Award-winning game designer Jessica Hammer will soon level up when she takes on the role of interim associate director of the Human-Computer Interaction Institute in Carnegie Mellon University's School of Computer Science. "We are lucky to do exceptional research and teaching at the HCII. Even better, we get to combine the two to shape the future of human-computer interaction," said Hammer, the HCII's Thomas and Lydia Moran Assistant Professor of Learning Science. "I want to make sure that all members of our community -- from our first-year undergraduates to the most senior faculty -- can contribute to this mission." Hammer, who has often learned the hard way how to develop a game to meet its vision, said that her training will help her ensure the department's practices and organizations are best suited to meet its goals.

A team of Carnegie Mellon University learning scientists are developing a tool that could change the way high school teachers and students approach their computer science classes. This month, Schmidt Futures announced that the team is one of the winners of their Futures Forum on Learning: Tools Competition. This award will fund tools to aid recovery from pandemic learning loss and advance the field of learning engineering. The tool, RecapCS, was created by Ember Liu and Neil Thawani with support from John Stamper, an assistant professor in the Human-Computer Interaction Institute. Liu and Thawani both graduated from the HCII's Master of Educational Technology and Applied Learning Science (METALS) program, which trains graduate students to become learning engineers and learning experience designers.

If you've heard of Carnegie Mellon University's Girls of Steel, I hope it was from someone who's participated in our program and not from a robot. Maybe you saw a young woman from Girls of Steel on the news as she constructed one of the program's 120-pound robots. Or heard that she and her teammates visited and made a presentation at the White House. Perhaps you read about their work in GeekWire. While the robots tend to get a lot of media attention, our focus is more straightforward: the girls who build them.

Renowned researchers Manuel Blum and Lenore Blum have devoted their entire lives to the study of computer science with a particular focus on consciousness. They've authored dozens of papers and taught for decades at prestigious Carnegie Mellon University. And, just recently, they published new research that could serve as a blueprint for developing and demonstrating machine consciousness. That paper, titled "A Theoretical Computer Science Perspective on Consciousness," may only a be a pre-print paper, but even if it crashes and burns at peer-review (it almost surely won't) it'll still hold an incredible distinction in the world of theoretical computer science. The Blum's are joined by a third collaborator, one Avrim Blum, their son.

The quest to understand consciousness, once the purview of philosophers and theologians, is now actively pursued by scientists of many stripes. This paper studies consciousness from the perspective of theoretical computer science. It formalizes the Global Workspace Theory (GWT) originated by cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, and others. Our major contribution lies in the precise formal definition of a Conscious Turing Machine (CTM), also called a Conscious AI. We define the CTM in the spirit of Alan Turing's simple yet powerful definition of a computer, the Turing Machine (TM). We are not looking for a complex model of the brain nor of cognition but for a simple model of (the admittedly complex concept of) consciousness. After formally defining CTM, we give a formal definition of consciousness in CTM. We then suggest why the CTM has the feeling of consciousness. The reasonableness of the definitions and explanations can be judged by how well they agree with commonly accepted intuitive concepts of human consciousness, the breadth of related concepts that the model explains easily and naturally, and the extent of its agreement with scientific evidence.

Carnegie Mellon's Robotics Academy studies how teachers use robots in classrooms to teach Computer Science, Science, Technology Engineering, and Mathematics (CS-STEM). Our mission is to use the educational affordances of robotics to excite students about science and technology. The Robotics Academy fulfills its mission by developing research-based solutions for teachers that are classroom-tested and foreground CS-STEM concepts. Visit our Research area to learn more about our projects, partners, and funding.

The Pittsburgh space robotics company Astrobotic has delivered its CubeRover to NASA's Kennedy Space Center in Florida, where the robot will undergo a battery of mobility and drop tests in a simulated lunar terrain. Co-developed by Astrobotic and Carnegie Mellon University with input from a NASA Kennedy team, CubeRover is a small, light robotic rover designed as an affordable mobile platform for scientific instruments and other payloads to operate on the surface of the moon. "Because our CubeRover is so light -- in the four-kilogram range -- it dramatically reduces flight cost, making the moon more accessible to more customers," said Mike Provenzano, Astrobotic's director of planetary mobility. CubeRover is a commercial version of Iris, a CMU-built rover scheduled to land on the moon as early as next summer.

An autonomous car programmed by a Carnegie Mellon University student team will race for the first time Sept. 24-25 when Roborace, an international competition for autonomous vehicles (AVs), begins its season on the island of Anglesey in Wales. In Roborace, each team prepares their own artificial intelligence algorithms to control their race car, but all of the teams use identically prepared AVs, compute platforms and venues. To prepare for this month's race, the CMU team spent the summer working on the fundamentals of driving and on building an optimal driving path. But this week was the first time they had the chance to run their computer code on a hardware simulator. "Our minimum goal is to be able to get the car to start driving crash-free for now," said Anirudh Koul, an alumnus of the Language Technologies Institute's Master of Computational Data Science (MCDS) program and the team's coach. But the CMU team, the first U.S. team in Roborace, is confident that it will soon be competitive with other teams that have previous experience in the racing series.

The current development of particular robots for NASA represents a methodical shift in how some Lunar or Martian vehicles are designed and how the related components or systems are included to support vehicle operation. Carnegie Mellon University and Pittsburgh-based Astrobotic are working on a lunar robot for NASA's Lunar Surface and Instrumentation and Technology Payload program, or LSITP, that is small, fast, solar-powered and will not be teleoperated nor radiation-hardened, which is quite a change from more risk-adverse prior methods. The more affordable yet dynamic approach of constructing the so-called MoonRanger is a shift from past rovers that were behemoth in size, protected from radiation and very slow, says William "Red" Whittaker, director of Carnegie Mellon University's (CMU's) Field Robotics Center, who is leading the technical development and construction of the MoonRanger. The rover will have fully autonomous operations and will provide high-fidelity 3D maps of the ice fields on the moon's south pole. The robot will be equipped with a special instrument with an optical laser designed to help guide the robot in the dark, as well as measure the ice fields and map the terrain of the pole.

Dr. David Touretzky has set out to change that. He's the founder and chair of the AI4K12 initiative, aimed at developing national guidelines for A.I. education and facilitating its instruction to students in kindergarten through 12th grade. "I looked at the national guidelines and there were just two sentences about A.I. and they were for 11th and 12th graders. I realized this was a problem," he said. Touretzky is also a Research Professor at Carnegie Mellon University and lead author of the five core concepts of A.I. education.