Forecasting the things that matter (with Peter Wildeford)
Spencer Greenberg and guest Yosha Bach explore intelligence as model-making, the nature of sentience, and how AI challenges our understanding of human minds. They delve into philosophical concepts like computational semantics and the nature of existence, offering insights into personal growth and intergroup relations.
Deep Dive Analysis
13 Topic Outline
Defining Intelligence: Models, Control, and Generalization
Intelligence, IQ, and the Nature of Pattern Recognition
Human Causal Inference vs. AI Statistical Correlations
Embodiment, Symbol Grounding, and Meaning from Text
GPT-3 in a Robot Body: Sentience and Online Learning
Westworld Analogy: Human Identity, Freedom, and Desires
Separating Pain from Suffering: Insights from Eastern Philosophy
Methods for Self-Regulation and Understanding Values
Defining Love: Shared Sacredness and Next-Level Agency
AI as a Philosophical Project: Bridging Math and Philosophy
Gödel's Incompleteness, Computability, and Truth
The Nature of Reality: Computable Universe and Existence
Limitations of Deep Learning and the Third Wave of AI
7 Key Concepts
Intelligence
Intelligence is defined as the ability to make models, typically in service of control. This allows a system to become an agent by predicting how its actions will lead to different future outcomes and preferring some over others, distinct from rationality, smartness, or wisdom.
Sentience
Sentience is the discovery of one's own nature as an agent in the world and the relationships one has to that world. It occurs when an intelligent system develops a model where it discovers itself in relation to its environment.
Vectors of Intelligence
Instead of a single linear scale, intelligence can be described across multiple dimensions, such as the capacity for autonomy, control, perception, reasoning, language learning, embodiment, collaboration, and knowledge representation. This allows for a richer comparison of different intelligent systems like humans, animals, and AI.
Causal Structure Discovery
This refers to the human ability to uncover the underlying systems that produce observed patterns, rather than merely recognizing statistical correlations. It is crucial for understanding how the world works and often relies on tracking changes and the flow of information over time.
Computational Semantics
A modern philosophical view where truth is understood as a stateful notion, assigned by executing an algorithm, rather than a timeless, platonic concept. This perspective implies that truth is tied to the procedure by which it is acquired and can change based on the sequence of states.
Shared Sacredness (Love)
This describes a form of love as the discovery of shared purposes that transcend individual ego, for which one is willing to sacrifice. It enables non-transactional interactions and the creation of 'next-level agency,' akin to how individual cells make sacrifices for the organism's existence.
Differentiable Programming
The underlying principle of deep learning, where programs (like neural networks) are written to describe a somewhat continuous state space. This allows solutions to problems to be found by following gradients, meaning small, predictable changes can be made to the program's parameters to move towards a desired output.
9 Questions Answered
Intelligence is defined as the ability to make models, typically in service of control, allowing a system to predict future outcomes of its actions and choose preferred branches.
Human intelligence involves algorithmic modeling, causal inference, and embodiment, while current AI models primarily focus on statistical correlations, often lacking true embodiment, online learning, or the ability to develop algorithms to model other algorithms.
Pain is a sensation, whereas suffering arises from a mismatch between what one tries to regulate and what can actually be regulated, often linked to narratives or stories one tells oneself about the pain or situation.
One can overcome emotional suffering by writing out thoughts to stop circular thinking, which allows for higher-level abstraction and a deeper understanding of the situation, including the perspectives of others and one's own role, leading to disentanglement from the immediate emotional state.
The philosophical project of AI aims to bridge mathematics and philosophy by building machine minds that can perform philosophy with higher acuity and detail than humans, ultimately seeking to understand what minds are as a mathematical model that can be automatically executed.
Gödel's proof implies that truth is not a stable, platonic concept but rather a stateful notion, a predicate assigned by executing an algorithm. Languages that contain infinities as if they existed become self-contradictory, suggesting that only computable results have true values.
From a computational perspective, for something to exist means it needs to be implemented. Its existence is tied to the degree of its implementation and the ability to describe it within a consistent language, often implying a causal structure that gives rise to regular observations.
Current deep learning models are not sample efficient, prone to overfitting (leading to adversarial examples), struggle with efficiently learning causal structures or programs, and rely on hardware 'hacks' rather than optimal architectures for intelligence.
