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Predictive Processing: Unlocking the Mysteries of Mind & Body (Part V)

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In the previous post, part 4 in this series on Predictive Processing (PP), I explored some aspects of reasoning and how different forms of reasoning can be built from a foundational bedrock of Bayesian inference (click here for parts 1, 2, or 3).  This has a lot to do with language, but I also claimed that it depends on how the brain is likely generating new models, which I think is likely to involve some kind of natural selection operating on neural networks.  The hierarchical structure of the generative models for these predictions as described within a PP framework, also seems to fit well with the hierarchical structure that we find in the brain’s neural networks.  In this post, I’m going to talk about the relation between memory, imagination, and unconscious and conscious forms of reasoning.

Memory, Imagination, and Reasoning

Memory is of course crucial to the PP framework whether for constructing real-time predictions of incoming sensory information (for perception) or for long-term predictions involving high-level, increasingly abstract generative models that allow us to accomplish complex future goals (like planning to go grocery shopping, or planning for retirement).  Either case requires the brain to have stored some kind of information pertaining to predicted causal relations.  Rather than memories being some kind of exact copy of past experiences (where they’d be stored like data on a computer), research has shown that memory functions more like a reconstruction of those past experiences which are modified by current knowledge and context, and produced by some of the same faculties used in imagination.

This accounts for any false or erroneous aspects of our memories, where the recalled memory can differ substantially from how the original event was experienced.  It also accounts for why our memories become increasingly altered as more time passes.  Over time, we learn new things, continuing to change many of our predictive models about the world, and thus have a more involved reconstructive process the older the memories are.  And the context we find ourselves in when trying to recall certain memories, further affect this reconstruction process, adapting our memories in some sense to better match what we find most salient and relevant in the present moment.

Conscious vs. Unconscious Processing & Intuitive Reasoning (Intuition)

Another attribute of memory is that it is primarily unconscious, where we seem to have this pool of information that is kept out of consciousness until parts of it are needed (during memory recall or or other conscious thought processes).  In fact, within the PP framework we can think of most of our generative models (predictions), especially those operating in the lower levels of the hierarchy, as being out of our conscious awareness as well.  However, since our memories are composed of (or reconstructed with) many higher level predictions, and since only a limited number of them can enter our conscious awareness at any moment, this implies that most of the higher-level predictions are also being maintained or processed unconsciously as well.

It’s worth noting however that when we were first forming these memories, a lot of the information was in our consciousness (the higher-level, more abstract predictions in particular).  Within PP, consciousness plays a special role since our attention modifies what is called the precision weight (or synaptic gain) on any prediction error that flows upward through the predictive hierarchy.  This means that the prediction errors produced from the incoming sensory information or at even higher levels of processing are able to have a greater impact on modifying and updating the predictive models.  This makes sense from an evolutionary perspective, where we can ration our cognitive resources in a more adaptable way, by allowing things that catch our attention (which may be more important to our survival prospects) to have the greatest effect on how we understand the world around us and how we need to act at any given moment.

After repeatedly encountering certain predicted causal relations in a conscious fashion, the more likely those predictions can become automated or unconsciously processed.  And if this has happened with certain rules of inference that govern how we manipulate and process many of our predictive models, it seems reasonable to suspect that this would contribute to what we call our intuitive reasoning (or intuition).  After all, intuition seems to give people the sense of knowing something without knowing how it was acquired and without any present conscious process of reasoning.

This is similar to muscle memory or procedural memory (like learning how to ride a bike) which is consciously processed at first (thus involving many parts of the cerebral cortex), but after enough repetition it becomes a faster and more automated process that is accomplished more economically and efficiently by the basal ganglia and cerebellum, parts of the brain that are believed to handle a great deal of unconscious processing like that needed for procedural memory.  This would mean that the predictions associated with these kinds of causal relations begin to function out of our consciousness, even if the same predictive strategy is still in place.

As mentioned above, one difference between this unconscious intuition and other forms of reasoning that operate within the purview of consciousness is that our intuitions are less likely to be updated or changed based on new experiential evidence since our conscious attention isn’t involved in the updating process. This means that the precision weight of upward flowing prediction errors that encounter downward flowing predictions that are operating unconsciously will have little impact in updating those predictions.  Furthermore, the fact that the most automated predictions are often those that we’ve been using for most of our lives, means that they are also likely to have extremely high Bayesian priors, further isolating them from modification.

Some of these priors may become what are called hyperpriors or priors over priors (many of these believed to be established early in life) where there may be nothing that can overcome them, because they describe an extremely abstract feature of the world.  An example of a possible hyperprior could be one that demands that the brain settle on one generative model even when it’s comparable to several others under consideration.  One could call this a “tie breaker” hyperprior, where if the brain didn’t have this kind of predictive mechanism in place, it may never be able to settle on a model, causing it to see the world (or some aspect of it) as a superposition of equiprobable states rather than simply one determinate state.  We could see the potential problem in an organism’s survival prospects if it didn’t have this kind of hyperprior in place.  Whether or not a hyperprior like this is a form of innate specificity, or acquired in early learning is debatable.

