The goal of Subconscious is to generate self-organizing ideas. Organizing ideas through sheer force of will is difficult, and I am lazy. Luckily there may be another way. Given the right mechanisms, the right conditions, and enough energy and time, a system can self-organize.
Subconscious is winding down
Subconscious started with an idea: to amplify intelligence using a worldwide decentralized knowledge graph. In 2022, we raised a seed and started building. Today we’re sharing difficult news. Subconscious will be winding down active operations. I’m proud of what our team built on a technical level—
Self-organizing systems: what, how, and why?
I present a personal account of self-organizing systems, framing relevant questions to better understand self-organization, information, complexity, and emergence. With this aim, I start with a notion and examples of self-organizing systems (what?), continue with their properties and related concepts (how?), and close with applications (why?) in physics, chemistry, biology, collective behavior, ecology, communication networks, robotics, artificial intelligence, linguistics, social science, urbanism, philosophy, and engineering.
Self-Organization in Biological Systems
The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns—phenomena that have fascinated naturalists for centuries—a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world. Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: To what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems? Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology—a field of study at the forefront of life sciences research.
Worst Possible Idea
There are many brainstorming methods (including bodystorming, p.30, brainwriting 6-3-5, p.32 and group passing, p.82) that are each useful in different circumstances. However, sometimes it can be difficult for people in a group setting to generate ideas. This may be because people are too stuck in current ways of thinking, or they might be concerned about being judged by others for the ideas they propose. Giving people the permission to come up with their worst possible ideas creates a playful, safe environment and helps to get a brainstorming session off to a good start. Ideas might build on each other during the process, and it is indeed possible to generate an idea or way of thinking about the problem that can be fed back into the design process. Managers that have used this method with their teams report that it outperforms by far any other brainstorming method (Dorf, 2017), largely because of its ability to energise a room and enable lateral thinking.
Co-Creation: Systems Thinking Beyond the Machine
Complexity thinking is all the rage — in the arts and sciences. Yet, there are two different strands of thinking about complexity, which are often confounded. The first comes from cybernetics, focussing on control in complex situations. The second is ecological, aiming at sustainable participation in a reality beyond control. Their difference rests on a fundamental distinction: is complexity rooted in feedback regulation or collective co-creation? While feedback remains mechanistic, co-creation generates new spaces of possibilities. We need it to understand life and its evolution. And it empowers us to rewrite our future, to escape our mechanistic cage without abandoning scientific rigor. In this paper, we illustrate how we implement these powerful yet abstract principles through our artistic and philosophical practice.
Cultivating a state of mind where new ideas are born
Solitary work, creativity and larval ideas
Our Minds Are Weirder than You Think
The Care of the Self within a Biopolitical Paradigm: Integrating Cognitive Psychology to resist Subjectification
Contemporary theories of resistance to biopolitical subjectification often reify unfreedom by lacking a plausible model of agency. This thesis resolves this by establishing an ontological foundation for the agent as fundamentally autopoietic and semiotic, drawing on contemporary cognitive science. It then proposes a new foundation for resistance by synthesizing Michel Foucault’s later work on the care of the self with the 4P/5E model of embodied cognition. I show how this interdisciplinary approach establishes Foucault’s ethical techniques as a systematic ecology of practices for cultivating a free, self-determining agent and by reframing resistance as a practical, embodied ethics of self-formation, it inherently fosters two vital skills: the gain of self-knowledge and self-mastery.
Functional Synchronization: The Emergence of Coordinated Activity in Human Systems
The topical landscape of psychology is highly compartmentalized, with distinct phenomena explained and investigated with recourse to theories and methods that have little in common. Our aim in this article is to identify a basic set of principles ...
