What if machines could reason like humans? We're racing toward that reality. It's called artificial general intelligence. The question is, can we build it safely?

In the second part of our conversation with Dr. Zico Kolter, head of Carnegie Mellon University's Machine Learning Department and OpenAI board member, where he chairs their Safety and Security Committee, we explore the critical challenges facing AI development today.

Dr. Kolter addresses deepfakes and the erosion of trust in media, explaining how AI accelerates existing problems while offering potential technological solutions. We examine privacy concerns, debunking common misconceptions about how chatbots use personal data. The discussion covers data scarcity, infrastructure challenges, and the massive energy demands of AI systems.

We also explore bias in AI models, the psychological impact of human-AI relationships on vulnerable populations, and the concept of artificial general intelligence (AGI). Dr. Kolter shares his optimistic yet cautious vision for the next five years, emphasizing the importance of building AI systems that safely serve humanity's best interests.

This is the Season Two finale of Where What If Becomes What's Next from Carnegie Mellon University.

What if AI is automating the one thing that's always made us human—Intelligence itself? And how do we ensure that it's developed safely?

In this first of a two-part series, we speak with Dr. Zico Kolter, head of Carnegie Mellon University's Machine Learning Department and newly appointed OpenAI board member, where he chairs their Safety and Security Committee, to explore the critical challenge of developing artificial intelligence safely.

Dr. Kolter discusses CMU's pioneering machine learning department and outlines four essential categories of AI safety concerns: immediate security threats like data exfiltration and prompt injection; societal impacts on jobs, economy, and mental health; catastrophic risks from malicious actors wielding AI-powered capabilities; and long-term scenarios of uncontrollable superintelligence.

Unlike previous technological revolutions that automated physical labor or computation, AI represents something unprecedented—the automation of intelligence itself. Dr. Kolter argues this fundamental difference demands collaborative oversight from industry, academia, and government to ensure AI serves humanity's best interests. The conversation emphasizes why getting AI safety right matters more than ever as we integrate thinking machines into our critical infrastructure.

What if AI could help design gene therapies so precise they eliminate chronic pain while leaving other senses completely intact? And what if the secret to treating Parkinson's Disease lies hidden in the genome of a mouse?

In this episode, we explore groundbreaking advances in genetic medicine with Andreas Pfenning, Associate Professor in Carnegie Mellon University's Computational Biology Department and School of Computer Science. Professor Pfenning discusses research in his experimental lab, and how AI is revolutionizing gene therapy by making treatments more targeted while reducing toxic side effects.

The conversation covers Pfenning's work developing precision gene therapies for chronic pain originating in the spine, where AI helps identify exactly which spinal cord cells transmit pain signals while preserving normal touch and movement functions. The episode also explores KGWAS (Knowledge Graph Genome-Wide Association Study), an AI-powered tool developed at CMU in partnership with other research institutions, that helps identify genetic problems that can cause rare diseases or disorders.

Pfenning shares insights from his collaboration on the ambitious Vertebrate Genomes Project, which aims to map genomes from more than 500 vertebrate species. This massive international effort is revealing surprising genetic similarities across species that could unlock new treatments for human diseases including Parkinson's, Alzheimer's, and other neurological disorders.

The discussion also highlights how machine learning is accelerating the path from laboratory discovery to clinical applications, with promising results already emerging in Parkinson's disease treatment trials.

What if AI could help emergency responders make split-second decisions that save lives during disasters? And what if that same technology could be used in healthcare to identify which patients desperately need care before it's too late?

In this episode, we explore how artificial intelligence is revolutionizing emergency response and healthcare decision-making. Host Randy Scott interviews Aarti Singh, a professor in the Machine Learning Department at Carnegie Mellon University and the director of the National Science Foundation's AI Institute for Societal Decision Making.

Professor Singh discusses breakthrough technologies like the CLARKE System, developed by the Institute’s partner Texas A&M University, which can analyze disaster damage to 2,000 homes in just seven minutes using drone footage and AI, compared to hours or days with traditional methods. The Institute has trained more than 60 emergency managers from 38 agencies on using the CLARKE System for rapid damage assessment and resource allocation during disasters like hurricanes and wildfires.

In healthcare, Singh discusses how AI is addressing the U.S.'s alarming maternal mortality rate—the worst among developed nations—by creating patient risk profiles and prioritizing health care worker interventions or text-message alerts to the maternal patients. Field tests in India showed a 30 percent improved patient engagement. The conversation also covers the Institute's work on responsible AI adoption frameworks, emphasizing the importance of accountability, proper training, and human-AI collaboration to ensure these life-saving technologies can be trusted and effectively integrated into real-world emergency and healthcare systems.

What if robots could pick apples without bruising them, detect diseases in tomatoes before farmers can see them, or even help prevent catastrophic wildfires?

In this episode, host Randy Scott speaks with Professor George Kantor from Carnegie Mellon University's Robotics Institute. Professor Kantor’s two decades of pioneering work in agricultural robotics are shaping the future of food and sustainability.

