ACM ByteCast

Association for Computing Machinery (ACM)

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.

  1. 30/06

    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.

    31 min

  2. 28/05

    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.

    41 min

  3. 14/05

    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.

    28 min

  4. 16/04

    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.

    36 min

  5. 31/03

    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.

    57 min

  6. 26/02

    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.

    51 min

  7. 4/02

    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.

    44 min

  8. 14/01

    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.

    43 min
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Sobre

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.

Informação

  • Autoria
    Association for Computing Machinery (ACM)
  • Anos em atividade
    2020 - 2026
  • Episódios
    87
  • Classificação
    Para todos
  • Copyright
    © Copyright 2020 All rights reserved.
  • Site do programa
    ACM ByteCast

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