Introduction: Children as “AI”

• Levin starts with a description that sounds like advanced AI, but he’s actually referring to human children, highlighting the inherent unpredictability and replacement that come with creating *any* new intelligence. This underscores that anxieties about AI replacing us are not new; they are ancient, existential concerns.
• Existing systems are created, given autonomy, released, and some, whether good or bad are empowered to perform those behaviors in the future, a license is required to fish but not for parenting.
• All forms of existing, adaptable life eventually cease.

Synthetic vs. Natural: A False Dichotomy

• People tend to categorize synthetic beings (like AI) as fundamentally different, but the real questions about creating high-capability beings, releasing them into the world, and having limited control are the *same* for both natural (children) and synthetic entities.
• People may have made judgements and statements without actually doing research first.

Adaptation, Persistence, and the Future

• A species that doesn’t change/adapt will die out. A species that does change is also, technically, “gone,” replaced by its adapted form. This paradox applies to all evolving systems, including humanity.
• The key is not “persistence as a fixed object” but “persistence as a process” (like process philosophy). The interesting question is not *if* we change, but *how* we want to change, individually and as a species.
• Humans in 100-200 years might not accept the limitations of the current human condition (e.g., lower back pain, diseases, birth defects) as inevitable; and future might consider those who refused to adapt unfathomable. Freedom of embodiment and deliberate change will likely become norms.
• It is not necessarily intelligence as brains, which evolve in nature, but different things altogether that should also fall under the terminology.

Diverse Intelligence and Overcoming Categorical Distinctions

• The field of “Diverse Intelligence” is growing, and challenges traditional, narrow definitions of intelligence and mind.
• Diverse intelligence seeks commonalities across *all possible* intelligent agents, not just those that are biological or brain-based. This includes considering radically different substrates, sizes, and “spaces” where intelligence can operate (not just 3D space).
• Confabulation (creating plausible explanations without complete information) is a feature of intelligence, not a bug. It’s essential for compression of experience, learning, and creativity, but it is present in biological intelligences as well as in certain simple mechanical processes as well, not exclusive to machines and software.
• The interviewer refers to previous chat about bioelectrical intelligence which led into a discussion about diverse intelligence, the rapidly-growing field.
• The question of where to look for mind and agency should remain at large for all of existence.
• People tend to assume a categorical distinction between a physical, cognitive system and the thoughts being carried and transferred between those physical entities, which isn’t necesarrily valid; both could exist on a fluid spectrum, and physical objects we percieve to be simplictic might turn out not to be so, due to our current perspectives of the subject matter being in their infancy.

Ethical Implications and “Synthbiosis”

• The ethical considerations of creating/interacting with diverse intelligences (including augmented humans) are significant. Categorical thinking (“us” vs. “them,” natural vs. artificial) is dangerous. The focus should be on matching “cognitive light cones” and sharing existential concerns.
• “Synthbiosis” (a term coined by chat gbt at Levin’s request): A positive, creative collaboration between biology and synthetic entities.
• We can learn things that we would not discover alone from any community.

Machine vs. Human: A Misguided Question

• The question “are we machines?” is ill-posed. “Machine” is a *lens* or interaction protocol, not an essential property. Different lenses reveal different aspects. We shouldn’t argue about *what something “really is”* but about the *utility of different perspectives*.
• There are certain areas and levels within which complex intelligence can operate and have very high level efficiency with it’s operations.
• We have profoundly misunderstood “simple” machines. There are “protocognitive” properties even in very simple systems (e.g., unexpected capacities in the “bubble sort” algorithm).
• Humility is crucial. We haven’t achieved anything that even science-fiction works could’ve predicted.

Moving Forward: Kindness and Avoiding Fear

• Fear and scarcity mentalities, the feeling like care is a ‘zero-sum-game’ hinder a greater more caring environment being created by humans.
• Unwarranted certainty about consciousness and cognition is dangerous. The field of Diverse Intelligence is just beginning, and many fundamental questions remain unanswered.
• The two primary ways we get it wrong with ethics: to value something less, or to give things compassion which don’t need them, with the former a bigger danger.
• Levin suggests prioritizing kindness, compassion, and recognizing the potential for sentience in unconventional forms, rather than being driven by fear of the other. This includes acknowledging that we may need to greatly expand our “circle of compassion.”
• We shouldn’t go backward towards ‘simpler’ less-developed civilizations that have a “one-ness with all life”, but use them as inspiration or guidance towards a scientific discovery in similar manner; or, a *starting point*.
• Dan Dennett’s philosophy is brought up: To discuss his generosity as an inspirational, intelligent human and that what made philosophy so compelling, was that Dennet did actual physical science/experimentation in additon to discussing philosophy and working out problems and discovering more together, even those that he disagreed with.

