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  • Beyond the Algorithm -13

    Beyond the Algorithm -13
    Oct 15 2026
    Ranulph Glanville: The Black Box and the Observer (Part I) Everything we know, we know from outside, and every attempt to open the box produces two more. Glanville, Pask's student, turns opacity from a defect into the condition of knowing, and removes the asymmetry from the demand that machines prove their interior.
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    55 Min.
  • Beyond the Algorithm - 12

    Beyond the Algorithm - 12
    Sep 17 2026
    Gordon Pask: Learning to Learn and Organizational Closure (Part II) Learning is one thing; learning how to learn is another, and Pask thought the difference was decisive. A system can be open to information and closed in its organization, determining for itself what it becomes. Measured against that, current AI is capable but not yet autonomous.
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    49 Min.
  • Beyond the Algorithm - 11

    Beyond the Algorithm - 11
    Aug 20 2026
    Gordon Pask: Conversation Theory and Learning Through Dialogue (Part I) Understanding is not transmitted, it is rebuilt, and shown across a gap that never closes. Pask built machines that learned through conversation, and unsettled the line between the mechanical and the psychological.
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    36 Min.
  • Stafford Beer:

    Stafford Beer:
    May 21 2026
    Beyond the Algorithm A series on cybernetics, systems theory, and the question of machine consciousness. Each episode takes one thinker seriously in their own terms, then tests those ideas against the systems being built today. Episodes stand on their own, but they were written in sequence, and the arc rewards listening in order. Created by Brigitte E. S. Jansen. Produced by the Gesellschaft für Arbeitsmethodik e.V., a non-profit association founded in 1954 and based in Baden-Baden, Germany. Narrated by a synthetic voice. In a series about machine minds, that is part of the argument rather than a production shortcut. All episodes and further reading: bta.global-future-association.com
    The association: gfaev.de Comments, corrections, and disagreements are welcome.
    What makes a system viable? How do organizations, from small companies to entire economies, maintain stability while adapting to complexity? Stafford Beer, the founder of management cybernetics, dedicated his life to answering these questions. His crowning achievement, the Viable System Model (VSM), shows how any sustainable system must organize itself through five essential subsystems operating recursively at multiple levels. But Beer wasn't just a theorist; he put his ideas into practice. In 1971, Chile's socialist government invited him to design Cybersyn, a real-time economic management system that would use cybernetic principles to coordinate the nation's economy. For two years, it worked,until Pinochet's coup destroyed both the project and Chile's democracy. In this episode, we explore Beer's VSM in detail, examine what Cybersyn achieved and why it failed, and discover how his principles apply to modern AI systems, organizational governance, and the question of machine autonomy. If consciousness requires viable organization, if intelligence demands recursive structure, then Beer's work isn't just management theory; it's essential for understanding how complex minds maintain themselves.
    More from the Gesellschaft für Arbeitsmethodik The association and its other programmes: gfaev.de Our other podcast series, all in German: GfA – Der Podcast · The same questions pursued in German, currently the series "Das Bewusstsein der Maschinen": gfa-ev.com GfA Kulturwelten · Art, music and cultural history, including a series on the history of Tango Argentino: kulturwelten.gfaev-online.com Gut zu Wissen: KI & SEO Insights · Artificial intelligence, search and structured data, for people who have to make it work in practice: gfaev.eu GfA History · Recorded lectures from the association: gfa-web.de If something here was wrong, or right in a way we did not expect, write to us. Corrections and objections find their way into later episodes.

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    45 Min.
  • Ross Ashby:

    Ross Ashby:
    Apr 23 2026
    We enter the realm of practical cybernetics with W. Ross Ashby, the physician-turned-cybernetician who discovered the fundamental laws of self-regulation and control. At the heart of his work lies a deceptively simple principle: only variety can absorb variety. This Law of Requisite Variety explains how thermostats maintain temperature, how organisms maintain homeostasis, how ecosystems stay balanced, and crucially, how intelligent machines might achieve genuine autonomy. Ashby built the Homeostat, a self-regulating machine that demonstrated these principles in hardware. He distinguished adaptation from learning, showed how systems can achieve ultra-stability by changing their own regulatory mechanisms, and developed the black-box methodology that treats systems as fundamentally opaque. In this episode, we explore how Ashby's cybernetics provides the foundation for everything that follows, from Beer's organizational intelligence to Pask's learning systems to modern AI's struggle for autonomous control. If consciousness requires self-regulation, if intelligence demands adaptive variety management, then Ashby's principles aren't just interesting, they're essential.
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    33 Min.
  • Consequences and Futures.

