Thank you for writing this! I’ve been curious about this exact intersection of topics, so I’m glad to see such a clear analysis.
My understanding of your framework is that Vipassana reduces suffering by training the mind to observe sensations without craving or aversion, which is to say it reduces unnecessary prediction error by training the mind not to compare reality to what is not the case. An accomplished meditator can therefore quickly dissipate stress by letting go of priors that would otherwise cause continued prediction error. I think this is a really valuable mapping of Vipassana to Active Inference.
At one point you write “suffering is fundamentally about experiencing prediction error” but then later you write that suffering is “the state which arises from updating one’s model to include fewer positive experiences in future or more negative experiences”. I think the first formulation is actually already sufficient. To me, it seems like suffering happens in the moment of discrepancy between prediction and sensation. For example, when I hear a sour note in a musical performance, I immediately experience distress. The sensation of the sour note clashes with my prediction, and that clash is unpleasant. So I would support the formulation where prediction error always contains an element of suffering.
You use the lottery winner as an example of positive prediction error, but I think even in that case the prediction error itself actually contains a faint discomfort which is hard to detect next to the joy and excitement. The actual happiness is not in the prediction error, but rather in the positive emotions the news brings. An analogy might be the high pitch noise a microwave makes. The noise itself is irritating, but the news that the food is ready is pleasant and usually outweighs the irritation.
I disagree that all prediction error equates to suffering. When you step into a warm shower you experience prediction error just as much as if you step into a cold shower, but I don’t think the initial experience of a warm shower contains any discomfort for most people, whereas I expect the cold shower usually does.
Furthermore, far more prediction error is experienced in life than suffering. Simply going for a walk leads to a continuous stream of prediction error, most of which people feel pretty neutral about.
I would say the warm shower causes less prediction error than the cold shower because it’s less shocking to the body, but there’s still a very subtle amount of discomfort which is hidden under all the positive feelings. The level of discomfort I’m talking about is very slight, but you would notice it if there was nothing else occupying your attention. I don’t mean to say it causes negative emotions. It’s more like the discomfort of imagining an unsatisfying shape, or watching a video at slightly lower resolution. If you compare any activity to deep sleep or unconsciousness, you can find sensations that grab your attention by being slightly irritating. As long as it’s noticeable I think it causes slight negative valence. But this is often outweighed by other aspects of the activity that increase valence.
Sitting at home doing nothing might involve the negative sensations of boredom, restlessness, and impatience, all of which disappear when we go for a walk, so any discomfort is hard to notice underneath the obvious increase in valence.
I think that the key is in the way that preferences inform our world model and thus what causes the prediction error to occur. There are errors you would observe that would strongly indicate that your preferences are less able to be met in the posterior model. This will cause suffering whereas an update towards a model in which your needs are met more easily is likely to cause a good feeling. For example, you sit down to eat a sandwich at Subway for the first time and the sub is actually way better than you expected. You will experience a pleasant feeling, and if things like this keep happening you might feel like you’ve really figured out some good strategy for operating.
In a sense you are actually decreasing prediction error more than you are increasing it when a good thing happens to you because you always generate prediction error based on the difference between your ideal world and your observed reality. So when you have a very positive experience, this error between the ideal and observed is lessened. This could outweigh the prediction error of the prediction itself being wrong. The example I think of for this is the ecstatic child in Disney world.
On the other hand, the more you get accustomed to a pleasurable stimulus, the less pleasure you receive from it over time (hedonic adaptation). Since this happens to both positive and negative emotions, it seems to me that there is a kind of symmetry here. To me this suggests that decreasing prediction error results in more neutral emotional states rather than pleasant states.
How do you feel about Bayeslord’s description of Jhana meditation being a positive form of prediction error, creating a sort of feedback loop of bliss?
In his method, I think the happiness of the first few Jhanas is not caused by prediction error directly, but rather indirectly through the activation of the reward circuitry. So while the method involves creating some amount of prediction error, the ultimate result is less overall prediction error, because the reward neurotransmitters bring the experiential world closer to the ideal.
After the first three Jhanas, the reward circuitry is less relevant and you start to reduce overall prediction error through other means, by allowing attention to let go of aspects of the world model. In the ninth Jhana / nirodha samapatti that he mentions, attention lets go of everything and there’s no prediction error.
By comparison with higher Jhanas that are less attention grabbing, you can see the subtle discomfort present in the first few Jhanas, and I think that’s the remaining prediction error.
Thank you for writing this! I’ve been curious about this exact intersection of topics, so I’m glad to see such a clear analysis.