An obvious trade-off with intuition (or any kind of innate biases) is that it provides us with fast, automated predictions that are robust and likely to be reliable much of the time, but at the expense of not being able to adequately handle more novel or complex situations, thereby leading to fallacious inferences.  Our cognitive biases are also likely related to this kind of unconscious reasoning whereby evolution has naturally selected cognitive strategies that work well for the kind of environment we evolved in (African savanna, jungle, etc.) even at the expense of our not being able to adapt as well culturally or in very artificial situations.

Imagination vs. Perception

One large benefit of storing so much perceptual information in our memories (predictive models with different spatio-temporal scales) is our ability to re-create it offline (so to speak).  This is where imagination comes in, where we are able to effectively simulate perceptions without requiring a stream of incoming sensory data that matches it.  Notice however that this is still a form of perception, because we can still see, hear, feel, taste and smell predicted causal relations that have been inferred from past sensory experiences.

The crucial difference, within a PP framework, is the role of precision weighting on the prediction error, just as we saw above in terms of trying to update intuitions.  If precision weighting is set or adjusted to be relatively low with respect to a particular set of predictive models, then prediction error will have little if any impact on the model.  During imagination, we effectively decouple the bottom-up prediction error from the top-down predictions associated with our sensory cortex (by reducing the precision weighting of the prediction error), thus allowing us to intentionally perceive things that aren’t actually in the external world.  We need not decouple the error from the predictions entirely, as we may want our imagination to somehow correlate with what we’re actually perceiving in the external world.  For example, maybe I want to watch a car driving down the street and simply imagine that it is a different color, while still seeing the rest of the scene as I normally would.  In general though, it is this decoupling “knob” that we can turn (precision weighting) that underlies our ability to produce and discriminate between normal perception and our imagination.

So what happens when we lose the ability to control our perception in a normal way (whether consciously or not)?  Well, this usually results in our having some kind of hallucination.  Since perception is often referred to as a form of controlled hallucination (within PP), we could better describe a pathological hallucination (such as that arising from certain psychedelic drugs or a condition like Schizophrenia) as a form of uncontrolled hallucination.  In some cases, even with a perfectly normal/healthy brain, when the prediction error simply can’t be minimized enough, or the brain is continuously switching between models, based on what we’re looking at, we experience perceptual illusions.

Whether it’s illusions, hallucinations, or any other kind of perceptual pathology (like not being able to recognize faces), PP offers a good explanation for why these kinds of experiences can happen to us.  It’s either because the models are poor (their causal structure or priors) or something isn’t being controlled properly, like the delicate balance between precision weighting and prediction error, any of which that could result from an imbalance in neurotransmitters or some kind of brain damage.

Imagination & Conscious Reasoning

While most people would tend to define imagination as that which pertains to visual imagery, I prefer to classify all conscious experiences that are not directly resulting from online perception as imagination.  In other words, any part of our conscious experience that isn’t stemming from an immediate inference of incoming sensory information is what I consider to be imagination.  This is because any kind of conscious thinking is going to involve an experience that could in theory be re-created by an artificial stream of incoming sensory information (along with our top-down generative models that put that information into a particular context of understanding).  As long as the incoming sensory information was a particular way (any way that we can imagine!), even if it could never be that way in the actual external world we live in, it seems to me that it should be able to reproduce any conscious process given the right top-down predictive model.  Another way of saying this is that imagination is simply another word to describe any kind of offline conscious mental simulation.

This also means that I’d classify any and all kinds of conscious reasoning processes as yet another form of imagination.  Just as is the case with more standard conceptions of imagination (within PP at least), we are simply taking particular predictive models, manipulating them in certain ways in order to simulate some result with this process decoupled (at least in part) from actual incoming sensory information.  We may for example, apply a rule of inference that we’ve picked up on and manipulate several predictive models of causal relations using that rule.  As mentioned in the previous post and in the post from part 2 of this series, language is also likely to play a special role here where we’ll likely be using it to help guide this conceptual manipulation process by organizing and further representing the causal relations in a linguistic form, and then determining the resulting inference (which will more than likely be in a linguistic form as well).  In doing so, we are able to take highly abstract properties of causal relations and apply rules to them to extract new information.

If I imagine a purple elephant trumpeting and flying in the air over my house, even though I’ve never experienced such a thing, it seems clear that I’m manipulating several different types of predicted causal relations at varying levels of abstraction and experiencing the result of that manipulation.  This involves inferred causal relations like those pertaining to visual aspects of elephants, the color purple, flying objects, motion in general, houses, the air, and inferred causal relations pertaining to auditory aspects like trumpeting sounds and so forth.

