Good Systems Call for Undergraduate Researchers

Although the application date for this project is past, the project is still ongoing. You may still wish to contact this professor about other ways of getting involved with this work. Please attend an info session or contact email for more information.

Opportunity Overview: Good Systems is a University of Texas at Austin research grand challenge with the goal of designing AI technologies that benefit society. We believe AI-based systems should be developed in accordance with broadly accepted values, such as equity, justice, privacy, safety, transparency, and trust to create the socially beneficial AI-based technologies we call “good systems.” Our campus-wide research effort brings students and researchers together from fields such as architecture, communication, engineering, informatics, liberal arts, and natural sciences to investigate how to define, evaluate, and build “good systems.”

Good Systems seeks undergraduates to participate in Good Systems core research projects over a ten-week period (normally, from June 6, 2022 to August 12, 2022). Undergraduate researchers should apply to support one of the following projects:

  • AI & the Future of Racial Justice: Explores racial disparities in AI-based systems and seeks to design and implement solutions in the areas of public safety, transportation, and health.
  • Being Watched: Embedding Ethics in Public Cameras: Investigates the social acceptance of cameras and video data and how to develop technical solutions that will satisfy privacy concerns.
  • Designing Responsible AI Technologies to Curb Disinformation: Employs machine learning to understand how disinformation arises and spreads and how to design effective human-centered interventions.
  • A Good System for Smart Cities: Seeks to build a system that will link city datasets to predict the effects of urban development projects, including Austin’s Project Connect.
  • Living and Working with Robots: Works to overcome the technical and social hurdles to deploying robots by building and studying them in the communities where they will be used.
  • Making Smart Tools Work for Everyone: Designs smart hand tools that have embedded AI to empower workers to accomplish more while keeping their jobs secure.

Good Systems is an interdisciplinary program and encourages students from all majors to apply.  

Compensation: Good Systems Undergraduate Researchers will be compensated $15/hour for a maximum of 40 hours/week for ten weeks over the course of the summer (June 6 – August 12, 2022). There are a total of 18 positions available.

Required Submission Materials:

  • Statement explaining your interest in one or more of the projects and your relevant background
  • Resumé
  • Academic Summary

Submission Instructions: Submit required documents via Qualtrics by 5 pm on April 8, 2022.

Qualifications

Students in good academic standing with a GPA of 3.0 or higher enrolled in any undergraduate major at UT Austin.

Duties
  • Participate in research activities in one of six active Good Systems core research projects,
  • Participate in Good Systems core research project team meetings,
  • Participate in supporting grant applications and publications within the core research projects, and
  • Write a blog post summarizing their activities over the summer.
Desired Length of Commitment
10 weeks

I'M INTERESTED IN THIS PROJECT. WHAT SHOULD I DO NEXT?

The Office of Undergraduate Research recommends that you attend an info session or advising before contacting faculty members or project contacts about research opportunities. We'll cover the steps to get involved, tips for contacting faculty, funding possibilities, and options for course credit. Once you have attended an Office of Undergraduate Research info session or spoken to an advisor, you can use the "Who to contact" details for this project to get in touch with the project leader and express your interest in getting involved.

Have you tried contacting professors and need more help? Schedule an appointment for additional support.