Where Minds Come From: The Scaling of Collective Intelligence, AI, and You | Michael Levin Lecture Bioelectricity Podcast Notes

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Introduction: Rethinking Discrete Categories

  • Traditional categorizations of living things (discrete species, clear separation between humans and other beings) are inadequate for understanding intelligence and future beings.
  • We need a framework for understanding, creating, and ethically relating to *diverse* intelligences, regardless of composition (what they’re made of) or origin (evolved, engineered, or a combination).
  • Focus should shift from categorizing natural and traditional “kinds” (types) to focusing on scales and intelligence.

The Continuum of Being and Intelligence

  • Evolution and developmental biology show a *continuum* of forms, not sharp distinctions between humans and other life stages (embryos, ancestors, or future augmented humans).
  • Horizontal Modification of beings are possible and very likely, which challenge these natural distinctions.
  • Humans will be modified (technologically, biologically) for health and augmentation. Distinguishing between “human” and “machine” becomes difficult.
  • We need a framework (like Rosenblueth & Bigelow’s scale) to relate to various intelligences: primates, birds, octopuses, colonial organisms, engineered life forms, AI (robotic or software), and even aliens. The scale is: Passive Matter, Computational Matter, Agent Materials and Metacoginition.
  • The goal of such framework is to create interaction (including creating new discoveires, and capabilites withing biomedicine and more), along with a much more sound etheical footing.
  • We all start as cells (“just physics”), eventually turning into things described by pscyology and even psychoanalysis.
  • We need a “story of scaling” to understand how systems described by physics also become describable by psychology.

Agential Material and Collective Intelligence

  • Unlike Legos, biological systems are made of “agential material” – cells with their own agendas and problem-solving capacities (e.g., *Lacremaria* single-cell organism).
  • All living systems, and even the “single” unified person is a *collective intelligence*.
  • We, people, *are all made of* parts. The body, especially even the pineal gland (in rene descarte times considered the singular organ), are collection of things with multiple things inside it.
  • Even our *selves* are “collective intelligences” composed of parts. The challenge is explaining how these parts create a unified sense of self.
  • Alan Turing saw a connection between the origin of bodies (morphogenesis) and the origin of minds.

The “Self” is Dynamic, Not Hardcoded

  • Counting “embryos” isn’t counting a fixed number of beings. It’s counting the alignment of cells committed to a shared anatomical plan.
  • Experiments with duck embryos show that the number of “selves” can change dynamically based on physiological processes (e.g., creating conjoined twins by separating groups of cells).
  • Selves construct themselves (including defining their own boundires from the envrionment); a “self” isn’t something predefined genetically.
  • Split-brain patients and dissociative identity disorders also show that the number of “selves” in a brain isn’t fixed.
  • Cognitive Glue (e.g. nerovus system): Creates a higher level entity, with cognitive abilities far exceding each single part.

Radical Plasticity: Caterpillars and Planaria

  • Caterpillar to Butterfly: Caterpillar (simple, 2D movement) is reorgnaized drastically to turn to Butterflies (flies, has hard parts, eat different things). Caterpillars, if trained, have memory. Butterfly memory persist, and what is useful for the caterpillar is translated into actions (of flight, eatings etc) for the butterfly, demonstrating profound adaptation beyond mere memory.
  • Planaria Memory and Regeneration: Planaria remember training even after their heads (including brains) are removed and regrown, implying memory storage outside the brain and transfer to a new brain.

Multiscale Competency Architecture

  • Biological systems have problem-solving abilities at multiple scales (molecules, cells, tissues, organs), not just in three-dimensional space but also in gene expression spaces, physiological spaces, and “anatomical morphospace.”

Beyond Reliability: Salamanders and Picasso Frogs

  • Salamanders (high ability for regenration) with varying numbers of chromosomes and cell sizes *still* build the correct structures, demonstrating robust adaptation to unexpected variations, even in the number of cells!
  • Shows evolution produces problemsolving capabalities rather than rigid reliability.
  • Evolution makes a “error minimization” and is not simply fixed instructions: Picasso frogs (organs scrambled) still develop into normal frogs, indicating a system for *error minimization,* not just following hardwired instructions. Organs do unusual pathways to correct itself.

Beyond Genetics: Morphogenetic Plasticity

  • Example 1: Flies run Ant-Morphogenetic programs on wings: it protects from predator. This illustrates morphogenetic (change in shape/structure) potential.
  • Example 2: Wasp on Oak-leaves. The typical oak and acorn, are well understood (shape and everything). But Wasp makes signals, causing structures on oaks very different to the ones typically observed.
  • Genetics defines the *hardware,* but cells can achieve diverse outcomes. A wasp can induce an oak leaf to build a *different* structure (a gall) without changing the leaf’s DNA.