Specific instances of these kinds of experienced causal relations have led to my inferring them as an abstract probabilistically-defined property (e.g. elephantness, purpleness, flyingness, etc.) that can be reused and modified to some degree to produce an infinite number of possible recreated perceptual scenes.  These may not be physically possible perceptual scenes (since elephants don’t have wings to fly, for example) but regardless I’m able to add or subtract, mix and match, and ultimately manipulate properties in countless ways, only limited really by what is logically possible (so I can’t possibly imagine what a square circle would look like).

What if I’m performing a mathematical calculation, like “adding 9 + 9”, or some other similar problem?  This appears (upon first glance at least) to be very qualitatively different than simply imagining things that we tend to perceive in the world like elephants, books, music, and other things, even if they are imagined in some phantasmagorical way.  As crazy as those imagined things may be, they still contain things like shapes, colors, sounds, etc., and a mathematical calculation seems to lack this.  I think the key thing to realize here is the fundamental process of imagination as being able to add or subtract and manipulate abstract properties in any way that is logically possible (given our current set of predictive models).  This means that we can imagine properties or abstractions that lack all the richness of a typical visual/auditory perceptual scene.

In the case of a mathematical calculation, I would be manipulating previously acquired predicted causal relations that pertain to quantity and changes in quantity.  Once I was old enough to infer that separate objects existed in the world, then I could infer an abstraction of how many objects there were in some space at some particular time.  Eventually, I could abstract the property of how many objects without applying it to any particular object at all.  Using language to associate a linguistic symbol for each and every specific quantity would lay the groundwork for a system of “numbers” (where numbers are just quantities pertaining to no particular object at all).  Once this was done, then my brain could use the abstraction of quantity and manipulate it by following certain inferred rules of how quantities can change by adding to or subtracting from them.  After some practice and experience I would now be in a reasonable position to consciously think about “adding 9 + 9”, and either do it by following a manual iterative rule of addition that I’ve learned to do with real or imagined visual objects (like adding up some number of apples or dots/points in a row or grid), or I can simply use a memorized addition table and search/recall the sum I’m interested in (9 + 9 = 18).

Whether we consider imagining a purple elephant, mentally adding up numbers, thinking about what I’m going to say to my wife when I see her next, or trying to explicitly apply logical rules to some set of concepts, all of these forms of conscious thought or reasoning are all simply different sets of predictive models that I’m simply manipulating in mental simulations until I arrive at a perception that’s understood in the desired context and that has minimal prediction error.

Putting it all together

In summary, I think we can gain a lot of insight by looking at all the different aspects of brain function through a PP framework.  Imagination, perception, memory, intuition, and conscious reasoning fit together very well when viewed as different aspects of hierarchical predictive models that are manipulated and altered in ways that give us a much more firm grip on the world we live in and its inferred causal structure.  Not only that, but this kind of cognitive architecture also provides us with an enormous potential for creativity and intelligence.  In the next post in this series, I’m going to talk about consciousness, specifically theories of consciousness and how they may be viewed through a PP framework.

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Predictive Processing: Unlocking the Mysteries of Mind & Body (Part IV)

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In the previous post which was part 3 in this series (click here for parts 1 and 2) on Predictive Processing (PP), I discussed how the PP framework can be used to adequately account for traditional and scientific notions of knowledge, by treating knowledge as a subset of all the predicted causal relations currently at our brain’s disposal.  This subset of predictions that we tend to call knowledge has the special quality of especially high confidence levels (high Bayesian priors).  Within a scientific context, knowledge tends to have an even stricter definition (and even higher confidence levels) and so we end up with a smaller subset of predictions which have been further verified through comparing them with the inferred predictions of others and by testing them with external means of instrumentation and some agreed upon conventions for analysis.

However, no amount of testing or verification is going to give us direct access to any knowledge per se.  Rather, the creation or discovery of knowledge has to involve the application of some kind of reasoning to explain the causal inputs, and only after this reasoning process can the resulting predicted causal relations be validated to varying degrees by testing it (through raw sensory data, external instruments, etc.).  So getting an adequate account of reasoning within any theory or framework of overall brain function is going to be absolutely crucial and I think that the PP framework is well-suited for the job.  As has already been mentioned throughout this post-series, this framework fundamentally relies on a form of Bayesian inference (or some approximation) which is a type of reasoning.  It is this inferential strategy then, combined with a hierarchical neurological structure for it to work upon, that would allow our knowledge to be created in the first place.

Rules of Inference & Reasoning Based on Hierarchical-Bayesian Prediction Structure, Neuronal Selection, Associations, and Abstraction

While PP tends to focus on perception and action in particular, I’ve mentioned that I see the same general framework as being able to account for not only the folk psychological concepts of beliefs, desires, and emotions, but also that the hierarchical predictive structure it entails should plausibly be able to account for language and ontology and help explain the relationship between the two.  It seems reasonable to me that the associations between all of these hierarchically structured beliefs or predicted causal relations at varying levels of abstraction, can provide a foundation for our reasoning as well, whether intuitive or logical forms of reasoning.

