Chapter 4 - Action and Expected Experience
Presented by Zoe Jenkin
The first three chapters of The Predictive Mind sketch how prediction error minimization underlies all perceptual processing, explaining various features of the mind using one unified framework. Chapter four addresses the question of how action fits into the PEM framework, arguing not only that PEM can adequately accommodate action, but also that action plays a crucial role in minimizing prediction error. We end up with a picture on which in any given case of a prediction error (a discrepancy between the prediction of the system and the sensory input), this error can in principle be minimized in one of two ways—by revising one’s priors and generating a new hypothesis, or by acting so as to selectively sample the world in a way that makes the input data match the selected hypothesis. An example of such selective sampling might be, if the system predicts that there will be a face before it, it will fixate its eyes toward the region where the prediction dictates a nose will be, and scan for a surface with a characteristically nose-like slope. Hohwy notes that this active, selective sampling method will be more efficient than random sampling, because it will target regions of space where the hypothesis makes a particular or unique prediction and so can easily be confirmed or disconfirmed. On this view, “perceiving and acting are but two different ways of doing the same thing” (71), where that “thing” is minimizing prediction error.
This raises the question of how the mind decides which of these courses of action to take in any individual case—should it revise its priors and generate a new hypothesis, or should it act so as to change the sensory input and match the current hypothesis? Hohwy indicates that precision predictions facilitate this decision. If the input that would be obtained upon acting is predicted to be more precise than the occurrent input, the action route is taken. If, in contrast, the input that would be obtained upon acting is predicted to be less precise than the occurrent input, the prediction revision route is taken (78). Both of these routes are fundamentally ways of minimizing prediction error. The core difference on this picture between beliefs and perceptions on the one hand, and desires on the other, is in their directions of fit—beliefs and perceptions involve making the mind fit the world, while desires (or mismatches of the sort that leads to action) involve making the world fit the mind (83).
One worry that arises right off the bat is, if the goal of the system is to minimize prediction error, why don’t we just always close our eyes and predict a dark room? This would create a state of no prediction error, because the sensory input would match the predicted state of the system, and thus seem to fulfill the goal of minimizing prediction error. Hohwy’s reply to this worry is that prior probabilities provide a constraint on the sorts of hypotheses that the system will generate, and thereby on those that can be confirmed or disconfirmed through selective sampling. The hypothesis of being in a dark room will have a low prior probability in most contexts, so it will not end up being selected as the contents of perception. Action can only be used to test the reliability of hypotheses over space and time, not to generate them in the first place.
This is related to a more general illicit confirmation worry: by engaging in selective sampling to test any hypothesis (dark room or otherwise), won’t we just confirm whatever prediction we generate, by taking as input whatever bit of the world would confirm it, thereby eliminating the check on predictions that sensory input was supposed to provide? This seems at least at first glance analogous to confirmation bias in empirical science. Hohwy’s reply to this worry takes two different forms for the interoceptive and exteroceptive senses. For the interoceptive senses, this sort of cycle is exactly what we want, because it allows us to maintain homeostasis. For the exteroceptive senses, while this cycle is not what we want in order to arrive at veridical perception of the world, the cycle won’t actually occur, because only hypotheses with high priors will be tested in the first place, and then the world will place significant constraints on which hypotheses can be confirmed. Even if selective that is sampling does allow for some leeway in which hypotheses might be confirmed, ultimately if the hypothesis is significantly off base, the brain will revert to revision by perceptual inference.
Another worry that arises is, if action and perception serve the same basic function of minimizing prediction error, why do we need action at all when we have Bayesian inference? Hohwy’s response to this question is that once a perceptual inference is made, action can strengthen our confidence in that inference, because it can confirm that hypothesis across alternative space and time contexts. This will help decrease uncertainty, especially when multiple competing hypotheses have relatively similar posterior probabilities. Also, this testing by active sampling is quick and efficient, because it only involves generating the predictions across space and time of the selected hypothesis, instead of running the entire Bayesian calculus multiple times on various sets of priors. For these reasons, while action has the same overall goal as prediction, it achieves that goal in some ways that are uniquely useful to the system.