Communicating with Morphogenetic Intelligence

  • Morphogenesis is the behavior of a collective intelligence in anatomical space. We need to learn how to *communicate* with this intelligence.
  • Example: The wasp above “communicates” (through evolution) to tell cells of a different kind to construct different.
  • Neurons/Nervous system uses computation and electricy. Evolution had already used and discovered the use of an electrial network to intergrate many cells both space and time way before it developed muscles.
  • Voltage-Sensitive Fluorescent Dye Imaging: A technology that lets us measure voltage. This allows viewing “bioelectric pattern” showing the frog forming their faces, and learning to understand/decode the pattern/process.
  • Electrical Pattern (“Electric Face”). Like brain scanning, shows activity but in organs: showing you can tell where a organ like a mouth/eyes is going to be way in advance.
  • Pathalogical patterns exist and could signal issue. For example: cancers have abnormal patterns and disconnect from surrounding envrionment/cells and causing cells to “forget” larger structure.
  • This approach offers way to do cancer therpatueis; by trying to change cell memory/state instead of “killing cells” or toxic therapies, and “reconnecting” the cells.
  • Examples: Cells disconnected from environment will loose big structure, the memory can be restored through reinflucing the connection back, even with genetical defects still present.

Reprogramming the Body Plan

  • The group has created ectopic eyes (induced on frog’s body): telling (through electral signal/patterns) cells to become another. Almost any region could be reprogramed into different organs, like eye. Cells cooperate with neighbours when only few cells are injected.
  • Proving that “eye master genes” theory only partially accurate; once you know how to “communicate” in right language/patterns/signals, any cell has way more potential.
  • Rewriting Pattern Memory (Planarian). Can change worm head: from one-head into two heads *forever*, they always reproduce/regenerate as two-heads after this. By Modifying Biopattern. Showing: DNA don’t dictate 100% how bodies change, the same genome (or DNA, no change in genetics here!) can still build very different things depending on how/where and by what the signal is/what the patterns are! The reprogramed cell can exist beyond generations/cuttings.

Origin of Goals and Xenobots

  • Questions raised about Goals (Where these morphoentic and goal pattern exist outside DNA? The option and limit, including the example of re-routing worms’s into head of different species with wildly different genetics.): they aren’t completely set, but re-programmable, a “rewritable”.
  • Just like reprograming computer instead of using “soldering iron”, the biology could and does re-program to fix and correct for goals.
  • Xenobots (created from frog skin cells): These cells, when separated from the embryo, *spontaneously* self-assemble into new organisms (“xenobots”) with novel behaviors, including *kinematic self-replication* (building copies of themselves from loose cells).
  • Xenobots have Cilia (hairs for frog mucas transport), in Xenobot use it to swim.
  • Kinematic Self-replication (discovered by accident!) – creating generation of copies of Xebot with materials/parts on envrionment.
  • Showcasing it is difficult to attribute Xenobot shape/behavours, as they don’t have any selective “evolution”.
  • Evoluation create problemsolvers, rather than fixated behaviors/forms, that is, under condition changes/challenges.
  • Anthrobots (from adult human tracheal cells): Similar to xenobots, these human cells also self-assemble into novel structures (“anthrobots”) with surprising capabilities, like repairing neural wounds.

The Spectrum of Persuadability and Ethics

  • It’s wrong to look at “philosophically” into beings and deciding which one is an intelligence. There is experimental way of looking at this (“spectrum of persuadability”, from tools/hardwiring -> behavorial science and trainings -> Rich relationship) and intelligence.
  • “Persuadability”: The kind of tools we use to communicate with things, scales. Cells are capable of things than what people thought, and it is easy to miss intelligence, making us “a lot left on table”.
  • We are on the era of “diversity intelligence”. Where today’s Large Language Models (GPT-4) don’t matter, What Matters Is that: We need to do experienments, there are non-human minds, even some of the simplest thing has incredible complexity.
  • Ethics: We must avoid denying moral worth to beings because they don’t look like us. The space of possible bodies and minds is expanding rapidly (cyborgs, chimeras, etc.), and we need better ethical frameworks. It’s about learning to relate to *different* beings. There will exist cyborgs and all types, including biological materials/evolved ones combined, making us “Synbiosis”, or beings living together and requiring a “ethical Framework”. It won’t just about whether things are “metal/human” that is traditional, or looking to the tree-of-life that decides on which being “count” – many, multiple things count, many will change. We are required to make moral frameworks and ethics in way never before required.
  • Humanity on the Long Term: We are not the “best, and most developed”. Humans, what does this actually mean (to want Roomba, companion?). What it wants is *NOT* DNA, what does that mean (relationship etc) What matters? (That are Worth-Thinking!)

