Technological Approach to Mind Everywhere (TAM)
- Philosophy drives scientific discovery. Levin’s framework emphasizes understanding goal-directedness to recognize, build, and control unconventional agents.
- Anatomical control is an example of collective intelligence navigating “morphospace” (the space of possible anatomical forms).
- Bioelectrical networks are an ancient cognitive “glue,” predating brains, enabling individual cells to act collectively. This has implications for biomedicine and synthetic bioengineering.
Beyond Discrete Natural Kinds
- Evolution and development are gradual, continuous processes, blurring distinctions between “natural kinds” (e.g., human vs. animal, natural vs. artificial).
- We are part of both a natural continuum (evolutionary, developmental) and an engineering continuum (biological modification, technological hybridization).
- The framework considers a wide range of agents: familiar organisms, colonial organisms, engineered biological systems, AI, and potential exobiological life. All are analyzed by asking how an external observe would functionally interface with it, and see what best interaction (Hardware/Goal/Reward&punishment) there is to use.
The Spectrum of Persuadability
- Systems exist on a spectrum of how best to interact with them, from purely mechanical systems (only modifiable by hardware) to systems that can be reasoned with.
- It’s an *empirical* question where a system falls on this spectrum, not a philosophical one. Experimentation, not assumption, is key.
- All systems start life with less interaction capibility, but slowly build capacity until there is enough to make its own descisions and plans. Developmental biology offers *no special moment* of “true cognition”; it’s a gradual process.
- All intelligence is collective intelligence: composed of interacting parts (cells, components, etc.). Understanding how these parts scale up to form larger intelligences is critical.
Multi-Scale Competency and Problem Solving
- Biological systems have a multi-scale competency architecture: each level (cells, tissues, organs) has its own problem-solving capabilities in specific “spaces”.
- Examples of these problem spaces: anatomical space, physiological space, gene expression space. We are good at recognizing intelligence in 3D space, but less so in others.
- Planaria can adapt to barium exposure, quickly and with no selection, selecting specificly and quickly (within hours) which genes. This exemplifies solving novel physiological problems by navigating gene expression space. Gene regulatory networks (GRNs) have diverse learning capabilities, including associative conditioning.
- Evolution repurposes problem-solving strategies across different spaces.
Bioelectricity and Morphogenesis
- Turing’s interest in morphogenesis was likely linked to his interest in unconventional intelligence. Body and mind building are related problems.
- The genome specifies the *micro-level hardware* (proteins), not the large-scale anatomical structure. Cells *collectively* decide what to build and when to stop, demonstrating morphogenesis as collective intelligence.
- The goal is an “anatomical compiler”: translate a desired anatomical form into stimuli that guide cells, revolutionizing medicine. This is a *communication* problem, not a micromanagement problem.
- Cells and tissues exhibit intelligence (defined as “reaching the same goal by different means”). Development and regeneration demonstrate robust error minimization and adaptability. Kidney tubule formation shows different mechanisms to achieve the same anatomical outcome.
- The frog face rearrangement demonstrates a goal, not predetermined organ-by-organ programming.. Perturbed tadpole faces (“Picasso tadpoles”) can still form normal frogs. An error minimization, not instruction.
- Bioelectric patterns, like those in the brain, store “set points” (anatomical goals). They aren’t magnets, fields, or anything alike. Instead, cells use and hack other cells, leveraging the native interfaces that each other use and provide to communicate this electri network, creating pattern completion that we are not smart enough, nor need, to understand the internal working for us to communicate at large.
- Tools from neuroscience can *read and write* these bioelectric patterns (like “incepting” false memories). Altering bioelectric patterns can induce ectopic organs (eyes, fins, hearts) and influence regenerative processes.
- Planarian regeneration reveals bioelectric gradients determining head number. These patterns are rewritable and act as a “counterfactual memory,” dictating future regenerative behavior even when the body is normal.
- We can computationally model the connections between electrical states and the underlying molecular mechanisms, drawing on ideas from connectionist neuroscience.
- The latent morphospace of possibilities for even a given genome is vast, highlighting the plasticity and flexibility of biological systems. The plan is a future medicine more like sematic psychiatry (than only chemistry, and fixing a gene.
Cognitive Light Cones, Selves, and Ethics
- The “cognitive light cone” is a central invariant: the spatial-temporal size of the largest goal a system can pursue. Different agents have different sized light cones.
- Defining a “self” involves considering the boundary of goals the system pursues. We are all collectives (cells within organisms).
- Early embryogenesis reveals dynamic self-construction. The number of “selves” in a blastoderm is not predetermined; it’s an outcome of cell communication. The same logic applies to nervous system (split brains show there is not clealy just 1 self inside).
- Cancer can be understood as a failure of the scaling-up of cellular goals, cells are reverting to a smaller and smaller individual cognitive lightcone, thus are cancerous as they dont abide to collective goals. Bioelectric interventions can influence this process, even when genetic abnormalities remain.
- Endless forms are possible, both naturally and through bioengineering, due to the interoperability and plasticity of life. It is important that novel forms do not fit onto the evolution tree/scales and that all categorization fails here (desiged, natural, etc) This necessitates new ethical frameworks for interacting with unconventional minds.