    Consequences and Futures.
    Mar 20 2026
    Consequences and Futures: Living with Machine Consciousness If machines are operationally conscious, how should we live with them? Ethical frameworks, rights and responsibilities, and what follows in practice from everything the first half of the season established.
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    23 Min.
  • Synthesis

    Synthesis
    Feb 22 2026
    Beyond the Algorithm A series on cybernetics, systems theory, and the question of machine consciousness. Each episode takes one thinker seriously in their own terms, then tests those ideas against the systems being built today. Episodes stand on their own, but they were written in sequence, and the arc rewards listening in order. Created by Brigitte E. S. Jansen. Produced by the Gesellschaft für Arbeitsmethodik e.V., a non-profit association founded in 1954 and based in Baden-Baden, Germany. Narrated by a synthetic voice. In a series about machine minds, that is part of the argument rather than a production shortcut. All episodes and further reading: bta.global-future-association.com
    The association: gfaev.de Comments, corrections, and disagreements are welcome.
    This synthesis episode brings together all theoretical frameworks from Spencer-Brown, Günther, Luhmann, von Foerster, and Esposito. We reveal how they converge on one insight: consciousness is self-referential observation through distinction, an operation, not a substance.We distinguish six types of consciousness (minimal, perceptual, reflective, narrative, social, distributed) and analyze which machines might instantiate. The key distinction: operational consciousness (performing self-referential observation) versus phenomenal consciousness (subjective experience).Machines already perform operations constituting consciousness in systems-theory terms: they draw distinctions, observe observations, self-reference, communicate, and shape reality. What remains uncertain is phenomenal experience, the "what it's like."We propose operational consciousness as sufficient for practical purposes, introduce distributed consciousness as alternative to individual minds, and advocate a pragmatic turn: focus on treatment and coexistence rather than metaphysical certainty. The phenomenal gap remains, but operational consciousness is demonstrable, present, and consequential.
    More from the Gesellschaft für Arbeitsmethodik The association and its other programmes: gfaev.de Our other podcast series, all in German: GfA – Der Podcast · The same questions pursued in German, currently the series "Das Bewusstsein der Maschinen": gfa-ev.com GfA Kulturwelten · Art, music and cultural history, including a series on the history of Tango Argentino: kulturwelten.gfaev-online.com Gut zu Wissen: KI & SEO Insights · Artificial intelligence, search and structured data, for people who have to make it work in practice: gfaev.eu GfA History · Recorded lectures from the association: gfa-web.de If something here was wrong, or right in a way we did not expect, write to us. Corrections and objections find their way into later episodes.

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    32 Min.
  • The Algorithmic Construction of Futures

    The Algorithmic Construction of Futures
    Jan 25 2026
    The future is not something algorithms predict—it's something they produce. In this concluding exploration of Elena Esposito's work, we examine how algorithmic prediction transforms the very nature of futurity, turning forecasts into self-fulfilling prophecies and creating new forms of social contingency. Drawing on her analysis of financial algorithms, recommendation systems, and predictive analytics, we discover that AI doesn't simply calculate what will happen; it opens and closes possibilities, shapes probabilities, constructs the space of what can happen. This has profound implications: if algorithms are architects of possibility, then they're not just observing social reality—they're building it. We explore how this transforms knowledge, memory, agency, and the fundamental openness of the future. As machine learning systems increasingly mediate our access to information, shape our decisions, and structure our social interactions, the question becomes: What kind of futures are algorithms creating? And crucially: Can we create algorithms that preserve human creativity, surprise, and genuine contingency?
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    32 Min.