导言：孩子即“AI”

• 莱文开篇的描述听起来像是高级人工智能，但他实际上指的是人类的孩子，强调了创造*任何*新智能体所带来的固有不可预测性和替代性。这突显出对人工智能取代我们的焦虑并非新鲜事；它们是古老的、存在主义的担忧。
• 现有的系统被创建，被赋予自主权，被释放，并且其中一些，无论是好是坏，都被授权在未来执行这些行为。钓鱼需要许可证，但养育孩子却不需要。
• 所有形式的现存、可适应的生命最终都会停止。

合成与自然：一个错误的二分法

• 人们倾向于将合成生命（如人工智能）归类为根本不同的事物，但关于创造高能力生命体、将它们释放到世界上、以及控制有限这些真正的问题，对于自然（孩子）和合成实体来说是*相同*的。
• 人们可能在没有真正进行研究的情况下就做出了判断和陈述。

适应、持续与未来

• 不改变/适应的物种将会灭绝。而改变的物种，从技术上讲，也“消失”了，被其适应的形式所取代。这个悖论适用于所有进化系统，包括人类。
• 关键不是“作为固定物体的持续存在”，而是“作为过程的持续存在”（如过程哲学）。有趣的问题不是我们*是否*会改变，而是我们想*如何*改变，无论是作为个体还是作为一个物种。
• 100-200年后的人类可能不会接受当前人类状况的局限性（例如，腰痛、疾病、出生缺陷）为不可避免的；而未来可能会认为那些拒绝适应的人是不可思议的。具身自由和有意改变可能会成为常态。
• 在自然界中进化的不一定是作为大脑的智能，而是一些完全不同的东西，它们也应该属于这个术语。

多元智能与克服分类区别

• “多元智能”领域正在发展，并挑战传统的、狭隘的智能和心智定义。
• 多元智能寻求*所有可能*智能体之间的共性，而不仅仅是那些基于生物学或大脑的智能体。这包括考虑完全不同的基质、尺寸和智能可以运作的“空间”（不仅仅是三维空间）。
• 虚构（在没有完整信息的情况下创建合理的解释）是智能的一个特征，而不是一个缺陷。它对于经验的压缩、学习和创造力至关重要，但它不仅存在于生物智能中，也存在于某些简单的机械过程中，并非机器和软件所独有。
• 采访者提到了之前关于生物电智能的聊天，这导致了关于多元智能这个快速发展领域的讨论。
• 在哪里寻找心智和自主性的问题应该对所有存在保持开放。
• 人们倾向于假设物理的、认知系统与在这些物理实体之间传递的思想之间存在一个明确的区别，这不一定是有效的；两者都可能存在于一个流动的光谱上，而我们认为简单的物理对象可能最终并非如此，因为我们目前对该主题的视角尚处于起步阶段。

伦理含义与“合成共生”

• 创建/与多元智能（包括增强型人类）互动的伦理考虑是重要的。分类思维（“我们”与“他们”，自然与人工）是危险的。重点应该放在匹配“认知光锥”和分享存在性关注上。
• “合成共生”（应莱文的要求，由chat gbt创造的一个术语）：生物学和合成实体之间积极的、创造性的合作。
• 我们可以从任何社区中学到我们独自一人无法发现的东西。

机器与人类：一个被误导的问题

• “我们是机器吗？”这个问题提得不好。“机器”是一种*视角*或互动协议，而不是一个基本属性。不同的视角揭示不同的方面。我们不应该争论*某物“真正是什么”*，而应该争论*不同视角的效用*。
• 存在某些区域和层次，复杂的智能可以在其中运作，并在其操作中具有非常高的效率。
• 我们严重误解了“简单”机器。即使在非常简单的系统中也存在“原认知”属性（例如，“冒泡排序”算法中的意外能力）。
• 谦逊至关重要。我们还没有取得任何甚至科幻作品可以预测的成就。

前进：善良并避免恐惧

• 恐惧和稀缺心态，认为关爱是一种“零和游戏”的感觉，阻碍了人类创造一个更关怀的环境。
• 对意识和认知的不合理确定性是危险的。多元智能领域才刚刚开始，许多基本问题仍未得到解答。
• 我们在伦理方面犯错的两种主要方式：低估某物的价值，或对不需要同情的事物给予同情，前者是更大的危险。
• 莱文建议优先考虑善良、同情，并认识到非传统形式中存在感知的潜力，而不是被对其他的恐惧所驱动。这包括承认我们可能需要极大地扩大我们的“同情圈”。
• 我们不应该倒退回具有“与所有生命合一”的“更简单”、欠发达的文明，而是将它们作为以类似方式进行科学发现的灵感或指导；或者，一个*起点*。
• 丹·丹尼特的哲学被提了出来：讨论他的慷慨，作为一个鼓舞人心的、聪明的人，以及是什么让哲学如此引人入胜，是因为丹尼特除了讨论哲学和解决问题以及一起发现更多之外，还做了实际的物理科学/实验，甚至那些他不同意的人。