The Turing Podcast

The Alan Turing Institute

The Turing Podcast is an exciting podcast from The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.

  1. 2 days ago

    Cleared for Takeoff: Navigating the Future of AI Air Traffic Control

    This special episode of the Turing Podcast revisits Project Bluebird – the project that featured on our very first ever episode on the podcast in 2020! Host Amelia Jabry is joined by Ben Carvell, an aviation researcher leading AI agent design on Project Bluebird, and Andrew “Andy” Pace, a London terminal air traffic control officer (ATCO), who describes ATCO work, sectorisation, radar-based operations, and the still-analogue reliance on voice. They examine the growing complexity of air traffic control as traffic returns to, and surpasses, pre-COVID levels and the added challenges from drones, new aircraft types, and emissions constraints, stressing human cognitive limits in a safety-critical environment. Bluebird is a multi-year partnership between the Alan Turing Institute, NATS, and the University of Exeter with three themes: building a high-fidelity digital twin, developing virtual controller agents using methods from rules to optimisation and reinforcement learning, and addressing trust/explainability. Join Amelia, Andy and Ben as they discuss the challenges and opportunities of building an AI system to assist ATCOs in one of the most safety-critical industries in the world.    00:00 The Hidden Chessboard at the heart of Air Traffic Control 00:37 Meet Ben Carvell and Andy Pace 03:20 What Air Traffic Control Officers (ATCOs) Do 06:20 Safety Rules for aviation and the moral responsibility of ATCOs 08:00 Introducing Project Bluebird 08:52 3 Main themes of Bluebird’s research: Digital Twins, AI Agents for Air Traffic Control, and Trust 10:30 The legal and moral responsibility of Air Traffic Control 12:20 The Science: The Physics Informed ML (PML) behind Bluebird. Including dealing with variability and the unknown. 14:55 Rules Optimisation versus Reinforcement Learning (RL) 15:50 A blast from the past 17:40 A collaboration with Johns Hopkins University tackling the issue of explainability in RL introducing ‘Relevant traffic’  20:36 TRUST: Safety Minima vs Collisions in Airspace – what is ‘non-negotiable’? 23:40 Interrogating the AI’s logic and maintaining trust 24:00 A curriculum for machines? The AI’s and ATCOs final exam 26:00 Bringing an ATCO onto project Bluebird – tool support for ATCOs 30:00 Intuition vs learning – the ‘mystical ATCO scan’  32:30 The ever-crowding airspace and increasing challenges to ATCOs 33:30 They history of Bluebird: 2020 versus now 35:40 How ATCOs really feel about Bluebird 36:02 Introducing Falcon - Are humans the ultimate guarantor of safety, or is our cognitive limit the ceiling for system efficiency? 40:15 Move 37 and the potential for Discovery 43:20 Collaboration between institutions and the real outputs Bluebird has made (the game!) 44:22 Wrap Up and Find Out More

    47 min
  2. 17 Feb

    The Survival of the Fittest Route: Genetic Algorithms in Shipping and Sustainability

