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.

心智无处不在的技术路径 (TAM)

• 哲学驱动科学发现。莱文的框架强调理解目标导向性，以识别、构建和控制非常规智能体。
• 解剖控制是集体智能在“形态空间”（可能的解剖形式空间）中导航的一个例子。
• 生物电网络是一种古老的认知“胶水”，早于大脑，使单个细胞能够集体行动。这对生物医学和合成生物工程具有重要意义。

超越离散的自然类别

• 进化和发育是渐进的、连续的过程，模糊了“自然类别”之间的区别（例如，人类与动物，自然与人工）。
• 我们既是自然连续体（进化、发育）的一部分，也是工程连续体（生物改造、技术杂交）的一部分。
• 该框架考虑了广泛的智能体：熟悉的生物体、群居生物体、工程生物系统、人工智能和潜在的外星生物。所有这些都通过询问外部观察者如何与其进行功能交互来分析，并查看最佳交互方式（硬件/目标/奖惩）。

可说服性光谱

• 系统存在于一个关于如何与它们进行最佳交互的光谱上，从纯粹的机械系统（只能通过硬件修改）到可以与之进行推理的系统。
• 一个系统落在这个光谱的哪个位置是一个*经验*问题，而不是一个哲学问题。 实验，而不是假设，才是关键。
• 所有系统在生命开始时都具有较少的交互能力，但会缓慢地建立能力，直到有足够的能力做出自己的决策和计划。发育生物学*没有提供*“真正认知”的特殊时刻；这是一个渐进的过程。
• 所有智能都是集体智能：由相互作用的部分（细胞、组件等）组成。理解这些部分如何扩展形成更大的智能至关重要。

多尺度能力和问题解决

• 生物系统具有多尺度能力架构：每个层次（细胞、组织、器官）在特定“空间”中都有自己的问题解决能力。
• 这些问题空间的例子：解剖空间、生理空间、基因表达空间。我们善于识别三维空间中的智能，但在其他空间中则不那么擅长。
• 涡虫可以适应钡暴露，快速且无需选择，特定且快速（数小时内）选择哪些基因。这体现了通过导航基因表达空间解决新的生理问题。基因调控网络 (GRN) 具有多种学习能力，包括联想条件反射。
• 进化在不同空间中重新利用问题解决策略。

生物电与形态发生

• 图灵对形态发生的兴趣可能与他对非常规智能的兴趣有关。 身体和心智的构建是相关的问题。
• 基因组指定*微观层面的硬件*（蛋白质），而不是大规模的解剖结构。 细胞*集体*决定构建什么以及何时停止，将形态发生展示为集体智能。
• 目标是“解剖编译器”：将所需的解剖形式转换为指导细胞的刺激，彻底改变医学。这是一个*沟通*问题，而不是微观管理问题。
• 细胞和组织表现出智能（定义为“通过不同方式达到相同目标”）。发育和再生表现出强大的误差最小化和适应性。肾小管形成显示了实现相同解剖结果的不同机制。
• 青蛙面部重排展示了一个目标，而不是预先确定的逐个器官的编程。扰动的蝌蚪面部（“毕加索蝌蚪”）仍然可以形成正常的青蛙。一个误差最小化，而不是指令。
• 生物电模式，就像大脑中的那些，存储“设定点”（解剖目标）。它们不是磁铁、场或任何类似的东西。相反，细胞使用和操纵其他细胞，利用彼此使用和提供的本地接口来通信这个电网络，创建模式补全，我们不够聪明，也不需要，来理解内部工作原理以便我们进行广泛的通信。
• 来自神经科学的工具可以*读取和写入*这些生物电模式（就像“植入”虚假记忆）。改变生物电模式可以诱导异位器官（眼睛、鳍、心脏）并影响再生过程。
• 涡虫再生揭示了决定头部数量的生物电梯度。这些模式是可重写的，并充当“反事实记忆”，指示未来的再生行为，即使身体是正常的。
• 我们可以对电状态和潜在分子机制之间的连接进行计算建模，借鉴连接主义神经科学的思想。
• 即使对于给定的基因组，潜在的形态空间也是巨大的，突出了生物系统的可塑性和灵活性。 该计划是一种未来的医学，更像躯体精神病学（而不是仅仅化学和修复基因）。

认知光锥、自我与伦理

• “认知光锥”是一个核心不变量：系统可以追求的最大目标的时空大小。不同的智能体具有不同大小的光锥。
• 定义“自我”涉及考虑系统追求的目标边界。我们都是集体（生物体内的细胞）。
• 早期胚胎发生揭示了动态的自我构建。 囊胚中的“自我”数量不是预先确定的；它是细胞沟通的结果。 同样的逻辑也适用于神经系统（裂脑表明内部不仅仅有1个自我）。
• 癌症可以理解为细胞目标扩大的失败，细胞正在恢复到越来越小的个体认知光锥，因此是癌性的，因为它们不遵守集体目标。即使基因异常仍然存在，生物电干预也可以影响这一过程。
• 由于生命的互操作性和可塑性，无限的形式是可能的，无论是自然的还是通过生物工程。重要的是，新形式不适合进化树/尺度，并且所有分类都在这里失败（设计的、自然的等） 这就需要新的伦理框架来与非常规心智互动。