Murray Shanahan

Join Murray Shanahan, Professor of Cognitive Robotics at Imperial College London and a principal scientist at Google DeepMind, as he explores the philosophical depths of AI. He discusses the limitations of the Turing Test, introducing the 'Garland test' for consciousness. Murray sheds light on the influence of films like 'Ex Machina' on public perception of AI. He also delves into the evolution of AI reasoning, contrasting symbolic methods with modern approaches, and questions the ethical implications of consciousness and suffering in artificial entities.

Murray Shanahan, a cognitive robotics expert at Google DeepMind, teams up with Harvard's Tomer Ullman, who focuses on cognition and development. They dive into what distinguishes human intelligence from that of large language models. The discussion unpacks the misconceptions of LLMs as intelligent beings, addressing their 'hallucinations' and inability to genuinely discern truth. They also ponder the alignment problem in AI and question whether LLMs embody real consciousness or merely simulate human-like behavior.

Murray Shanahan, a Professor of Cognitive Robotics at Imperial College London and a senior research scientist at DeepMind, dives deep into AI consciousness and the perils of anthropomorphizing machines. He discusses the limitations of current language in describing AI and stresses the need for nuanced vocabulary. Shanahan explores Reinforcement Learning and the 'Waluigi Effect,' as well as the complexities of agency in AI. He also touches on consciousness in relation to non-human entities, emphasizing how our perceptions shape understanding and the philosophical implications behind it.

Murray Shanahan, a Professor at Imperial College London, dives into the fascinating intersection of AI, consciousness, and philosophy. He explores how AI could develop a form of consciousness and what that means for humanity's self-awareness. Discussions range from the stages of cognitive awareness to the ethical implications of treating AI as sentient beings. Shanahan also contrasts human and AI experiences, examining creativity's role in technology and the philosophical shifts needed in education for future generations.

Forget what sci-fi has told you about superintelligent robots that are uncannily human-like; the reality is more prosaic. Inside DeepMind’s robotics laboratory, Hannah explores what researchers call ‘embodied AI’: robot arms that are learning tasks like picking up plastic bricks, which humans find comparatively easy. Discover the cutting-edge challenges of bringing AI and robotics together, and learning from scratch how to perform tasks. She also explores some of the key questions about using AI safely in the real world.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further reading:Blogs on AI safety and further resources from Victoria KrakovnaThe Future of Life Institute: The risks and benefits of AIThe Wall Street Journal: Protecting Against AI’s Existential ThreatTED Talks: Max Tegmark - How to get empowered, not overpowered, by AIRoyal Society lecture series sponsored by DeepMind: You & AINick Bostrom: Superintelligence: Paths, Dangers and Strategies (book)OpenAI: Learning from Human PreferencesDeepMind blog: Learning from human preferencesDeepMind blog: Learning by playing - how robots can tidy up after themselvesDeepMind blog: AI safetyInterviewees: Software engineer Jackie Kay and research scientists Murray Shanahan, Victoria Krakovna, Raia Hadsell and Jan Leike.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!  

Murray Shanahan, a Professor of Cognitive Robotics at Imperial College London and a principal research scientist at Google DeepMind, dives deep into the intersection of consciousness and artificial intelligence. He explores whether the robot Ava from 'Ex Machina' was truly conscious, critiques the Turing Test, and discusses the concept of 'Conscious Exotica.' The conversation also touches on the Attention Schema Theory and the implications of embodied cognition for AI, rounding off with thoughts on the future of consciousness in a technological age.