    How can the study of ant colonies and evolutionary theory help us ensure the resilience and sustainability of global shipping? In this episode, host Amelia Jabry is joined by Professor Adam Sobey (Mission Director for Sustainability at the Alan Turing Institute) and Senior Applied Scientist Dr. Przemyslaw (Slaw) Grudniewski from Theyr. Together, they explore the ‘evolution’ of shipping route optimisation - from early concepts proposed by Alan Turing to cutting-edge Multi-Objective Genetic Algorithms. Discover how these ‘survival of the fittest’ models are being used to navigate the complex world of charter party agreements, fuel efficiency, and autonomous vessels. They also dive into the environmental impact of rerouting, discussing how a 1% change in fuel consumption can protect vital megafauna like whales, and what the melting Arctic means for the future of global trade.   Chapter Markers 0:30 | Co-Host Introduction: Professor Adam Sobey Introduction of Adam Sobey, Mission Director for Sustainability at the Alan Turing Institute and Professor at the University of Southampton. 1:20 | Guest Introduction: Dr. Przemyslaw (Slaw) Grudniewski Introduction of Slava, Senior Applied Scientist atTheyr The history of Adam and Slava’s collaboration, starting from Slava's PhD in 2015. 4:30 | The Path to Genetic Algorithms Why the team focused on genetic algorithms, including the influence of a talk at the University of Bristol on co-evolution mechanisms. 5:00 | Why Shipping Matters: The Ever Given Incident The significance of global trade by sea (80-90%) and the 2021 Suez Canal blockage by theEver Given. 6:20 | The Sustainability Imperative Shipping currently accounts for 2-3% of world emissions, emphasizing the massive need for reduced costs and improved sustainability. 7:15 | Defining Genetic Algorithms Explaining unsupervised learning algorithms based on "survival of the fittest" and evolutionary mechanics. 8:40 | Applying Evolutionary Principles to Route Optimisation How routes are treated as individuals that create "offspring" through crossover and mutation. 10:20 | Multi-Objective Genetic Algorithms "There is no one best route"—balancing conflicting goals like voyage time vs. fuel consumption. Explaining why multi-objective approaches provide a set of optimal solutions rather than a single answer. 11:00 | Charter Party Agreements & Alternative Fuels The complexity of "rental agreements" (charter parties) and the shift toward net-zero fuels like ammonia, hydrogen, and nuclear. 12:20 | The Rise of Fully Autonomous Vessels Navigating the challenges of crewless ships and how they allow for real-time route adjustments. 13:30 | Sustainability Benefits of Autonomy Removing crew-related weight can lead to estimated fuel reductions of around 20%. 14:40 | Safety and Regulation The role of the Alan Turing Institute and Lloyd’s Register in developing standards and validation for autonomous systems. 16:15 | Risks: Cyber Threats and Bad Actors Addressing piracy, cybersecurity risks, and the safety of alternative fuel sources. 18:00 | Why Genetic Algorithms Win Comparing genetic algorithms against local search methods like A* and Dijkstra for complex, real-world problems. 19:00 | Top Performance: cMLSGA ThecMLSGA (Convolutional Multi-Level Selection Genetic Algorithm) and its 7-8% improvement over other models. This represents a saving of 50 to 380 tonnes of fuel per day for large vessels. 20:20 | History: From Alan Turing to Today How the field traces back to Turing’s 1948 ideas of "child-like" intelligence that learns and evolves. 22:20 | Ants, Tribes, and Co-Evolution Using the study of ant colonies and human tribal behaviour to understand collective fitness and reproduction. 23:50 | Scaling Solutions through Collectives Applying the concept of "collectives" to solve large-scale optimisation problems through collaboration. 25:25 | Multi-Level Selection How "groups of individuals" (collectives) can compete and work together to look at different objectives simultaneously. 26:20 | Collective vs. Convergence-Based Algorithms Why maintaining diversity in a population is more effective than focusing on a single "perfect" solution too early. Diversity provides better and more informed choices with the data at hand. 28:00 | Success Stories: TVOS and Whale Protection TheTVOS (Theyr Voyage Optimisation Software) and its real-world impact. The importance of protecting marine life and megafauna. 29:50 | Navigating the Environment The difficulty of rerouting massive ships and the role of deep learning vs. genetic algorithms in icy environments. 32:50 | The Arctic and New Trade Routes How melting sea ice is opening new routes and the resulting need for specialized "ice-class" vessels. 35:50 | Industry Adoption and Client Surprises Overcoming the lack of maritime background to deliver results that surprise industry veterans. 38:30 | The Future: Power Prediction Models What’s next for the field, including more advanced predictive modelling. 41:00 | Summary and the Power of Collaboration A hopeful look at how the Alan Turing Institute acts as a convening power for sustainability research.

    43 min
  3. 06/11/2025

    Navigating Change: AI in Arctic Sea Ice Forecasting

    The Arctic is undergoing rapid changes due to climate change, making sea ice forecasting increasingly important. In this episode of the Turing Podcast, hosts Amelia Jabry and Dr. Sophie Arana discuss the critical role of AI models like IceNet in predicting sea ice conditions and aiding conservation efforts. Featuring Dr. Ellie Bowler from the British Antarctic Survey, the conversation dives into the technical details of IceNet, its applications for wildlife conservation, and the challenges of predicting sea ice dynamics. The discussion also covers the importance of these predictions for indigenous communities and wildlife that rely on the frozen Arctic landscape. Learn how AI is revolutionising our approach to these urgent environmental challenges. Read more about our environmental forecasting work here: https://www.turing.ac.uk/blog/democratising-environmental-forecasting-age-ai  Explore IceNet: https://icenet.ai/ Find out more about Dr Ellie Bowler's publications: https://www.bas.ac.uk/profile/eller/ Read more about Dr Sophie Arana here: https://www.turing.ac.uk/people/dr-sophie-arana    Chapters: 00:00 Introduction to Arctic Climate Change 00:39 Meet the your host Amelia and co-host Dr Sophie Arana  00:57 Understanding the Role of a Research Application Manager 01:47 Introduction to ICE Net 02:47 AI vs. Traditional Physics-based Forecasting Models 03:40 Human Expertise and AI Collaboration 04:56 Introducing Dr. Ellie Bowler and her sea ice and caribou migration forecasting research 06:21 Challenges in Sea Ice Forecasting 10:01 Caribou Migration and Conservation 12:30 Impact of Human Activities on Arctic Wildlife 16:38 Innovative Conservation Methods 23:25 Future of ICE Net and AI in Conservation 26:54 Conclusion and Further Resources

    28 min

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The Turing Podcast is an exciting podcast from The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.

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