Cross-Cutting Themes

Cross-Cutting Themes graphic

 

AI Alignment and Safety

How do we align the goals and behaviors of AI systems with human interests? How can we convey human preferences using reinforcement learning?

This theme explores the challenges of aligning AI models to human values along three research thrusts: designing a methodology for aligned reward functions, identifying harmful traits of AI companions, and developing a recommender system for intention-driven engagement with digital devices.

Theme lead:

Brad Knox
College of Natural Sciences
Computer Science

 

Knowledge, Generative AI and Power

How does the automation of creative processes shift institutional, organizational and technological power dynamics in society? How does it shift practitioners' relationships with their jobs, crafts and artistic endeavors? What criteria determine whether AI-generated content should be considered art?

This theme examines the interplay among generative AI, knowledge production and creative work, and power dynamics. It also incorporates a study on the communication of ethics within interdisciplinary AI development teams, investigating how ethical knowledge is constructed, negotiated and operationalized across disciplinary boundaries.

Theme lead:

Jared Jensen
Moody College of Communication
Journalism and Media

 

Past Theme: Work at the Human-AI Frontier

This theme explored the role of AI in the future workplace and human values of work as they relate to AI and was led by Lingyuan Li, a postdoctoral fellow in the School of Information.

 

News


Jared Jensen presents at Good Systems’ annual research kickoff event on September 26th.
Dec. 17, 2025
Meaning, Making and Machine Learning

Last year, Good Systems launched cross-cutting themes to connect its six core research projects and explore questions that span technical, ethical and social domains. One of the scholars continuing that work is postdoctoral fellow Jared Jensen, whose Knowledge, Generative AI and Power theme focuses on two interweaving concepts: how interdisciplinary teams pursue “ethical AI,” and how generative technologies are transforming creative labor and power dynamics.

Brad Knox, a research associate professor in the Department of Computer Science, discusses AI alignment at Good Systems' annual research kickoff event, on September 26, 2025, at The University of Texas at Austin.
Nov. 24, 2025
Cross-Cutting Edge

Last year, UT Austin's Good Systems initiative introduced cross-cutting themes to link its six core research projects and explore questions that span multiple fields. This year, one of the researchers who launched that effort will continue his work: computer scientist Brad Knox focuses on ensuring AI systems act in ways that reflect human values, a problem known as AI alignment.

AHOI co-leaders, from left to right: Kyle Mahowald (assistant professor of linguistics), Harvey Lederman (professor of philosophy) and Brad Knox (research associate professor of computer science)
Nov. 17, 2025
AI+Human Objectives Initiative at UT Austin Receives Grant from Coefficient Giving

The AI+Human Objectives Initiative (AHOI) at The University of Texas at Austin has received an award from the grantmaking organization Coefficient Giving. The grant will fund AHOI’s work in the emerging field of AI alignment, which seeks to ensure that AI development is aligned with the goals and values of humanity.