Infosomatic Alignment: A Paradigm for Human-Centered AI
Dr. Leon TSVASMAN, PhD, FCybS
Polymath on a Mission ↑Radical Innovation by 2nd-order Cybernetics ??Maven in Strategic Visioning ? AI ? Deep-tech Ethics | ThinkTank Lead | ???? AI-Thinking ? Infosomatic Shift ? Age of Sapiocracy ? Sapiognosis ∞ ??????
As artificial intelligence increasingly shapes the global landscape, it raises fundamental questions about its role in defining the future of human civilization. Can AI systems truly respect and reflect the vast diversity of human experience? Or will they, if unchecked, risk homogenizing creative expression and reinforcing narrow cultural paradigms? How can we ensure that AI serves not just as a tool for optimization but as a facilitator of human potential, creativity, and cultural plurality?
In addressing these urgent issues, Infosomatic Alignment offers a paradigm that seeks to bridge AI with the self-regulatory, cognitive, and ethical dimensions of human existence. Rather than simply processing vast amounts of data or optimizing for efficiency, AI systems aligned with infosomatic principles engage dynamically with human cognition, amplifying creativity and fostering ethical growth. As I explore in my works AI-Thinking and Infosomatische Wende(Infosomatic Shift), this model invites us to reimagine technology as an enabling infrastructure that supports human flourishing.
Drawing from interdisciplinary insights in cybernetics, constructivist theory, and cognitive neuroscience, Infosomatic Alignment proposes a model of AI that amplifies human autonomy and self-realization. This framework offers a critical roadmap for ensuring that AI technologies contribute to a future where creativity, cultural diversity, and ethical engagement are at the forefront of our technological aspirations.
Cognitive Neuroscience and Relevance Realization
At the core of human cognition is relevance realization, a process where the brain filters out irrelevant data and focuses on what is most important in any given context. John Vervaeke’s work on this subject highlights the dynamic nature of human cognition, which does not passively absorb data but actively engages with it to extract meaning. This approach contrasts with traditional AI systems, which often overwhelm users with brute-force data processing, leading to redundancy and homogenization of content.
Infosomatic Alignment addresses this gap by creating AI systems that mirror the brain’s ability to focus on relevance, enhancing creativity and decision-making. Instead of producing overwhelming outputs, AI can dynamically interact with a user’s cognitive framework, fostering self-regulation and personal growth.
Overcoming Redundancy in Large Language Models
The rise of Large Language Models (LLMs) has prompted discussions about the risks of AI-generated content becoming homogenized. While LLMs can produce human-like responses, they often reflect cultural biases and reinforce dominant linguistic patterns. Research published in PNAS Nexus demonstrates that such models frequently align with Western, English-speaking cultural norms, limiting the diversity of their outputs.
Infosomatic Alignment mitigates this risk by ensuring AI systems go beyond cultural biases. By aligning AI with cognitive diversity and pluralistic values, Infosomatic AI fosters individual creativity and helps users navigate complex cultural environments more effectively. This approach encourages a deeper, more authentic engagement with technology, where AI serves as a catalyst for personal expression.
Constructivist and Cybernetic Foundations
The philosophical roots of Infosomatic Alignment lie in cybernetics and constructivism, particularly in the works of Humberto Maturana, Francisco Varela, and Heinz von Foerster. Maturana’s theory of autopoiesis—the idea that living systems are self-organizing and self-regulating—directly informs the design of Infosomatic AI, which must continuously adapt to human contexts and foster structural coupling between the system and its users.
In alignment with these ideas, Heinz von Foerster’s principle of increasing choices reflects the ethical dimension of Infosomatic Alignment. Von Foerster argues that technology should expand human autonomy, not constrain it. AI systems aligned with Infosomatic principles serve as enablers of creative freedom and self-regulation, supporting a user’s ability to engage meaningfully with their environment.
This connection between cybernetics and Infosomatic Alignment is essential for ensuring that AI systems are responsive to human creativity and ethical growth. Rather than merely optimizing for efficiency, these systems are designed to amplify human potential and foster a more dynamic, adaptive interaction with the world.
Cultural Bias and Pluralism in AI
One of the key challenges facing AI today is the issue of cultural bias, where models reflect the dominant norms of the cultures they are trained on. A study on cultural prompting, which tested AI across over 100 countries, demonstrates how AI systems can be realigned to reflect diverse cultural contexts more accurately. However, this is just the beginning. Infosomatic Alignment extends this process by ensuring that AI systems are inherently adaptive to the cognitive and cultural environments they encounter.
This adaptability allows Infosomatic AI to function as an active participant in fostering cultural diversity and creative autonomy. By enabling users from different backgrounds to engage with technology in ways that are meaningful to them, Infosomatic Alignment ensures that AI enhances, rather than diminishes, cultural pluralism.
Perspective on AI Limitations
In a recent interview, mathematician Terence Tao discussed the limitations and potential of AI systems. Tao argues that while AI can handle routine tasks efficiently, it lacks the creative intuition that characterizes human intelligence. He emphasizes that AI can assist in industrial-scale mathematics, but it still requires human oversight for more nuanced and creative problem-solving.