引言:重新思考离散类别

  • 传统的生物分类(离散物种、人类与其他生物的明确区分)不足以理解智能和未来的存在。
  • 我们需要一个框架来理解、创造和道德地对待 *多样化的* 智能,无论其构成(由什么构成)或起源(进化、工程或组合)如何。
  • 重点应该从归类自然和传统的“种类”(类型)转向关注尺度和智能。

存在与智能的连续体

  • 进化和发育生物学显示了形式的 *连续体*,而不是人类与其他生命阶段(胚胎、祖先或未来增强型人类)之间的明显区别。
  • 生物体的水平修改是可能的,而且很可能发生,这挑战了这些自然的区别。
  • 人类将为了健康和增强而被改造(技术上、生物学上)。区分“人类”和“机器”变得困难。
  • 我们需要一个框架(如罗森布鲁斯和比奇洛的尺度)来关联各种智能:灵长类动物、鸟类、章鱼、群居生物、工程生命形式、人工智能(机器人或软件),甚至外星人。这个尺度是:被动物质、计算物质、自主材料和元认知。
  • 这种框架的目标是创造互动(包括创造新的发现,以及生物医学等领域的能力),以及更健全的道德基础。
  • 我们都从细胞开始(“只是物理”),最终变成用心理学甚至精神分析来描述的东西。
  • 我们需要一个“尺度化故事”来理解物理学描述的系统如何也能被心理学描述。

自主材料与集体智能

  • 与乐高积木不同,生物系统是由“自主材料”构成的——细胞具有自己的议程和解决问题的能力(例如,*Lacremaria* 单细胞生物)。
  • 所有生命系统,甚至“单一”的统一的人,都是 *集体智能*。
  • 我们,人类,*都是由* 部分组成的。身体,甚至松果体(在勒内·笛卡尔时代被认为是单一器官),都是由多个内部事物组成的集合。
  • 甚至我们的 *自我* 也是由部分组成的“集体智能”。挑战在于解释这些部分如何创造统一的自我感。
  • 艾伦·图灵看到了身体起源(形态发生)和心灵起源之间的联系。

“自我”是动态的,而不是硬编码的

  • 计算“胚胎”数量并不是计算固定数量的生物。它是计算致力于共同解剖计划的细胞的排列。
  • 鸭胚胎实验表明,“自我”的数量可以根据生理过程动态变化(例如,通过分离细胞群来创造连体双胞胎)。
  • 自我构建自己(包括定义自己与环境的边界);“自我”不是基因预先定义的东西。
  • 裂脑患者和分离性身份障碍也表明,大脑中“自我”的数量不是固定的。
  • 认知胶水(例如神经系统):创建一个更高层次的实体,其认知能力远远超过每个单独的部分。

激进的可塑性:毛毛虫和涡虫

  • 毛毛虫变蝴蝶:毛毛虫(简单的二维运动)被彻底重组以变成蝴蝶(飞行,有坚硬的部分,吃不同的东西)。如果经过训练,毛毛虫是有记忆的。蝴蝶的记忆持续存在,对毛毛虫有用的东西被转化为蝴蝶的行动(飞行、进食等),证明了超越单纯记忆的深刻适应。
  • 涡虫的记忆和再生:即使在头部(包括大脑)被移除并重新生长后,涡虫也能记住训练,这意味着记忆存储在大脑之外并转移到新的大脑。

多尺度能力架构

  • 生物系统在多个尺度(分子、细胞、组织、器官)上具有解决问题的能力,不仅在三维空间中,而且在基因表达空间、生理空间和“解剖形态空间”中也具有解决问题的能力。

超越可靠性:蝾螈和毕加索蛙

  • 具有不同数量染色体和细胞大小的蝾螈(具有很强的再生能力)*仍然* 构建正确的结构,证明了对意外变化的强大适应性,甚至在细胞数量上也是如此!
  • 表明进化产生了解决问题的能力,而不是僵化的可靠性。
  • 进化实现了“错误最小化”,而不仅仅是固定的指令:毕加索蛙(器官被打乱)仍然发育成正常的青蛙,表明了一个 *错误最小化* 系统,而不仅仅是遵循硬编码的指令。器官会采取不寻常的途径来纠正自己。

超越遗传学:形态发生可塑性

  • 例子1:果蝇在翅膀上运行蚂蚁形态发生程序:它保护免受捕食者的侵害。这说明了形态发生(形状/结构的变化)的潜力。
  • 例子2:橡树叶上的黄蜂。典型的橡树和橡子是很好理解的(形状和其他一切)。但是黄蜂发出信号,导致橡树上的结构与通常观察到的结构非常不同。
  • 遗传学定义了 *硬件*,但细胞可以实现不同的结果。黄蜂可以诱导橡树叶在不改变叶子DNA的情况下构建 *不同的* 结构(虫瘿)。