Another important feature of how action works in a PEM system is that the system includes models of itself, in addition to models of the external world. So in humans, the perceptual system will also make predictions about inner states such as heartbeat, arousal, and proprioceptive and kinesthetic states, allowing for the regulation of such internal systems. This explains both how the interoceptive senses function to regulate bodily states, as well as how information about out inner states can figure in our predictions of the world (for example in calculations about whether you could leap over a puddle of a certain length). When action is taken so as to minimize error with respect to distal goal states, lower-level predictions are made with respect to all of the internal routes to those goals, including the small-scale muscle movements that would arise when pursing a particular course of action. This allows for specificity in our determination of which route to a goal state to pursue. In these sorts of cases, the system’s models on internal and external states of the body and world will function together to generate action.
Here are some questions about the role of action in the PEM framework:
1. Hohwy says that the system determines whether to minimize prediction error by acting or by revising priors depending on the relative precision predictions about the occurrent vs. counterfactual input data. How does the mind know whether the data that will be gleaned upon acting will be more or less precise than the occurrent input data? This seems to depend on the quality of input data that the system would receive in the future. How does the calculation of these counterfactual precision predictions work?
2. Is the selective sampling that occurs selective in the sense that it targets areas that would be likely to confirm the hypothesis, or in the sense that it targets areas that would be likely to bear on the hypothesis one way or the other? Only the first sort of selective sampling seems to be the sort that would cause an illicit confirmation worry. However, the first sort seems like it would do much better than the second toward minimizing prediction error.
3. The PEM account attempts to reduce desires to beliefs with a different direction of fit. For example, having a desire for a muffin would be selecting a hypothesis with the content “there is a muffin before me” when there was no sensory input indicating muffin-presence. This would in turn explain the connection between desire and action, because you would be driven to act so as to change the sensory input so it would indicate that there was in fact a muffin before you (by, for example, getting yourself a muffin). But how would we ever get into the sort of predictive state that would drive action toward such a specific goal? In most contexts, your muffin prior is not high—it would only be high in certain situations, such as if you were near an oven from which a muffin smell was emanating, or if you were on a street near a bakery that you knew sold muffins. So given that the muffin prior is usually very low in contexts when it would not be reasonable to expect a muffin, how can we explain cases like one in which I am sitting at my desk and all of a sudden I want a muffin? This sort of out of the blue (or at least unconnected from any occurrent sensory input) desire seems to occur all the time, and it does not seem obvious how it would be generated given what it seems the inputs to the Bayesian calculus would be in these contexts. How do we ever end up desiring anything unexpected?
4. Where does this picture, on which the difference between belief and desire is simply a difference in direction of fit, leave other mental attitudes? It does not on the face of it seem to leave much room for more finely-grained distinctions between fears, hopes, and other standardly accepted folk psychological states. Does the view hold that all of these can be reduced to beliefs or desires?
5. Does the PEM framework have any resources to explain associational connections between mental states, such as why reading the word “salt” makes me think of “pepper”, or why the smell of Guinness makes me think of Oxford? While it is possible there could be inferential connections between the two concepts/experiences in these cases, there also seems to be many psychological transitions that are driven simply by brute associations (that were likely formed due to past co-occurrence). The basic mechanisms of the PEM system are inferential, so this sort of associational triggering, whether perceptually or cognitively based, does not seem to fit in naturally. How does the PEM framework make sense of such cases?
6. Hohwy says that our inability to tickle ourselves (which survives even across extensive changes in body image) supports the idea that precision predictions help determine whether to act or revise predictions in any given case. This was an intriguing illustration and I am curious to hear more. How is this evidence for the view?
7. How separable is the PEM account of action from the rest of the PEM model of the mind? If we had particular reasons for rejecting the explanation of action as fundamentally a route to minimizing prediction error, could we still accept the broad strokes of the account of perceptual processing from the first three chapters? Or must they stand and fall together?