To illustrate some of the importance of associations between beliefs, consider an example like the belief in object permanence (i.e. that objects persist or continue to exist even when I can no longer see them).  This belief of ours has an extremely high prior because our entire life experience has only served to support this prediction in a large number of ways.  This means that it’s become embedded or implicit in a number of other beliefs.  If I didn’t predict that object permanence was a feature of my reality, then an enormous number of everyday tasks would become difficult if not impossible to do because objects would be treated as if they are blinking into and out of existence.

We have a large number of beliefs that require object permanence (and which are thus associated with object permanence), and so it is a more fundamental lower-level prediction (though not as low level as sensory information entering the visual cortex) and we use this lower-level prediction to build upon into any number of higher-level predictions in the overall conceptual/predictive hierarchy.  When I put money in a bank, I expect to be able to spend it even if I can’t see it anymore (such as with a check or debit card).  This is only possible if my money continues to exist even when out of view (regardless of if the money is in a paper/coin or electronic form).  This is just one of many countless everyday tasks that depend on this belief.  So it’s no surprise that this belief (this set of predictions) would have an incredibly high Bayesian prior, and therefore I would treat it as a non-negotiable fact about reality.

On the other hand, when I was a newborn infant, I didn’t have this belief of object permanence (or at best, it was a very weak belief).  Most psychologists estimate that our belief in object permanence isn’t acquired until after several months of brain development and experience.  This would translate to our having a relatively low Bayesian prior for this belief early on in our lives, and only once a person begins to form predictions based on these kinds of recognized causal relations can we begin to increase that prior and perhaps eventually reach a point that results in a subjective experience of a high degree in certainty for this particular belief.  From that point on, we are likely to simply take that belief for granted, no longer questioning it.  The most important thing to note here is that the more associations made between beliefs, the higher their effective weighting (their priors), and thus the higher our confidence in those beliefs becomes.

Neural Implementation, Spontaneous or Random Neural Activity & Generative Model Selection

This all seems pretty reasonable if a neuronal implementation worked to strengthen Bayesian priors as a function of the neuronal/synaptic connectivity (among other factors), where neurons that fire together are more likely to wire together.  And connectivity strength will increase the more often this happens.  On the flip-side, the less often this happens or if it isn’t happening at all then the connectivity is likely to be weakened or non-existent.  So if a concept (or a belief composed of many conceptual relations) is represented by some cluster of interconnected neurons and their activity, then it’s applicability to other concepts increases its chances of not only firing but also increasing the strength of wiring with those other clusters of neurons, thus plausibly increasing the Bayesian priors for the overlapping concept or belief.

Another likely important factor in the Bayesian inferential process, in terms of the brain forming new generative models or predictive hypotheses to test, is the role of spontaneous or random neural activity and neural cluster generation.  This random neural activity could plausibly provide a means for some randomly generated predictions or random changes in the pool of predictive models that our brain is able to select from.  Similar to the role of random mutation in gene pools which allows for differential reproductive rates and relative fitness of offspring, some amount of randomness in neural activity and the generative models that result would allow for improved models to be naturally selected based on those which best minimize prediction error.  The ability to minimize prediction error could be seen as a direct measure of the fitness of the generative model, within this evolutionary landscape.

This idea is related to the late Gerald Edelman’s Theory of Neuronal Group Selection (NGS), also known as Neural Darwinism, which I briefly explored in a post I wrote long ago.  I’ve long believed that this kind of natural selection process is applicable to a number of different domains (aside from genetics), and I think any viable version of PP is going to depend on it to at least some degree.  This random neural activity (and the naturally selected products derived from them) could be thought of as contributing to a steady supply of new generative models to choose from and thus contributing to our overall human creativity as well whether for reasoning and problem solving strategies or simply for artistic expression.

Increasing Abstraction, Language, & New Rules of Inference

This kind of use it or lose it property of brain plasticity combined with dynamic associations between concepts or beliefs and their underlying predictive structure, would allow for the brain to accommodate learning by extracting statistical inferences (at increasing levels of abstraction) as they occur and modifying or eliminating those inferences by changing their hierarchical associative structure as prediction error is encountered.  While some form of Bayesian inference (or an approximation to it) underlies this process, once lower-level inferences about certain causal relations have been made, I believe that new rules of inference can be derived from this basic Bayesian foundation.

