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Episode 3 08.03.2010
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What happens when engineered systems become too complex for humans to understand, let alone control? Riccardo Sanz argues that the path forward requires machines capable of controlling themselves , and that this leads, perhaps inevitably, toward machine self-awareness. Subscribe for more from the Convergent Science Network podcast series. Riccardo Sanz approaches consciousness not from philosophy or neuroscience, but from the hard edge of control engineering. In this interview, he explains why traditional control theory breaks down when the controller itself becomes so complex that it can fail in ways no human operator can diagnose. Modern countrywide electrical grids, flight control systems, and computing infrastructures already exceed human comprehension during failure states , leading to blackouts, crashes, and cascading breakdowns. Sanz’s provocative claim is that the only scalable solution is to give these systems the capacity to model and manage themselves. This is not, he insists, an attempt to mimic human consciousness. Instead, his research group arrived at concepts of self-awareness and self-modeling from purely technical requirements for robust, adaptive control. The convergence with consciousness research was discovered after the fact, when they found that the competences they needed, self-monitoring, self-repair, cognitive flexibility, overlapped with properties that consciousness researchers attribute to sentient systems. The distinction matters: Sanz argues that copying the human brain would reproduce its evolutionary limitations, whereas extracting the underlying principles of self-awareness could yield systems that far exceed human capabilities in speed and information integration. The conversation probes the risk of infinite regress , if a controller needs a meta-controller, what controls that? Sanz proposes that each successive layer of self-representation compresses complexity, collapsing into increasingly compact models until the system converges on a unified self-description. He draws parallels to industrial process control, where hierarchies of control loops ultimately reduce to a single variable like profitability, but notes that current systems lack the self-awareness to handle their own failures. On the question of existential risk from superintelligent machines, Sanz is sanguine. He believes that by the time engineering reaches the sophistication needed to create deeply self-aware systems, the technology for bounding their behavior will be equally mature. His core message is a call for rigor: the fragmentation of control engineering, neuroscience, and philosophy into separate communities with incompatible vocabularies is the real barrier to progress.
Tagged as:
consciousness control engineering machine consciousness Self-awareness
About the author call_made
Both the triumphs of humanity and its most evil deeds have resulted from collaboration. In a time where humanity is required to aspire to the former and minimize the latter, the question arises of how collaboration arises and why it fails. Surprisingly, this phenomenon, so central to who we are, is not well understood. Hence, a collaborative effort is required to understand collaboration in its full biological, psychological, sociological, cultural, and economic complexity and to translate this understanding into operational impact. This series of podcasts is one step toward achieving these complementary goals. The Collaboration Podcast presents interviews with people who are central orchestrators of collaboration in various domains including business, government, science, art, health, sustainability, and the military. The discussions were conducted by Prof. Dr. Paul F.M.J. Verschure and members of the Program Advisory Committee of the Ernst Strungmann Forum on Collaboration (https://www.esforum.de/forums/ESF32_Collaboration.html) during 2021 and had the goal to sketch a map of opportunities, challenges, and obstacles in human collaboration. The forum took place in May 2022, and now we would like to share this series of interviews with a broader audience. The full report of the Forum will be published in 2023 by MIT Press. The podcast was produced by the Convergent Science Network (https://www.convergentsciencenetwork.org/). Context: The stability of social systems depends critically on realizing sustainable methods of “collaboration,” yet how and by which means collaboration is achieved is not clearly understood; neither are the conditions or processes that lead to its breakdown or failure. Collaboration can be understood as cooperation between agents toward mutually constructed goals. Part of the reason for our lack of understanding is that the phenomenon of collaboration is, by nature, a highly multidisciplinary problem, and effective research into its complexities has been difficult to achieve across the broad range of scientific and technical disciplines involved. The need for a fundamental understanding of collaboration, however, has become increasingly important. Not only does humankind demand answers as it attempts to address critical challenges at multiple scales (e.g., climate change, migration, enhanced automation, social and economic inequality), but ever-increasing technological and economic means of interconnecting people and societies are disrupting long-established, familiar patterns of how we interact. Radical technological changes that are ongoing have the potential to reshape collaboration in ways that are currently hard to predict or influence (e.g., by altering configurations in interaction, information creation, and modes of communication). On one hand, such changes could disrupt hitherto stable forms of collaboration by affecting critical communication channels and traditional roles, as can be observed in the rapidly changing patterns in governance, commerce, and social interaction. Conversely, technology could lead to the emergence of novel, successful forms of collaboration that deviate from traditional “hierarchical” architectures. Evidence of this can be seen in areas as diverse as highly automated manufacturing plants, the open science movement, collaborative software repositories, user-centered services, and the sharing of economy-based modes of organization. Without a fundamental understanding of the mechanisms, processes, and boundary conditions of collaboration, it is not possible to evaluate or predict which of these possible scenarios are sustainable or even plausible. The Forum “How Collaboration Arises and Why it Fails” (May 8–13, 2022, Location: Frankfurt am Main, Germany) Chairs: Andreas Roepstorff and Paul Verschure Program Advisory Committee: Jenna Bednar, Julia R. Lupp, Bhavani R. Rao , Andreas Roepstorff, Ferdinand von Siemens, and Paul Verschure
Exploring the convergence of neuroscience, robotics, and AI through conversations with leading researchers since 2010.
A project of the Convergent Science Network Foundation.
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