can easily use and rely on.
Future of Work
The way people work is changing. Our research explores new ways for people and AI to work together.
Public interest TEchnology
We build teams that gather public, open, and accessible data, to integrate research with policy, journalism, and local activism.
Machine Learning and robotics
We focus on how fairness and other ethical considerations are applied in machine learning and robotics.
We serve as a resource for education, community engagement, and research at the intersections between racial justice and technology/AI.
We develop transformative technologies to achieve resiliency and sustainable growth in urban communities.
Current and Upcoming Projects
Good systems are human-AI partnerships that address the needs and values of society. Developing them is our mission.
Austin AI Housing Analysis
Project summary: A lack of affordable housing is a major problem in US cities from the Bay Area to Boston. Austin is no exception. In 2015, the Austin-Round Rock metropolitan … Keep reading
Cameras, AI, and Public Values in Smart Cities
Project summary: This project investigates comparative policies around the creation and use of video data in the public sector. As more cities deploy monitoring and sensing technologies, cameras are in … Keep reading
Countering Misinformation and Disinformation
Project summary: Older adults are especially vulnerable to believing and circulating disinformation online, and we want to enable this population to use social media more responsibly. We aim to do … Keep reading
Designing Human-AI Partnerships for Information Search and Evaluation
Project summary: Our research designs and prototypes new ways to find, interpret, and evaluate online information with the goal of helping to combat rampant misinformation. Our prototypes also will enable … Keep reading
Humanist-in-the-Loop: Responsible Data Operations and Workforce Development in Libraries, Archives, and Museums
Project summary: Information and cultural heritage professionals have become increasingly interested in using data science, machine learning, and AI applications in the management of data and operations at libraries, archives, … Keep reading
Inclusive and Trustworthy AI Governance and Design
Project summary: Artificial intelligence systems increasingly automate and assist people in making managerial and governance decisions. AI manages worker routines and tasks, determines how to distribute resources within cities and … Keep reading
Inspection of City Infrastructure Via Peripheral Perception
Project summary: One of the main tasks of any city government is to keep infrastructure such as roads, signs, accessibility ramps, and sewers in perpetual working order. The first step … Keep reading
ML4GIS: Developing and Evaluating Computer Vision Methods to Enhance Access to Geospatial Data in Large Historical Map Collections
Project summary: The Austin History Center, the City of Austin and UT Libraries maintain substantial collections of scanned maps, which are needed for historical reference when conducting research or planning … Keep reading
Optimize EMS Responses During Extreme Events
Project summary: Optimizing ambulance allocation and routing is one of the most efficient ways for EMS to save more lives at virtually no cost. However, current EMS software was developed … Keep reading
Postpartum Support-Bot: An Ethically Co-Designed Chatbot for Mothers Experiencing or at Risk of Postpartum Mood and Anxiety Disorders
Project summary: Postpartum mood and anxiety disorders affect as many as one in five women globally. Left untreated, these can have major negative effects on maternal and child health and … Keep reading
Smart Cities Should be Good Cities: AI, Equity, and Homelessness
Project summary: We are working with several city of Austin offices to confront the problem of homelessness. People experience homelessness as a continuum, ranging from housing instability to incarceration, couch-surfing … Keep reading
Design of Fair AI Systems via Human-Centric Detection and Mitigation of Biases
Project summary: AI systems may not only reproduce data bias but even amplify it. Unfortunately, even defining data bias is difficult, let alone detecting and mitigating it. For example, consider … Keep reading
Probabilistically Safe and Correct Imitation Learning
Project summary: Most AI research is concerned with best case (single demo) or average case performance. However, given in many safety-critical tasks such as robotics, average case performance is often … Keep reading
Building and Testing Machine Learning Methods for Metadata Generation in Audiovisual Collections
Project summary: Audiovisual materials play a fundamental role as historical and scientific records. AV materials provide evidence for every activity on earth from endangered languages to rare bird calls to … Keep reading
Bad AI and Beyond: Exploring How Popular Media Shape the Perceived Opportunities and Threats of AI
Project summary: We will report on how media representations shape public perceptions of AI and then use what we learn to explore how we might better represent everyday interactions with … Keep reading
How African-American and Latinx Youth Evaluate Their Experiences with Digital Assistants
Project summary: As AI-driven devices and toys play an increasingly important role in children’s lives, little research has considered how social and economic disparities and cultural differences shape children’s engagement … Keep reading
Ethical Data Design for Good Systems
Project summary: Data and the systems that manage it are not neutral but, instead, are part of the process that affects how AI-based technologies work. Not all data and computer … Keep reading
Privacy Preferences and Values for Computer Vision Applications
Project summary: Technology is transforming people’s lives, but it’s a constant struggle to ensure that technology designs address people’s values and preferences, especially those of traditionally underserved groups. Computer vision, … Keep reading