By now you’ve probably heard about the new chatbot called ChatGPT. There’s no question it’s something of a marvel. It distills complex information into clear prose; it offers instructions and suggestions; it reasons its way through problems. With the right prompting, it can even mimic famous writers. And it does all this with an air of cool competence, of intelligence. But, if you're like me, you’ve probably also been wondering: What’s really going on here? What are ChatGPT—and other large language models like it—actually doing? How much of their apparent competence is just smoke and mirrors? In what sense, if any, do they have human-like capacities? My guest today is Dr. Murray Shanahan. Murray is Professor of Cognitive Robotics at Imperial College London and Senior Research Scientist at DeepMind. He's the author of numerous articles and several books at the lively intersections of artificial intelligence, neuroscience, and philosophy. Very recently, Murray put out a paper titled 'Talking about Large Language Models’, and it’s the focus of our conversation today. In the paper, Murray argues that—tempting as may be—it's not appropriate to talk about large language models in anthropomorphic terms. Not yet, anyway. Here, we chat about the rapid rise of large language models and the basics of how they work. We discuss how a model that—at its base—simply does “next-word prediction" can be engineered into a savvy chatbot like ChatGPT. We talk about why ChatGPT lacks genuine “knowledge” and “understanding”—at least as we currently use those terms. And we discuss what it might take for these models to eventually possess richer, more human-like capacities. Along the way, we touch on: emergence, prompt engineering, embodiment and grounding, image generation models, Wittgenstein, the intentional stance, soft robots, and "exotic mind-like entities." Before we get to it, just a friendly reminder: applications are now open for the Diverse Intelligences Summer Institute (or DISI). DISI will be held this June/July in St Andrews Scotland—the program consists of three weeks of intense interdisciplinary engagement with exactly the kinds of ideas and questions we like to wrestle with here on this show. If you're intrigued—and I hope you are!—check out disi.org for more info. Alright friends, on to my decidedly human chat, with Dr. Murray Shanahan. Enjoy!   The paper we discuss is here. A transcript of this episode is here.   Notes and links 6:30 – The 2017 “breakthrough” article by Vaswani and colleagues. 8:00 – A popular article about GPT-3. 10:00 – A popular article about some of the impressive—and not so impressive—behaviors of ChatGPT. For more discussion of ChatGPT and other large language models, see another interview with Dr. Shanahan, as well as interviews with Emily Bender and Margaret Mitchell, with Gary Marcus, and with Sam Altman (CEO of OpenAI, which created ChatGPT). 14:00 – A widely discussed paper by Emily Bender and colleagues on the “dangers of stochastic parrots.” 19:00 – A blog post about “prompt engineering”. Another blog post about the concept of Reinforcement Learning through Human Feedback, in the context of ChatGPT. 30:00 – One of Dr. Shanahan’s books is titled, Embodiment and the Inner Life. 39:00 – An example of a robotic agent, SayCan, which is connected to a language model. 40:30 – On the notion of embodiment in the cognitive sciences, see the classic book by Francisco Varela and colleagues, The Embodied Mind. 44:00 – For a detailed primer on the philosophy of Ludwig Wittgenstein, see here. 45:00 – See Dr. Shanahan’s general audience essay on “conscious exotica" and the space of possible minds. 49:00 – See Dennett’s book, The Intentional Stance.   Dr. Shanahan recommends: Artificial Intelligence: A Guide for Thinking Humans, by Melanie Mitchell (see also our earlier episode with Dr. Mitchell) ‘Abstraction for Deep Reinforcement Learning’, by M. Shanahan and M. Mitchell   You can read more about Murray’s work on his website and follow him on Twitter.   Many Minds is a project of the Diverse Intelligences Summer Institute (DISI) (https://disi.org), which is made possible by a generous grant from the Templeton World Charity Foundation to UCLA. It is hosted and produced by Kensy Cooperrider, with help from Assistant Producer Urte Laukaityte and with creative support from DISI Directors Erica Cartmill and Jacob Foster. Our artwork is by Ben Oldroyd (https://www.mayhilldesigns.co.uk/). Our transcripts are created by Sarah Dopierala (https://sarahdopierala.wordpress.com/). You can subscribe to Many Minds on Apple, Stitcher, Spotify, Pocket Casts, Google Play, or wherever you like to listen to podcasts. **You can now subscribe to the Many Minds newsletter here!** We welcome your comments, questions, and suggestions. Feel free to email us at: manymindspodcast@gmail.com. For updates about the show, visit our website (https://disi.org/manyminds/), or follow us on Twitter: @ManyMindsPod.

Murray Shanahan, veteran AI scientist at Imperial College London and principal scientist at DeepMind, discusses the importance of embodied interaction in AI progress, potential breakthroughs in the field, and how salary inflation for commercial AI engineers may hinder research.

Murray Shanahan, a Professor of cognitive robotics at Imperial College London and senior research scientist at DeepMind, dives into the intricate tapestry of consciousness and AI. He critiques the notion of subjective experience, arguing that diverse forms of minds extend beyond the natural realm. Shanahan discusses the capabilities and limitations of large language models, cautioning against anthropomorphism. Emphasizing the importance of embodiment, he highlights that true consciousness requires real-world interaction, a quality current AI systems lack.

Murray Shanahan, a Professor of Cognitive Robotics at Imperial College London and consultant for Ex Machina, joins journalist Azeem Azhar and The Economist's Tom Standage. They delve into the fascinating idea of AI as the 'space of possible minds.' The discussion covers the ethical complexities of AI, the differences between AI and machine learning, and the societal impacts of automation. Shanahan also shares an intriguing easter egg from Ex Machina, leaving listeners reflecting on their responsibilities towards intelligent technologies.