To see how this might work, consider how we acquire a skill like learning how to speak and write in some particular language.  The rules of grammar, the syntactic structure and so forth which underlie any particular language are learned through use.  We begin to associate words with certain conceptual structures (see part 2 of this post-series for more details on language and ontology) and then we build up the length and complexity of our linguistic expressions by adding concepts built on higher levels of abstraction.  To maximize the productivity and specificity of our expressions, we also learn more complex rules pertaining to the order in which we speak or write various combinations of words (which varies from language to language).

These grammatical rules can be thought of as just another higher-level abstraction, another higher-level causal relation that we predict will convey more specific information to whomever we are speaking to.  If it doesn’t seem to do so, then we either modify what we have mistakenly inferred to be those grammatical rules, or depending on the context, we may simply assume that the person we’re talking to hasn’t conformed to the language or grammar that my community seems to be using.

Just like with grammar (which provides a kind of logical structure to our language), we can begin to learn new rules of inference built on the same probabilistic predictive bedrock of Bayesian inference.  We can learn some of these rules explicitly by studying logic, induction, deduction, etc., and consciously applying those rules to infer some new piece of knowledge, or we can learn these kinds of rules implicitly based on successful predictions (pertaining to behaviors of varying complexity) that happen to result from stumbling upon this method of processing causal relations within various contexts.  As mentioned earlier, this would be accomplished in part by the natural selection of randomly-generated neural network changes that best reduce the incoming prediction error.

However, language and grammar are interesting examples of an acquired set of rules because they also happen to be the primary tool that we use to learn other rules (along with anything we learn through verbal or written instruction), including (as far as I can tell) various rules of inference.  The logical structure of language (though it need not have an exclusively logical structure), its ability to be used for a number of cognitive short-cuts, and it’s influence on our thought complexity and structure, means that we are likely dependent on it during our reasoning processes as well.

When we perform any kind of conscious reasoning process, we are effectively running various mental simulations where we can intentionally manipulate our various generative models to test new predictions (new models) at varying levels of abstraction, and thus we also manipulate the linguistic structure associated with those generative models as well.  Since I have a lot more to say on reasoning as it relates to PP, including more on intuitive reasoning in particular, I’m going to expand on this further in my next post in this series, part 5.  I’ll also be exploring imagination and memory including how they relate to the processes of reasoning.

Predictive Processing: Unlocking the Mysteries of Mind & Body (Part II)

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In the first post of this series I introduced some of the basic concepts involved in the Predictive Processing (PP) theory of perception and action.  I briefly tied together the notions of belief, desire, emotion, and action from within a PP lens.  In this post, I’d like to discuss the relationship between language and ontology through the same framework.  I’ll also start talking about PP in an evolutionary context as well, though I’ll have more to say about that in future posts in this series.

Active (Bayesian) Inference as a Source for Ontology

One of the main themes within PP is the idea of active (Bayesian) inference whereby we physically interact with the world, sampling it and modifying it in order to reduce our level of uncertainty in our predictions about the causes of the brain’s inputs.  Within an evolutionary context, we can see why this form of embodied cognition is an ideal schema for an information processing system to employ in order to maximize chances of survival in our highly interactive world.

In order to reduce the amount of sensory information that has to be processed at any given time, it is far more economical for the brain to only worry about the prediction error that flows upward through the neural system, rather than processing all incoming sensory data from scratch.  If the brain is employing a set of predictions that can “explain away” most of the incoming sensory data, then the downward flow of predictions can encounter an upward flow of sensory information (effectively cancelling each other out) and the only thing that remains to propagate upward through the system and do any “cognitive work” (i.e. the only thing that needs to be processed) on the predictive models flowing downward is the remaining prediction error (prediction error = predictions of sensory input minus the actual sensory input).  This is similar to data compression strategies for video files (for example) that only worry about the information that changes over time (pixels that change brightness/color) and then simply compress the information that remains constant (pixels that do not change from frame-to-frame).

The ultimate goal for this strategy within an evolutionary context is to allow the organism to understand its environment in the most salient ways for the pragmatic purposes of accomplishing goals relating to survival.  But once humans began to develop culture and evolve culturally, the predictive strategy gained a new kind of evolutionary breathing space, being able to predict increasingly complex causal relations and developing technology along the way.  All of these inferred causal relations appear to me to be the very source of our ontology, as each hierarchically structured prediction and its ability to become associated with others provides an ideal platform for differentiating between any number of spatio-temporal conceptions and their categorical or logical organization.

An active Bayesian inference system is also ideal to explain our intellectual thirst, human curiosity, and interest in novel experiences (to some degree), because we learn more about the world (and ourselves) by interacting with it in new ways.  In doing so, we are provided with a constant means of fueling and altering our ontology.

Language & Ontology

Language is an important component as well and it fits well within a PP framework as it serves to further link perception and action together in a very important way, allowing us to make new kinds of predictions about the world that wouldn’t have been possible without it.   A tool like language makes a lot of sense from an evolutionary perspective as well since better predictions about the world result in a higher chance of survival.