My understanding of your framework is that Vipassana reduces suffering by training the mind to observe sensations without craving or aversion, which is to say it reduces unnecessary prediction error by training the mind not to compare reality to what is not the case. An accomplished meditator can therefore quickly dissipate stress by letting go of priors that would otherwise cause continued prediction error. I think this is a really valuable mapping of Vipassana to Active Inference.
At one point you write “suffering is fundamentally about experiencing prediction error” but then later you write that suffering is “the state which arises from updating one’s model to include fewer positive experiences in future or more negative experiences”. I think the first formulation is actually already sufficient. To me, it seems like suffering happens in the moment of discrepancy between prediction and sensation. For example, when I hear a sour note in a musical performance, I immediately experience distress. The sensation of the sour note clashes with my prediction, and that clash is unpleasant. So I would support the formulation where prediction error always contains an element of suffering.
You use the lottery winner as an example of positive prediction error, but I think even in that case the prediction error itself actually contains a faint discomfort which is hard to detect next to the joy and excitement. The actual happiness is not in the prediction error, but rather in the positive emotions the news brings. An analogy might be the high pitch noise a microwave makes. The noise itself is irritating, but the news that the food is ready is pleasant and usually outweighs the irritation.
I disagree that all prediction error equates to suffering. When you step into a warm shower you experience prediction error just as much as if you step into a cold shower, but I don’t think the initial experience of a warm shower contains any discomfort for most people, whereas I expect the cold shower usually does.
Furthermore, far more prediction error is experienced in life than suffering. Simply going for a walk leads to a continuous stream of prediction error, most of which people feel pretty neutral about.
I would say the warm shower causes less prediction error than the cold shower because it’s less shocking to the body, but there’s still a very subtle amount of discomfort which is hidden under all the positive feelings. The level of discomfort I’m talking about is very slight, but you would notice it if there was nothing else occupying your attention. I don’t mean to say it causes negative emotions. It’s more like the discomfort of imagining an unsatisfying shape, or watching a video at slightly lower resolution. If you compare any activity to deep sleep or unconsciousness, you can find sensations that grab your attention by being slightly irritating. As long as it’s noticeable I think it causes slight negative valence. But this is often outweighed by other aspects of the activity that increase valence.
Sitting at home doing nothing might involve the negative sensations of boredom, restlessness, and impatience, all of which disappear when we go for a walk, so any discomfort is hard to notice underneath the obvious increase in valence.
I think that the key is in the way that preferences inform our world model and thus what causes the prediction error to occur. There are errors you would observe that would strongly indicate that your preferences are less able to be met in the posterior model. This will cause suffering whereas an update towards a model in which your needs are met more easily is likely to cause a good feeling. For example, you sit down to eat a sandwich at Subway for the first time and the sub is actually way better than you expected. You will experience a pleasant feeling, and if things like this keep happening you might feel like you’ve really figured out some good strategy for operating.
In a sense you are actually decreasing prediction error more than you are increasing it when a good thing happens to you because you always generate prediction error based on the difference between your ideal world and your observed reality. So when you have a very positive experience, this error between the ideal and observed is lessened. This could outweigh the prediction error of the prediction itself being wrong. The example I think of for this is the ecstatic child in Disney world.
There might be more work here though.
On the other hand, the more you get accustomed to a pleasurable stimulus, the less pleasure you receive from it over time (hedonic adaptation). Since this happens to both positive and negative emotions, it seems to me that there is a kind of symmetry here. To me this suggests that decreasing prediction error results in more neutral emotional states rather than pleasant states.
How do you feel about Bayeslord’s description of Jhana meditation being a positive form of prediction error, creating a sort of feedback loop of bliss?
https://open.substack.com/pub/bayeslord/p/a-simple-mechanistic-theory-of-jhanas?utm_source=share&utm_medium=android&r=34hoq
In his method, I think the happiness of the first few Jhanas is not caused by prediction error directly, but rather indirectly through the activation of the reward circuitry. So while the method involves creating some amount of prediction error, the ultimate result is less overall prediction error, because the reward neurotransmitters bring the experiential world closer to the ideal.
After the first three Jhanas, the reward circuitry is less relevant and you start to reduce overall prediction error through other means, by allowing attention to let go of aspects of the world model. In the ninth Jhana / nirodha samapatti that he mentions, attention lets go of everything and there’s no prediction error.
By comparison with higher Jhanas that are less attention grabbing, you can see the subtle discomfort present in the first few Jhanas, and I think that’s the remaining prediction error.