Leaders in AI, Robotics and Ethical Innovation Come Together at UT Austin

The symposium addressed topical issues through interdisciplinary and cross-sector discourse, with programming that included panels and research presentations on:

• Agentic AI and the changing landscape of work
• The role of robotics in health care
• The harmful traits of AI companions
• Speech generation technologies
• Advances in robotic surgery
• Fair and transparent data use
• Music and creative work in the age of generative AI
• And more

Attendees engaged with experts to examine ethical considerations and leading-edge interdisciplinary research during the two-day event. Common themes emerged, including the value of collaboration between academia, industry and government; the increasing importance of critical thinking, creativity and continuous learning as key practices to hone for students, faculty and practitioners alike; and the need to work together to better define and safeguard human agency and responsibility as we develop and use robots, AI agents and autonomous systems.

"Right now, we're in a moment where machine learning, artificial intelligence - especially generative artificial intelligence - is changing the world in many ways," said Peter Stone, department chair in Computer Science. "This is the first time these three organizations have come together to give a joint symposium, but I think, especially in this moment, it's fitting to have machine learning, robotics and Good Systems Ethical AI all together in this room."

Tuesday's opening panel set the tone for the event, with a bold exploration into the role of intelligent systems across society. Moderated by Stone, the faculty leaders of Texas Robotics, Good Systems, and the Machine Learning Lab - José del R. Millán, Ken Fleischmann and Adam Klivans, respectively - shared what they most look forward to for the future of AI, ML and robotics at UT and beyond.

Klivans discussed the value of open-source AI models in advancing responsible research and technologies, such as those being developed by the Machine Learning Lab, the Institute for Foundations of Machine Learning, and the Center for Generative AI, all powered by vast computing resources, including the largest compute cluster in academia at the Texas Advanced Computing Center. "We'll be able to train close to frontier-size models and try out a lot of ideas to find out what's really going on at these closed-source companies," said Klivans.

Millán highlighted how UT's unique collaborative culture enables the University to lead in interdisciplinary fields such as embodied AI and robotics as well as build transformative resources for the community: The University's emerging academic health system will include a state-of-the-art, digitally enabled hospital. "We have the possibility to start thinking about and start implementing how artificial intelligence, how robotics will be integrated into that future hospital," shared Millán.

Fleischmann spoke about considerations for the future of work, including government work and national security, and the importance of a people-centered and values-driven approach to AI adoption and use. "There's never been a more important time to question - what should we do?" Fleischmann emphasized.

Stone, reflecting on the unique environment at UT where researchers propel scientific discovery and technological advancement while considering the ethical implications of their work and collaborating with colleagues in the humanities and social sciences, offered encouragement.