Ethics will be at the forefront of robotics education thanks to a new University of Texas at Austin program that will train tomorrow's technologists to understand the positive -- and potentially negative -- implications of their creations. Today, much robotic technology is developed without considering its potentially harmful effects on society, including how these technologies can infringe on privacy or further economic inequity. The new UT Austin program will fill an important educational gap by prioritizing these issues in its curriculum. "In the next 10 years, we are going to live more closely alongside robots, and we want to be sure that those robots are fair, inclusive and free from bias," said Junfeng Jiao, associate professor in the School of Architecture and the program lead. "And because the robots we create are reflections of ourselves, it is imperative that technologists receive an excellent ethics education. We want our students to work directly with companies to create practices and technologies that are equitable and fair."

The National Science Foundation has selected The University of Texas at Austin to lead the NSF AI Institute for Foundations of Machine Learning, bolstering the university's existing strengths in this emerging field. Machine learning is the technology that drives AI systems, enabling them to acquire knowledge and make predictions in complex environments. This technology has the potential to transform everything from transportation to entertainment to health care. UT Austin -- already among the world's top universities for artificial intelligence -- is poised to develop entirely new classes of algorithms that will lead to more sophisticated and beneficial AI technologies. The university will lead a larger team of researchers that includes the University of Washington, Wichita State University and Microsoft Research.

Soon, though, you may be able to ask your smartphone. A University of Texas at Austin computer science team, in partnership with researchers from Cornell Tech, Georgia Tech and Facebook AI Research, has developed an artificial intelligence system that can look at a photo of an outfit and suggest helpful tips to make it more fashionable. Suggestions may include tweaks such as selecting a sleeveless top or a longer jacket. "We thought of it like a friend giving you feedback," said Kristen Grauman, a professor of computer science whose previous research has largely focused on visual recognition for artificial intelligence. "It's also motivated by a practical idea: that we can work with a given outfit to make small changes so it's just a bit better."

AUSTIN, Texas – Computer scientists at The University of Texas at Austin have taught an artificial intelligence agent how to do something that usually only humans can do--take a few quick glimpses around and infer its whole environment, a skill necessary for the development of effective search-and-rescue robots that one day can improve the effectiveness of dangerous missions. The team, led by professor Kristen Grauman, Ph.D. candidate Santhosh Ramakrishnan and former Ph.D. candidate Dinesh Jayaraman (now at the University of California, Berkeley) published their results today in the journal Science Robotics. Most AI agents--computer systems that could endow robots or other machines with intelligence--are trained for very specific tasks--such as to recognize an object or estimate its volume--in an environment they have experienced before, like a factory. But the agent developed by Grauman and Ramakrishnan is general purpose, gathering visual information that can then be used for a wide range of tasks. "We want an agent that's generally equipped to enter environments and be ready for new perception tasks as they arise," Grauman said.