ACM ByteCast

Hosted by Association for Computing Machinery (ACM)

Business Careers ScienceInterviews guests

Website RSS feed

Episodes

Latest episode

Jul 2026

Language

About the show

ACM ByteCast is a podcast series from ACM’s Practitioners Board in which hosts Rashmi Mohan, Bruke Kifle, Scott Hanselman, Sabrina Hsueh, and Harald Störrle interview researchers, practitioners, and innovators who are at the intersection of computing research and practice. In each episode, guests will share their experiences, the lessons they’ve learned, and their own visions for the future of computing.

Listen to episodes

60 recent

July 30, 2026Episode 881 hr 2 min

Ricardo Baeza-Yates - Episode 88

In this episode of ACM ByteCast, host Juan Miguel de Joya welcomes 2025 ACM Luiz André Barroso Award recipient Ricardo Baeza-Yates, the Search Chief Scientist at You.com, holding part-time professor appointments at KTH Royal Institute of Technology (Sweden), Universitat Pompeu Fabra (Spain), and Universidad de Chile. The award recognizes his pioneering contributions to algorithms and information retrieval as well as his leadership in fostering a vibrant transnational research community across Latin America. Baeza-Yates is widely regarded as one of the world’s foremost researchers in information retrieval, celebrated especially for pioneering innovative data structures that have shaped the field. His work has produced influential algorithms for string searching and fuzzy matching, including the well-known Shift-Or algorithm. As a practitioner, Baeza-Yates served as VP of Research for Yahoo Labs, secured 14 patents, and co-founded several startups in Chile and Spain, including Theodora AI, devoted to mitigating technological bias. Among his honors, he received the CLEI Distinction for Contributions to Computing in Latin America in 2009, the Spanish “Ángela Ruiz Robles” Award for research excellence and entrepreneurship in applied computing in 2018, the 2024 Chilean National Prize for Applied Sciences and Technology, and the first Merit Award from the Chilean Computing Science Society in 2025. Ricardo is a member of Academia Europaea, and a Fellow of ACM and IEEE. He is the co-author of Modern Information Retrieval, which became the field's most cited textbook. Ricardo shares his unconventional path into computing, from influential teachers to his discovery of the mathematical and logical beauty of algorithms. He discusses his current research, which focuses on evaluating AI by examining failures, harm, and risk rather than simply measuring success, since errors can have profound consequences in fields like medicine and law, where users may not have the expertise to recognize errors. He advocates for combining reliable search with AI to provide AI agents with accurate, trustworthy information. The conversation also explores the limitations and social consequences of increasingly replacing traditional search with AI-generated responses, including the risk of "cognitive offloading." Ricardo also shares his views on how AI is shifting computer science, offers advice for future AI developers, highlighting ACM’s principles for responsible computing, and advocates for more inclusion of Latin American perspectives in computing and AI.

June 30, 2026Episode 8731 min

Kelly Shortridge - Episode 87

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast) welcomes ACM Queue Editorial Board member Kelly Shortridge, Chief Product Officer at Fastly, where she previously served as VP of Security Products. Shortridge is the author of Security Chaos Engineering: Sustaining Resilience in Software and Systems (O'Reilly). An accomplished product executive, software innovator, and internationally recognized technical expert on resilience in complex systems, she is known for the application of behavioral economics, resilience, and DevOps principles to cybersecurity, and modernizing security programs. In the Kelly explains that security chaos engineering is really about resilience engineering—building systems that can recover quickly from inevitable failures. She makes an argument that organizations should prioritize adaptability, redundancy, and recovery over prevention, and encourages greater collaboration between security and platform engineering teams. The wide-ranging conversation covers “metrics theater,” the cost-resilience tradeoff, why software has unique advantages for simulation that we're not leveraging, and where LLMs fit (and don't fit) in security workflows.

May 28, 2026Episode 8640 min

Cynthia Rudin - Episode 86

In this episode of ACM ByteCast, Rashmi Mohan hosts 2025 ACM Fellow Cynthia Rudin, the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics, and Biostatistics and Bioinformatics at Duke University, where she leads the Interpretable Machine Learning Lab. Her lab, which seeks to design predictive ML models that people can understand, focuses on areas including healthcare, criminal justice, and energy reliability. Among her honors, she has received the Squirrel Award for Artificial Intelligence from the Association for the Advancement of Artificial Intelligence (AAAI), as well as the IJCAI John McCarthy Award. Rudin was recently named an ACM Fellow for contributions to and leadership in interpretable machine learning and societal applications. In the interview, Cynthia clarifies the crucial distinction between "interpretable" and “explainable" AI and makes the argument that true interpretability is foundational to trustworthy, ethical AI. She shares her extensive field experience collaborating with Con Edison engineers on power grid maintenance, neurologists on medical diagnostics, and the Cambridge Police Department on crime series detection, countering the widespread industry myth that AI performance must be sacrificed for transparency. She describes an innovative paradigm her lab developed to solve the "interaction bottleneck" between data scientists and domain experts, leveraging "Rashomon sets" to generate millions of equally accurate models simultaneously, using human-computer interaction (HCI) tools to create visual, encyclopedia-like interfaces.