When we use language by speaking or writing it, we are performing an action which is instantiated by the desire to do so (see previous post about “desire” within a PP framework).  When we interpret language by listening to it or by reading, we are performing a perceptual task which is again simply another set of predictions (in this case, pertaining to the specific causes leading to our sensory inputs).  If we were simply sending and receiving non-lingual nonsense, then the same basic predictive principles underlying perception and action would still apply, but something new emerges when we send and receive actual language (which contains information).  With language, we begin to associate certain sounds and visual information with some kind of meaning or meaningful information.  Once we can do this, we can effectively share our thoughts with one another, or at least many aspects of our thoughts with one another.  This provides for an enormous evolutionary advantage as now we can communicate almost anything we want to one another, store it in external forms of memory (books, computers, etc.), and further analyze or manipulate the information for various purposes (accounting, inventory, science, mathematics, etc.).

By being able to predict certain causal outcomes through the use of language, we are effectively using the lower level predictions associated with perceiving and emitting language to satisfy higher level predictions related to more complex goals including those that extend far into the future.  Since the information that is sent and received amounts to testing or modifying our predictions of the world, we are effectively using language to share and modulate one brain’s set of predictions with that of another brain.  One important aspect of this process is that this information is inherently probabilistic which is why language often trips people up with ambiguities, nuances, multiple meanings behind words and other attributes of language that often lead to misunderstanding.  Wittgenstein is one of the more prominent philosophers who caught onto this property of language and its consequence on philosophical problems and how we see the world structured.  I think a lot of the problems Wittgenstein elaborated on with respect to language can be better accounted for by looking at language as dealing with probabilistic ontological/causal relations that serve some pragmatic purpose, with the meaning of any word or phrase as being best described by its use rather than some clear-cut definition.

This probabilistic attribute of language in terms of the meanings of words having fuzzy boundaries also tracks very well with the ontology that a brain currently has access to.  Our ontology, or what kinds of things we think exist in the world, are often categorized in various ways with some of the more concrete entities given names such as: “animals”, “plants”, “rocks”, “cats”, “cups”, “cars”, “cities”, etc.  But if I morph a wooden chair (say, by chipping away at parts of it with a chisel), eventually it will no longer be recognizable as a chair, and it may begin to look more like a table than a chair or like nothing other than an oddly shaped chunk of wood.  During this process, it may be difficult to point to the exact moment that it stopped being a chair and instead became a table or something else, and this would make sense if what we know to be a chair or table or what-have-you is nothing more than a probabilistic high-level prediction about certain causal relations.  If my brain perceives an object that produces too high of a prediction error based on the predictive model of what a “chair” is, then it will try another model (such as the predictive model pertaining to a “table”), potentially leading to models that are less and less specific until it is satisfied with recognizing the object as merely a “chunk of wood”.

From a PP lens, we can consider lower level predictions pertaining to more basic causes of sensory input (bright/dark regions, lines, colors, curves, edges, etc.) to form some basic ontological building blocks and when they are assembled into higher level predictions, the amount of integrated information increases.  This information integration process leads to condensed probabilities about increasingly complex causal relations, and this ends up reducing the dimensionality of the cause-effect space of the predicted phenomenon (where a set of separate cause-effect repertoires are combined into a smaller number of them).

You can see the advantage here by considering what the brain might do if it’s looking at a black cat sitting on a brown chair.  What if the brain were to look at this scene as merely a set of pixels on the retina that change over time, where there’s no expectations of any subset of pixels to change in ways that differ from any other subset?  This wouldn’t be very useful in predicting how the visual scene will change over time.  What if instead, the brain differentiates one subset of pixels (that correspond to what we call a cat) from all the rest of the pixels, and it does this in part by predicting proximity relations between neighboring pixels in the subset (so if some black pixels move from the right to the left visual field, then some number of neighboring black pixels are predicted to move with it)?

This latter method treats the subset of black-colored pixels as a separate object (as opposed to treating the entire visual scene as a single object), and doing this kind of differentiation in more and more complex ways leads to a well-defined object or concept, or a large number of them.  Associating sounds like “meow” with this subset of black-colored pixels, is just one example of yet another set of properties or predictions that further defines this perceived object as distinct from the rest of the perceptual scene.  Associating this object with a visual or auditory label such as “cat” finally links this ontological object with language.  As long as we agree on what is generally meant by the word “cat” (which we determine through its use), then we can share and modify the predictive models associated with such an object or concept, as we can do with any other successful instance of linguistic communication.