与形态发生智能沟通

  • 形态发生是解剖空间中集体智能的行为。我们需要学习如何与这种智能 *沟通*。
  • 例子:上面的黄蜂“沟通”(通过进化)告诉不同种类的细胞构建不同的东西。
  • 神经元/神经系统使用计算和电力。进化在发展肌肉之前很久就已经使用和发现了使用电网络来整合许多细胞的空间和时间。
  • 电压敏感荧光染料成像:一种让我们测量电压的技术。这允许观察“生物电模式”,显示青蛙形成它们的面部,并学习理解/解码模式/过程。
  • 电模式(“电脸”):就像大脑扫描一样,显示器官中的活动:显示你可以提前知道像嘴巴/眼睛这样的器官将在哪里。
  • 存在病理模式,可能预示着问题。例如:癌症具有异常模式,并与周围环境/细胞断开连接,导致细胞“忘记”更大的结构。
  • 这种方法提供了进行癌症治疗的方法;通过尝试改变细胞记忆/状态,而不是“杀死细胞”或毒性疗法,并“重新连接”细胞。
  • 例子:与环境断开连接的细胞将失去大结构,即使仍然存在遗传缺陷,也可以通过重新影响连接来恢复记忆。

重新编程身体计划

  • 该小组已经创造了异位眼睛(诱导在青蛙的身体上):通过电信号/模式告诉细胞变成另一种细胞。几乎任何区域都可以重新编程为不同的器官,如眼睛。当只注射少量细胞时,细胞会与邻居合作。
  • 证明“眼睛主基因”理论只是部分准确的;一旦你知道如何用正确的语言/模式/信号“沟通”,任何细胞都有更大的潜力。
  • 重写模式记忆(涡虫):可以改变蠕虫的头部:从单头变成 *永远* 双头,它们在此之后总是繁殖/再生为双头。通过修改生物模式。表明:DNA并不能100%决定身体如何变化,相同的基因组(或DNA,这里没有遗传变化!)仍然可以根据信号的方式/位置和信号是什么/模式是什么来构建非常不同的东西!重新编程的细胞可以存在于世代/切割之外。

目标和异种机器人的起源

  • 提出了关于目标的问题(这些形态发生和目标模式存在于DNA之外吗?选项和限制,包括将蠕虫重新路由到具有完全不同遗传学的不同物种头部的例子):它们不是完全固定的,而是可重新编程的,一种“可重写的”。
  • 就像重新编程计算机而不是使用“烙铁”一样,生物学可以并且确实重新编程以修复和纠正目标。
  • 异种机器人(由青蛙皮肤细胞制成):这些细胞,当与胚胎分离时,会 *自发地* 自组装成新的生物体(“异种机器人”),具有新颖的行为,包括 *运动学自我复制*(从松散的细胞中构建自己的副本)。
  • 异种机器人有纤毛(用于青蛙黏液运输的毛发),在异种机器人中用它来游泳。
  • 运动学自我复制(偶然发现!)- 使用环境中的材料/部件创建一代又一代的异种机器人副本。
  • 展示了很难归因于异种机器人的形状/行为,因为它们没有任何选择性的“进化”。
  • 进化创造了问题解决者,而不是固定的行为/形式,也就是说,在条件变化/挑战下。
  • 人类机器人(来自成人人类气管细胞):类似于异种机器人,这些人类细胞也会自组装成具有惊人能力的新结构(“人类机器人”),例如修复神经伤口。

可说服性谱系和伦理

  • 从“哲学上”看待生物并决定哪个是智能是错误的。有一种实验性的方法来看待这个问题(“可说服性谱系”,从工具/硬连线 -> 行为科学和训练 -> 丰富的关系)和智能。
  • “可说服性”:我们用来与事物沟通的工具类型,尺度。 细胞能够做人们认为的事情,而且很容易错过智能,这使得我们“在桌子上留下了很多东西”。
  • 我们正处于“多样性智能”时代。在当今的大型语言模型(GPT-4)并不重要的情况下, 重要的是:我们需要做实验,存在非人类的思想,即使是一些最简单的东西也具有令人难以置信的复杂性。
  • 伦理:我们必须避免否认生物的道德价值,因为它们看起来不像我们。可能的身体和思想的空间正在迅速扩大(半机械人、嵌合体等),我们需要更好的伦理框架。这是关于学习与 *不同的* 生物建立联系。 将存在半机械人和所有类型,包括生物材料/进化材料的组合,使我们成为“共生体”,或者共同生活并需要“伦理框架”的生物。 这不仅仅是关于事物是传统的“金属/人类”,还是看生命之树来决定哪些生物“算数”——许多,多个事物算数,许多事物将改变。我们需要以前所未有的方式制定道德框架和伦理。
  • 从长远来看人类:我们不是“最好的,最发达的”。人类,这实际上是什么意思(想要扫地机器人,同伴?)。 它想要的 *不是* DNA,那是什么意思(关系等) 什么才是重要的? (这些都是值得思考的!)