May 14, 2026Episode 8527 min

Eric Allman - Episode 85

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast ) welcomes ACM Fellow Eric Allman, a foundational figure of the early Internet as the developer of Sendmail and its precursor Delivermail (for the original ARPANET) in the late 1970s at UC Berkeley. Sendmail is the mail transfer agent that powered a large portion of global email infrastructure through the formative years of the network and helped shape how messages move across the web. Allman is also an ACM Distinguished Engineer and was inducted into the Internet Hall of Fame in 2014. The conversation explores the origins of Internet email, the messy realities of building software that must operate at planetary scale, and what lessons today’s engineers can learn from the systems and design decisions that quietly underpin modern computing. Eric shares his work at UC Berkeley spanning a variety of domains, from user interfaces to neural networks. He and Scott touch on current AI capabilities, including their personal experiments in assistive coding with current models such as Claude, and discuss into the programming languages Python, C#, TypeScript, and JavaScript. Eric also shares candid thoughts on letting go of computing after retirement.

April 16, 2026Episode 8435 min

Peter Stone - Episode 84

In this episode of ACM ByteCast, Rashmi Mohan hosts 2024 ACM/AAAI Allen Newell Award recipient Peter Stone, Professor at the University of Texas at Austin and Chief Scientist at Sony AI. He received the award for significant contributions to the theory and practice of AI, especially in reinforcement learning (RL), multiagent systems, transfer learning, and intelligent robotics. As a leading figure in AI research, Stone has fundamentally advanced how autonomous agents learn, plan, and collaborate. His groundbreaking work on RL algorithms has enabled robots to acquire skills through experience. He is an ACM, AAAI, AAAS, and IEEE Fellow, an Alfred P. Sloan Research Fellow, and a Fulbright Scholar. At UT Austin, he is the founder and director of the Learning Agents Research Group (LARG) within the Artificial Intelligence Laboratory, as well as Founding Director of Texas Robotics. In the past, he also worked at AT&T Labs - Research and co-founded Cogitai, Inc. (acquired by Sony). Peter explores the intersection of professional research and personal passion, detailing how his lifelong love for soccer fueled his involvement in RoboCup, where he aims to develop humanoid robots capable of competing at a World Cup level by 2050. The conversation highlights his leadership as the Chief Scientist of Sony AI, focusing on landmark projects like GT Sophy, an AI that mastered the complexities of Gran Turismo, and the development of FHIBE, an ethically sourced dataset designed to mitigate bias in machine learning. Throughout the interview, Stone emphasizes the importance of ad hoc teamwork—the ability of autonomous agents to collaborate on the fly with unfamiliar partners. He also shares his passion for undergraduate research and advocacy for AI education at all levels.

March 31, 2026Episode 8357 min

Monica Bertagnolli - Episode 83

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, Sabrina Hsueh and Li Zhou host Monica Bertagnolli, a surgical oncologist, physician-scientist, and President Elect of the National Academy of Medicine—the first woman to hold that position in NAM’s history. She previously served as the 17th Director of the National Institutes of Health and the 16th Director of the National Cancer Institute (NCI), as well as President of the American Society of Clinical Oncology. In the past, she was the Richard E. Wilson Professor of Surgery in surgical oncology at Harvard Medical School, a surgeon at Brigham and Women’s Hospital, and a member of the Gastrointestinal Cancer Treatment and Sarcoma Centers at Dana-Farber Cancer Institute. In the interview, Dr. Bertagnolli shares her unique journey from Princeton engineering to cancer surgery and national leadership. She emphasizes collaboration, system thinking, and bringing an engineering mindset of “pilot, test, scale, and continuously improve” to AI in healthcare. She highlights her role in founding mCODE, an initiative to improve patient care through oncological data interoperability, and how NAM's six core commitments and ten guiding principles for responsible AI address issues of bias and equity. Dr. Bertagnolli also offers insights on the growing erosion of trust in science and medicine—and how to restore it.

February 26, 2026Episode 8250 min

Ray Eitel-Porter - Episode 82

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, Sabrina Hsueh and Li Zhou host AI safety and ethics expert Ray Eitel-Porter, Luminary and Senior Advisor for AI at Accenture and an Intellectual Forum Senior Research Associate at Jesus College, the University of Cambridge. Previously, he served as Accenture's Global Responsible AI Lead. Ray is the author of Governing the Machine and sits on several boards and councils advising on data analytics and strategy. In the interview, Ray shares how he was inspired to research responsible AI by data privacy concerns and how biased datasets harm models. He describes his objective as helping people understand the potential risks of emerging technologies in order to confidently use them. He discusses case studies from his book where companies successfully implement responsible AI practices in the workplace, and shares how his framework will be useful even as technologies continue to emerge and change. Finally, Ray offers some advice for younger professionals in AI and medicine.