The third wave of AI is expected to produce systems that can extend themselves into the world, understand and create languages, integrate deeply with people, use more universal representations, and perform program synthesis as effectively as they follow gradients.
13 Actionable Insights
1. Challenge Fixed Identity
Question your fixed identity (e.g., gender, personal story) to overcome self-imposed limitations and understand your full potential, as a rigid identity can prevent you from seeing other possibilities for yourself.
2. Alleviate Suffering by Regulating
Reduce suffering by improving your models of how the world works and your place within it, as suffering often arises from attempting to regulate things that are beyond your control.
3. Separate Pain from Suffering
Practice viewing pain as a neutral sensation rather than inherently ‘bad’ to create a distinction between the physical experience and the emotional suffering, fostering greater acceptance.
4. Process Emotional Pain by Writing
When experiencing intense emotional pain, such as heartbreak, sit down and write out your thoughts to prevent repetitive rumination and access higher-level understanding and more effective coping behaviors.
5. Resolve Disagreements by Elevating Perspective
To resolve disagreements, ascend at least two levels of abstraction to understand the underlying values and their construction in both yourself and others, which facilitates deeper understanding and negotiation.
6. Cultivate Multi-Generational Perspective
Perceive yourself as part of a multi-generational entity, such as a family line or a broader societal project, to foster a deeper sense of purpose and love that extends beyond individual desires.
7. Seek Good in All Worldviews
Actively look for positive aspects and valid ideas in all worldviews, including those of ‘out-groups,’ to gain a more accurate understanding of the world and avoid the belief that only your in-group holds the correct answers.
8. Develop Self-Understanding for Growth
Reverse engineer your own mind to build deeper structures of understanding, which enables personal growth and more reasonable interactions, such as evolving from infatuation to love based on shared purpose.
9. Test Child’s Programming Aptitude
For children, giving them the task to write programs from scratch, even without prior learning, can serve as a valuable predictor for later cognitive performance in life.
10. Adopt Model-Making Intelligence View
Consider intelligence primarily as the ability to make models, distinguishing it from rationality, smartness, or wisdom (the ability to pick the right goals), to gain a clearer understanding of cognitive abilities.
11. Understand Information as Change
Recognize that the meaning of information is fundamentally its relationship to change and other information, as the brain primarily registers and models changes to construct an understanding of stability.
12. Persist in Learning from Text
Be aware that deriving meaning and ‘signal’ from purely textual symbols is possible but often requires significantly more time and exposure compared to learning through embodied interaction with the world.
13. Embrace Computational View of Reality
Adopt a computational perspective where existence implies implementation and truth is a stateful, algorithmic process, rather than a timeless, platonic concept, to develop internally consistent languages for describing reality.
7 Key Quotes
Personally, I think of intelligence as the ability to make models, and it's distinct from being rational, right? A lot of irrational people are highly intelligent and vice versa.
Yosha Bach
Sentience is not the same thing as consciousness. It's basically just a discovery of your own nature as an agent in the world and the relationships that you have to the world.
Yosha Bach
The true message of Westworld is not a story about robots. It's a story about ourselves. Because we are like these robots. We are not actually human beings. We are not actually hairless monkeys. What I am is a mind. I am a side effect of the regulation needs of a monkey. I just happen to run on a monkey's brain. I am not that monkey. I can be whatever I want to be if I stop believing in the stories of the monkey and the desires of the monkey.
Yosha Bach
Suffering is not the result of the universe doing something to you as an agent. The universe that you experience is not the physical universe. It's not some weird quantum pattern or something. It's a world full of meanings, of desires, of stories that we have already chosen to adhere to before we got to the discovery of our own self.
Yosha Bach
The benefits of philosophy tend to be tiny. And even though I think it's the most important philosophical project of all, philosophy, for the most part, is not that important to humanity. Most of the big questions are no longer philosophical questions.
Yosha Bach
Pi is not a value. Pi is just a function from the computational perspective, which means you can plug your machine that computes digits of pi into an energy source, into your local sun. And when the sun burns out, this is your last digit.
Yosha Bach
I don't think that you are, if you do philosophy or if you do modeling as a mathematician, you are entitled to arbitrary ambiguity. I think that's a cop-out.
Yosha Bach