The Self-Evidencing Agent: Mind, Existence, and Predictive Processing
How the concept of self-evidencing offers a philosophical principle for understanding mind and behavior, consciousness, value, wisdom, and meaning.What is
Thinking through other minds: A variational approach to cognition and culture
The processes underwriting the acquisition of culture remain unclear. How are shared habits, norms, and expectations learned and maintained with precision and reliability across large-scale sociocultural ensembles? Is there a unifying account of the mechanisms involved in the acquisition of culture? Notions such as “shared expectations,” the “selective patterning of attention and behaviour,” “cultural evolution,” “cultural inheritance,” and “implicit learning” are the main candidates to underpin a unifying account of cognition and the acquisition of culture; however, their interactions require greater specification and clarification. In this article, we integrate these candidates using the variational (free-energy) approach to human cognition and culture in theoretical neuroscience. We describe the construction by humans of social niches that afford epistemic resources called cultural affordances. We argue that human agents learn the shared habits, norms, and expectations of their culture through immersive participation in patterned cultural practices that selectively pattern attention and behaviour. We call this process “thinking through other minds” (TTOM) – in effect, the process of inferring other agents’ expectations about the world and how to behave in social context. We argue that for humans, information from and about other people's expectations constitutes the primary domain of statistical regularities that humans leverage to predict and organize behaviour. The integrative model we offer has implications that can advance theories of cognition, enculturation, adaptation, and psychopathology. Crucially, this formal (variational) treatment seeks to resolve key debates in current cognitive science, such as the distinction between internalist and externalist accounts of theory of mind abilities and the more fundamental distinction between dynamical and representational accounts of enactivism.
Layers of Memory, Layers of Compression
AI superpower = strategic amnesia. Letta caches memory like a CPU, Anthropic spreads it across agent swarms, Cognition warns of chaos. Curious how forgetting makes machines smarter? Dive in.
Software in the natural world: A computational approach to hierarchical emergence
Understanding the functional architecture of complex systems is crucial to illuminate their inner workings and enable effective methods for their prediction and control. Recent advances have introduced tools to characterise emergent macroscopic levels; however, while these approaches are successful in identifying when emergence takes place, they are limited in the extent they can determine how it does. Here we address this limitation by developing a computational approach to emergence, which characterises macroscopic processes in terms of their computational capabilities. Concretely, we articulate a view on emergence based on how software works, which is rooted on a mathematical formalism that articulates how macroscopic processes can express self-contained informational, interventional, and computational properties. This framework establishes a hierarchy of nested self-contained processes that determines what computations take place at what level, which in turn delineates the functional architecture of a complex system. This approach is illustrated on paradigmatic models from the statistical physics and computational neuroscience literature, which are shown to exhibit macroscopic processes that are akin to software in human-engineered systems. Overall, this framework enables a deeper understanding of the multi-level structure of complex systems, revealing specific ways in which they can be efficiently simulated, predicted, and controlled.
Large language memories: Psychosis and antisocial media
Using the fields of memory studies and digital humanities, this article argues that there has been a shift from more collective and social memory to more personalised and individual memory. This shift, it is argued here, can be conceptualised through the psychoanalytic concept of ‘psychosis’. While the causes of the changes in our patterns of memory have been located in capitalist and neoliberal principles, the effects of the changes in our memory habits might be found in psychosis. From falling in love with machinic AI replicas to indulging in conspiracy theories to acting as if we are social media influencers or backing ourselves to win out in impossible job markets, we are inclined towards personal fantasy, often at the expense of participating in social life. But why do we do this? Why is it easier to believe a farfetched conspiracy theory or wild personal dream than it is to participate socially and collectively in the world we live in? Part of the reason, at least, is found in our increasing habitual reliance on new and emergent technologies. Often presented to us as a brand-new form of Artificial Intelligence, these generative tools are the latest update to a longer pattern in our digital world: the trend of developing ‘relationships’ with algorithms that, to larger and smaller degrees, we come to rely on for habits of cognition and recognition. By affecting our patterns of memory, these technologies produce a kind of isolation that lends itself to individual and fantastical – rather than shared and realist – thinking.