As the global population races toward 10 billion by 2050, robotics and AI may be key to feeding the world while protecting the planet. Professor Kantor shares breakthroughs in robotic harvesters, disease-detecting drones and robots and AI-driven "digital twins" that simulate and optimize farm operations. He also explains how robots are optimizing specialty crops, balancing labor shortages, and reducing reliance on pesticides and fertilizers with real-time monitoring of nitrogen—all while lowering the negative impact of agriculture on the environment. He explains how robots and drones are helping to prevent wildfires in the Safe Forest program by mapping and then clearing potentially flammable vegetation.

Building on last July's Season One discussion about teaching robots to pick apples, Professor Kantor shares new "learning from demonstration" methods where robots learn by analyzing videos of humans performing complex tasks.

The conversation extends beyond the farm to CMU's new Robotics Innovation Center at Hazelwood Green in Pittsburgh, which will be a world-class testing facility for next-generation robots. He also discusses the Girls of Steel Robotics program, which he co-founded 15 years ago and runs through CMU—a K-12 initiative giving students of all genders and ages hands-on robot-building experiences. The program will soon move to the new facility.

From apple orchards to tomato greenhouses to wildfire prevention, discover how robotics is becoming agriculture's most essential tool and a source of hope for a resilient and sustainable future for farming.

Imagine a telescope so powerful it could give us a whole new picture of the cosmos and help answer some of the biggest questions about the universe–if we can handle the data.

From a mountaintop in Chile, the Vera C. Rubin Observatory is revolutionizing astronomy. The Observatory began capturing images of the entire night sky in June 2025, launching the most ambitious astronomical survey in history. This powerful telescope–with the world’s largest digital camera–generates 20 terabytes of data daily, creating a decade-long "movie" of the cosmos through its Legacy Survey of Space and Time (LSST) initiative.

But without the development of innovative software, algorithms and computational systems, much of what the telescope is capturing would be unusable.

In this episode, host Randy Scott talks with Carnegie Mellon University’s Professor Rachel Mandelbaum and Jeremy Kubica, who take us behind the scenes to reveal the computational innovations and interdisciplinary collaborations making this massive data collection scientifically useful. Through the LINCC Frameworks initiative, their team has developed innovative open-source software that enables scientists worldwide to analyze data from the telescope with unprecedented access, collaboration and scale. Professor Mandelbaum is the interim head of Carnegie Mellon's Department of Physics and CMU's lead for the LINCC Frameworks, and Jeremy Kubica is the Director of Engineering for the LINCC Frameworks.

Our conversation explores groundbreaking technologies like algorithms for measuring galaxy shapes and gravitational lensing effects, software for detecting faint and distant moving objects in our solar system that we otherwise couldn’t see, and collaborative tools that bring researchers to the data rather than downloading massive datasets locally.

Over the next ten years, this project will revolutionize our understanding of dark matter, the formation of our solar system, and the fundamental nature of the universe itself.

We first reported on the Rubin Observatory in our podcast’s first season in the episode “Stellar Observations: AI’s Journey Into the Cosmos.”

The universe is about to reveal its secrets—if our computers can keep up.

The sound of someone chewing can be annoying. But what if only one specific person's chewing bothered you? And what if it went beyond annoyance to actual pain?

In this the second of a two-part episode on the Science of Sound, host Randy Scott discusses with Professor Laurie Heller what happens when our brain's relationship with sound goes wrong. Heller is a professor of psychology at Carnegie Mellon University, where she runs the Auditory Perception and Cognition Lab. The discussion covers various sound-related disorders including tinnitus, auditory processing disorder, and misophonia—a debilitating condition where certain sounds like chewing trigger intense emotional reactions. Through an engaging demonstration on the podcast, Professor Heller reveals how our brain's recognition of where a sound comes from, rather than its actual acoustics, controls our emotional responses. The episode also examines noise pollution's impact on wildlife, technological innovations such as enhanced virtual reality experiences, and AI's role in creating and detecting fake audio. Professor Heller further discusses what’s next for hearing technology, including better treatments for sound disorders and more sophisticated hearing aids that can adaptively filter environmental sounds.

We live in an increasingly noisy world. Our cities are louder than ever. Our devices can pump dangerous levels of sound directly into our ears. One in eight kids has permanent hearing damage. And while we count calories and track our steps, most of us have no idea how much acoustic damage we're absorbing every day.

In Part 1 of a two-part episode, we explore the Science of Sound and its profound impact on our lives. Host Randy Scott speaks with Laurie Heller, a professor of psychology at Carnegie Mellon University where she runs the Auditory Perception and Cognition Lab.

We speak with Professor Heller about how our brains process sound, the dangers of noise pollution, and the importance of protecting our hearing. The conversation delves into the physiological aspects of hearing and how too much noise can lead to not only hearing loss but other health consequences such as high blood pressure, sleep disturbances and even heart disease. Professor Heller gives us practical tips for safeguarding our auditory health and emphasizes the need for managing a balanced sound environment that promotes hearing safety and well-being.