Language, Context, and Linguistic Relativism

However, it should be noted that as we get to more complex causal relations (more complex concepts/objects), we can no longer give these concepts a simple one word label and expect to communicate information about them nearly as easily as we could for the concept of a “cat”.  Think about concepts like “love” or “patriotism” or “transcendence” and realize how there’s many different ways that we use those terms and how they can mean all sorts of different things and so our meaning behind those words will be heavily conveyed to others by the context that they are used in.  And context in a PP framework could be described as simply the (expected) conjunction of multiple predictive models (multiple sets of causal relations) such as the conjunction of the predictive models pertaining to the concepts of food, pizza, and a desirable taste, and the word “love” which would imply a particular use of the word “love” as used in the phrase “I love pizza”.  This use of the word “love” is different than one which involves the conjunction of predictive models pertaining to the concepts of intimacy, sex, infatuation, and care, implied in a phrase like “I love my wife”.  In any case, conjunctions of predictive models can get complicated and this carries over to our stretching our language to its very limits.

Since we are immersed in language and since it is integral in our day-to-day lives, we also end up being conditioned to think linguistically in a number of ways.  For example, we often think with an interior monologue (e.g. “I am hungry and I want pizza for lunch”) even when we don’t plan on communicating this information to anyone else, so it’s not as if we’re simply rehearsing what we need to say before we say it.  I tend to think however that this linguistic thinking (thinking in our native language) is more or less a result of the fact that the causal relations that we think about have become so strongly associated with certain linguistic labels and propositions, that we sort of automatically think of the causal relations alongside the labels that we “hear” in our head.  This seems to be true even if the causal relations could be thought of without any linguistic labels, in principle at least.  We’ve simply learned to associate them so strongly to one another that in most cases separating the two is just not possible.

On the flip side, this tendency of language to associate itself with our thoughts, also puts certain barriers or restrictions on our thoughts.  If we are always preparing to share our thoughts through language, then we’re going to become somewhat entrained to think in ways that can be most easily expressed in a linguistic form.  So although language may simply be along for the ride with many non-linguistic aspects of thought, our tendency to use it may also structure our thinking and reasoning in large ways.  This would account for why people raised in different cultures with different languages see the world in different ways based on the structure of their language.  While linguistic determinism seems to have been ruled out (the strong version of the Sapir-Whorf hypothesis), there is still strong evidence to support linguistic relativism (the weak version of the Sapir-Whorf hypothesis), whereby one’s language effects their ontology and view of how the world is structured.

If language is so heavily used day-to-day then this phenomenon makes sense as viewed through a PP lens since we’re going to end up putting a high weight on the predictions that link ontology with language since these predictions have been demonstrated to us to be useful most of the time.  Minimal prediction error means that our Bayesian evidence is further supported and the higher the weight carried by these predictions, the more these predictions will restrict our overall thinking, including how our ontology is structured.

Moving on…

I think that these are but a few of the interesting relationships between language and ontology and how a PP framework helps to put it all together nicely, and I just haven’t seen this kind of explanatory power and parsimony in any other kind of conceptual framework about how the brain functions.  This bodes well for the framework and it’s becoming less and less surprising to see it being further supported over time with studies in neuroscience, cognition, psychology, and also those pertaining to pathologies of the brain, perceptual illusions, etc.  In the next post in this series, I’m going to talk about knowledge and how it can be seen through the lens of PP.

Predictive Processing: Unlocking the Mysteries of Mind & Body (Part I)

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I’ve been away from writing for a while because I’ve had some health problems relating to my neck.  A few weeks ago I had double-cervical-disc replacement surgery and so I’ve been unable to write and respond to comments and so forth for a little while.  I’m in the second week following my surgery now and have finally been able to get back to writing, which feels very good given that I’m unable to lift or resume martial arts for the time being.  Anyway, I want to resume my course of writing beginning with a post-series that pertains to Predictive Processing (PP) and the Bayesian brain.  I’ve written one post on this topic a little over a year ago (which can be found here) as I’ve become extremely interested in this topic for the last several years now.

The Predictive Processing (PP) theory of perception shows a lot of promise in terms of finding an overarching schema that can account for everything that the brain seems to do.  While its technical application is to account for the acts of perception and active inference in particular, I think it can be used more broadly to account for other descriptions of our mental life such as beliefs (and knowledge), desires, emotions, language, reasoning, cognitive biases, and even consciousness itself.  I want to explore some of these relationships as viewed through a PP lens more because I think it is the key framework needed to reconcile all of these aspects into one coherent picture, especially within the evolutionary context of an organism driven to survive.  Let’s begin this post-series by first looking at how PP relates to perception (including imagination), beliefs, emotions, and desires (and by extension, the actions resulting from particular desires).

Within a PP framework, beliefs can be best described as simply the set of particular predictions that the brain employs which encompass perception, desires, action, emotion, etc., and which are ultimately mediated and updated in order to reduce prediction errors based on incoming sensory evidence (and which approximates a Bayesian form of inference).  Perception then, which is constituted by a subset of all our beliefs (with many of them being implicit or unconscious beliefs), is more or less a form of controlled hallucination in the sense that what we consciously perceive is not the actual sensory evidence itself (not even after processing it), but rather our brain’s “best guess” of what the causes for the incoming sensory evidence are.

