AF - Shard Theory - is it true for humans? by ErisApprentice
The Nonlinear Library
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Understanding Attention and Consciousness in Neuroscience
Exploration of how the brain filters stimuli through the salience network, dorsal attention system, and dopamine/reward networks, and the relationship between attention, consciousness, and goal-setting. Discussion on theories of consciousness, effective neuroscience, and the interaction between conscious processes and emotions in behavior.
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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Shard Theory - is it true for humans?, published by ErisApprentice on June 14, 2024 on The AI Alignment Forum.
And is it a good model for value learning in AI?
(Read on Substack:
https://recursingreflections.substack.com/p/shard-theory-is-it-true-for-humans)
TLDR
Shard theory proposes a view of value formation where experiences lead to the creation of context-based 'shards' that determine behaviour. Here, we go over psychological and neuroscientific views of learning, and find that while shard theory's emphasis on context bears similarity to types of learning such as conditioning, it does not address top-down influences that may decrease the locality of value-learning in the brain.
What's Shard Theory (and why do we care)?
In 2022, Quintin Pope and Alex Turner posted '
The shard theory of human values', where they described their view of how experiences shape the value we place on things. They give an example of a baby who enjoys drinking juice, and eventually learns that grabbing at the juice pouch, moving around to find the juice pouch, and modelling where the juice pouch might be, are all helpful steps in order to get to its reward.
'Human values', they say, 'are not e.g. an incredibly complicated, genetically hard-coded set of drives, but rather sets of contextually activated heuristics…' And since, like humans, AI is often trained with reinforcement learning, the same might apply to AI.
The original post is long (over 7,000 words) and dense, but Lawrence Chan helpfully posted a condensation of the topic in '
Shard Theory in Nine Theses: a Distillation and Critical Appraisal'. In it, he presents nine (as might be expected) main points of shard theory, ending with the last thesis: 'shard theory as a model of human values'. 'I'm personally not super well versed in neuroscience or psychology', he says, 'so I can't personally attest to [its] solidity…I'd be interested in hearing from experts in these fields on this topic.' And that's exactly what we're here to do.
A Crash Course on Human Learning
Types of learning
What is learning? A baby comes into the world and is inundated with sensory information of all kinds. From then on, it must process this information, take whatever's useful, and store it somehow for future use.
There's various places in the brain where this information is stored, and for various purposes. Looking at these various types of storage, or memory, can help us understand what's going on:
3 types of memory
We often group memory types by the length of time we hold on to them - 'working memory' (while you do some task), 'short-term memory' (maybe a few days, unless you revise or are reminded), and 'long-term memory' (effectively forever). Let's take a closer look at long-term memory:
Types of long-term memory
We can broadly split long-term memory into 'declarative' and 'nondeclarative'. Declarative memory is stuff you can talk about (or 'declare'): what the capital of your country is, what you ate for lunch yesterday, what made you read this essay. Nondeclarative covers the rest: a grab-bag of memory types including knowing how to ride a bike, getting habituated to a scent you've been smelling all day, and being motivated to do things you were previously rewarded for (like drinking sweet juice).
For most of this essay, we'll be focusing on the last type: conditioning.
Types of conditioning
Conditioning
Sometime in the 1890s, a physiologist named Ivan Pavlov was researching salivation using dogs. He would feed the dogs with powdered meat, and insert a tube into the cheek of each dog to measure their saliva.As expected, the dogs salivated when the food was in front of them. Unexpectedly, the dogs also salivated when they heard the footsteps of his assistant (who brought them their food).
Fascinated by this, Pavlov started to play a metronome whenever h...
And is it a good model for value learning in AI?
(Read on Substack:
https://recursingreflections.substack.com/p/shard-theory-is-it-true-for-humans)
TLDR
Shard theory proposes a view of value formation where experiences lead to the creation of context-based 'shards' that determine behaviour. Here, we go over psychological and neuroscientific views of learning, and find that while shard theory's emphasis on context bears similarity to types of learning such as conditioning, it does not address top-down influences that may decrease the locality of value-learning in the brain.
What's Shard Theory (and why do we care)?
In 2022, Quintin Pope and Alex Turner posted '
The shard theory of human values', where they described their view of how experiences shape the value we place on things. They give an example of a baby who enjoys drinking juice, and eventually learns that grabbing at the juice pouch, moving around to find the juice pouch, and modelling where the juice pouch might be, are all helpful steps in order to get to its reward.
'Human values', they say, 'are not e.g. an incredibly complicated, genetically hard-coded set of drives, but rather sets of contextually activated heuristics…' And since, like humans, AI is often trained with reinforcement learning, the same might apply to AI.
The original post is long (over 7,000 words) and dense, but Lawrence Chan helpfully posted a condensation of the topic in '
Shard Theory in Nine Theses: a Distillation and Critical Appraisal'. In it, he presents nine (as might be expected) main points of shard theory, ending with the last thesis: 'shard theory as a model of human values'. 'I'm personally not super well versed in neuroscience or psychology', he says, 'so I can't personally attest to [its] solidity…I'd be interested in hearing from experts in these fields on this topic.' And that's exactly what we're here to do.
A Crash Course on Human Learning
Types of learning
What is learning? A baby comes into the world and is inundated with sensory information of all kinds. From then on, it must process this information, take whatever's useful, and store it somehow for future use.
There's various places in the brain where this information is stored, and for various purposes. Looking at these various types of storage, or memory, can help us understand what's going on:
3 types of memory
We often group memory types by the length of time we hold on to them - 'working memory' (while you do some task), 'short-term memory' (maybe a few days, unless you revise or are reminded), and 'long-term memory' (effectively forever). Let's take a closer look at long-term memory:
Types of long-term memory
We can broadly split long-term memory into 'declarative' and 'nondeclarative'. Declarative memory is stuff you can talk about (or 'declare'): what the capital of your country is, what you ate for lunch yesterday, what made you read this essay. Nondeclarative covers the rest: a grab-bag of memory types including knowing how to ride a bike, getting habituated to a scent you've been smelling all day, and being motivated to do things you were previously rewarded for (like drinking sweet juice).
For most of this essay, we'll be focusing on the last type: conditioning.
Types of conditioning
Conditioning
Sometime in the 1890s, a physiologist named Ivan Pavlov was researching salivation using dogs. He would feed the dogs with powdered meat, and insert a tube into the cheek of each dog to measure their saliva.As expected, the dogs salivated when the food was in front of them. Unexpectedly, the dogs also salivated when they heard the footsteps of his assistant (who brought them their food).
Fascinated by this, Pavlov started to play a metronome whenever h...
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