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Tao’s perspective aligns closely with the principles of Infosomatic Alignment, which envisions AI as a complement to, rather than a replacement for, human creativity. In this model, AI systems handle routine processing tasks, freeing humans to focus on the creative and intuitive dimensions of their work. By integrating human creativity with the efficiency of AI, Infosomatic Alignment supports a balanced approach to technological and intellectual growth.
Sapiocracy and Ethical AI Design
The principles of Infosomatic Alignment are also deeply connected to the concept of Sapiocracy, a model of governance that prioritizes human potential and creative autonomy. In a Sapiocratic society, AI is seen not merely as a tool for enhancing productivity, but as a facilitator of self-regulation and ethical growth. Rather than being optimized solely for efficiency, AI systems are designed to support self-realization and cultural diversity.
As explored in works like AI-Thinking, Infosomatic Alignment is essential for ensuring that AI systems align with the ethical and creative needs of human society. By integrating AI into the fabric of human life in a way that respects plurality and cognitive diversity, Infosomatic Alignment provides a framework for building a more dynamic and inclusive future.
The Infosomatic Alignment framework represents a unique evolution of existing concepts, such as cybernetics, autopoiesis, and self-regulation, but it applies these principles in novel ways to AI and societal systems. While it draws from established theories (e.g., Maturana’s autopoiesis, Beer’s VSM, and Heinz von Foerster’s ethical imperative), it synthesizes them into a fresh approach that directly addresses the challenges of modern AI, human potential alignment, and self-regulation within complex, adaptive systems.
What sets it apart and makes it marketable is its practical applicability across multiple domains—healthcare, climate resilience, governance, and more—focusing on how AI can be proactively aligned with human self-regulation and ethical decision-making, rather than being just a tool for optimization or data processing. This shift toward human-centered, adaptive AI is timely, given the concerns over AI ethics, bias, and the erosion of human autonomy.
If framed correctly, Infosomatic Alignment offers a revolutionary practical toolkit for designing systems that extend beyond traditional AI models. By embedding self-regulation and real-time adaptation into system architectures, it opens up new possibilities for scalable, transformative solutions in industries grappling with AI's ethical and operational challenges. The appeal lies in its focus on expanding human autonomy, ethical self-regulation, and aligning AI with meaningful human goals.
In short, while it draws on known concepts, the synthesis and application of these ideas to AI and societal challenges are novel enough to market, especially in an era where organizations are seeking more holistic, ethical solutions. The value of Infosomatic Alignment is in its scalability and adaptability, offering both theoretical depth and practical relevance for real-world issues.
Real-Life Application: Infosomatic Alignment in Health Diagnostics
Consider the case of adaptive health diagnostics. In traditional systems, diagnostics are often reactive—based on existing symptoms or accumulated data, which leads to an overwhelming amount of information but doesn't inherently improve decision-making. By applying Infosomatic Alignment, the system instead operates like a self-regulating organism that continuously monitors relevant differences within the patient’s data.
For instance, wearable health technology can function by aligning with self-regulation principles. Rather than flagging every anomaly, it focuses on relevant differences that expand patient autonomy—such as subtle patterns in heart rate variability that predict a potential issue before it manifests into a critical symptom. The system aligns these inputs with the body’s self-regulation, offering real-time adjustments, predictive advice, and healthier choices based on adaptive insights, much like Beer’s Viable System Model within the body.
This process doesn't overwhelm the patient or physician with redundant data but instead offers actionable intelligencebased on what enhances autonomous, proactive healthcare. This enables early interventions that go beyond reactive medicine and empower individuals to make decisions that expand their health autonomy through self-regulated data inputs. The system continuously adjusts based on real-time physiological changes, fostering an expansive, autonomous decision loop between the patient, system, and healthcare provider.
This model can be extended across industries—from predictive maintenance in industrial systems to climate resilience strategies. It illustrates how Infosomatic Alignment transforms reactive systems into proactive, adaptive infrastructures, expanding autonomy and decision-making at every step.
Conclusion: The Future of Human-Centered AI
As AI continues to evolve, the need for Infosomatic Alignment becomes more pressing. Traditional models that prioritize data processing and efficiency risk undermining the diversity and richness of human experience. Infosomatic Alignment offers a solution by ensuring that AI systems are self-regulating, adaptive, and aligned with human cognition.
By integrating insights from cognitive neuroscience, cybernetics, and constructivist theory, Infosomatic Alignment paves the way for a future where AI enhances human creativity, cultural diversity, and self-realization. As we move into an increasingly AI-driven world, the principles of Infosomatic Alignment will be critical for creating a technology that serves not only to optimize tasks, but also to amplify human potential.
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Managing Director @ Yoush Consulting - PM and Staff Augmentation for IT
1 周AI?is a topic with few experts in the industry yet widely marketed as the next COOL thing. The public, as do people in the IT industry, deserves more education in this area. The article leaves me craving to explore deeper. Thank you!