February 4, 2026Episode 8143 min

Nicole Forsgren - Episode 81

In this episode of ACM ByteCast, Rashmi Mohan hosts software development productivity expert Nicole Forsgren, Senior Director of Developer Intelligence at Google. Forsgren co-founded DevOps Research and Assessment (DORA), a Google Cloud team that utilizes opinion polling to improve software delivery and operations performance. Forsgren also serves on the ACM Queue Editorial Board. Previously, she led productivity efforts at Microsoft and GitHub, and was a tenure track professor at Utah State University and Pepperdine University. Forsgren co-authored the award-winning book Accelerate: The Science of Lean Software and DevOps and the recently published Frictionless: 7 Steps to Remove Barriers, Unlock Value, and Outpace Your Competition in the AI Era. In this interview, Forsgren shares her journey from psychology and family science to computer science and how she became interested in evidence-based arguments for software delivery methods. She discusses her role at Google utilizing emerging and agentic workflows to improve internal systems for developers. She reflects on her academic background, as the idea for DORA emerged from her PhD program, and her time at IBM. Forsgren also shares the relevance of the DORA metrics in a rapidly changing industry, and how she's adjusting her framework to adapt to new AI tools.

January 14, 2026Episode 8042 min

Andrew Barto and Richard Sutton - Episode 80

In this episode of ACM ByteCast, Rashmi Mohan hosts 2024 ACM A.M. Turing Award laureates Andrew Barto and Richard Sutton. They received the Turing Award for developing the conceptual and algorithmic foundations of reinforcement learning, a computational framework that underpins modern AI systems such as AlphaGo and ChatGPT. Barto is Professor Emeritus in the Department of Information and Computer Sciences at the University of Massachusetts, Amherst. His honors include the UMass Neurosciences Lifetime Achievement Award, the IJCAI Award for Research Excellence, and the IEEE Neural Network Society Pioneer Award. He is a Fellow of IEEE and AAAS. Sutton is a Professor in Computing Science at the University of Alberta, a Research Scientist at Keen Technologies (an artificial general intelligence company) and Chief Scientific Advisor of the Alberta Machine Intelligence Institute (Amii). In the past he was a Distinguished Research Scientist at Deep Mind and served as a Principal Technical Staff Member in the AI Department at the AT&T Shannon Laboratory. His honors include the IJCAI Research Excellence Award, a Lifetime Achievement Award from the Canadian Artificial Intelligence Association, and an Outstanding Achievement in Research Award from the University of Massachusetts at Amherst. Sutton is a Fellow of the Royal Society of London, AAAI, and the Royal Society of Canada. In the interview, Andrew and Richard reflect on their long collaboration together and the personal and intellectual paths that led both researchers into CS and reinforcement learning (RL), a field that was once largely neglected. They touch on interdisciplinary explorations across psychology (animal learning), control theory, operations research, cybernetics, and how these inspired their computational models. They also explain some of their key contributions to RL, such as temporal difference (TD) learning and how their ideas were validated biologically with observations of dopamine neurons. Barto and Sutton trace their early research to later systems such as TD-Gammon, Q-learning, and AlphaGo and consider the broader relationship between humans and reinforcement learning-based AI, and how theoretical explorations have evolved into impactful applications in games, robotics, and beyond.

December 18, 2025Episode 7930 min

Dawn Song - Episode 79

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast ) welcomes ACM Fellow Dawn Song, Professor in Computer Science at UC Berkeley, Co-Director of Berkeley Center for Responsible Decentralized Intelligence (RDI), and Founder of Oasis Labs. Her research interest lies in AI safety and security, Agentic AI, deep learning, security and privacy, and decentralization technology. Dawn is the recipient of numerous awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, ACM SIGSAC Outstanding Innovation Award, and more than 10 Test-of-Time awards and Best Paper awards from top conferences in Computer Security and Deep Learning. She has been recognized as Most Influential Scholar (AMiner Award) for being the most cited scholar in computer security. Dawn is an IEEE Fellow and an Elected Member of American Academy of Arts and Sciences. She is also a serial entrepreneur and has been named on the Female Founder 100 List by Inc. and Wired25 List of Innovators. Dawn shares her academic journey in cybersecurity, which used to be a much smaller field and how the MacArthur Fellowship (aka the “Genius Grant”) and other prestigious recognitions enabled her to pursue impactful multidisciplinary research. Dawn and Scott cover a myriad of topics around Agentic AI, including current and future security vulnerabilities from AI-powered malicious attacks, Dawn’s popular MOOC at RDI, and the associated AgentX-AgentBeats global competition (with more than $1 million in prizes and resources) focused on standardized, reproducible agent evaluation benchmarks to advance the field as a public good. AgentX-AgentBeats Agentic AI Competition Berkeley RDI Agentic AI MOOC