Desires can be best described as another subset of one’s beliefs, and a set of beliefs which has the special characteristic of being able to drive action or physical behavior in some way (whether driving internal bodily states, or external ones that move the body in various ways).  Finally, emotions can be thought of as predictions pertaining to the causes of internal bodily states and which may be driven or changed by changes in other beliefs (including changes in desires or perceptions).

When we believe something to be true or false, we are basically just modeling some kind of causal relationship (or its negation) which is able to manifest itself into a number of highly-weighted predicted perceptions and actions.  When we believe something to be likely true or likely false, the same principle applies but with a lower weight or precision on the predictions that directly corresponds to the degree of belief or disbelief (and so new sensory evidence will more easily sway such a belief).  And just like our perceptions, which are mediated by a number of low and high-level predictions pertaining to incoming sensory data, any prediction error that the brain encounters results in either updating the perceptual predictions to new ones that better reduce the prediction error and/or performing some physical action that reduces the prediction error (e.g. rotating your head, moving your eyes, reaching for an object, excreting hormones in your body, etc.).

In all these cases, we can describe the brain as having some set of Bayesian prior probabilities pertaining to the causes of incoming sensory data, and these priors changing over time in response to prediction errors arising from new incoming sensory evidence that fails to be “explained away” by the predictive models currently employed.  Strong beliefs are associated with high prior probabilities (highly-weighted predictions) and therefore need much more counterfactual sensory evidence to be overcome or modified than for weak beliefs which have relatively low priors (low-weighted predictions).

To illustrate some of these concepts, let’s consider a belief like “apples are a tasty food”.  This belief can be broken down into a number of lower level, highly-weighted predictions such as the prediction that eating a piece of what we call an “apple” will most likely result in qualia that accompany the perception of a particular satisfying taste, the lower level prediction that doing so will also cause my perception of hunger to change, and the higher level prediction that it will “give me energy” (with these latter two predictions stemming from the more basic category of “food” contained in the belief).  Another prediction or set of predictions is that these expectations will apply to not just one apple but a number of apples (different instances of one type of apple, or different types of apples altogether), and a host of other predictions.

These predictions may even result (in combination with other perceptions or beliefs) in an actual desire to eat an apple which, under a PP lens could be described as the highly weighted prediction of what it would feel like to find an apple, to reach for an apple, to grab it, to bite off a piece of it, to chew it, and to swallow it.  If I merely imagine doing such things, then the resulting predictions will necessarily carry such a small weight that they won’t be able to influence any actual motor actions (even if these imagined perceptions are able to influence other predictions that may eventually lead to some plan of action).  Imagined perceptions will also not carry enough weight (when my brain is functioning normally at least) to trick me into thinking that they are actual perceptions (by “actual”, I simply mean perceptions that correspond to incoming sensory data).  This low-weighting attribute of imagined perceptual predictions thus provides a viable way for us to have an imagination and to distinguish it from perceptions corresponding to incoming sensory data, and to distinguish it from predictions that directly cause bodily action.  On the other hand, predictions that are weighted highly enough (among other factors) will be uniquely capable of affecting our perception of the real world and/or instantiating action.

This latter case of desire and action shows how the PP model takes the organism to be an embodied prediction machine that is directly influencing and being influenced by the world that its body interacts with, with the ultimate goal of reducing any prediction error encountered (which can be thought of as maximizing Bayesian evidence).  In this particular example, the highly-weighted prediction of eating an apple is simply another way of describing a desire to eat an apple, which produces some degree of prediction error until the proper actions have taken place in order to reduce said error.  The only two ways of reducing this prediction error are to change the desire (or eliminate it) to one that no longer involves eating an apple, and/or to perform bodily actions that result in actually eating an apple.

Perhaps if I realize that I don’t have any apples in my house, but I realize that I do have bananas, then my desire will change to one that predicts my eating a banana instead.  Another way of saying this is that my higher-weighted prediction of satisfying hunger supersedes my prediction of eating an apple specifically, thus one desire is able to supersede another.  However, if the prediction weight associated with my desire to eat an apple is high enough, it may mean that my predictions will motivate me enough to avoid eating the banana, and instead to predict what it is like to walk out of my house, go to the store, and actually get an apple (and therefore, to actually do so).  Furthermore, it may motivate me to predict actions that lead me to earn the money such that I can purchase the apple (if I don’t already have the money to do so).  To do this, I would be employing a number of predictions having to do with performing actions that lead to me obtaining money, using money to purchase goods, etc.

This is but a taste of what PP has to offer, and how we can look at basic concepts within folk psychology, cognitive science, and theories of mind in a new light.  Associated with all of these beliefs, desires, emotions, and actions (which again, are simply different kinds of predictions under this framework), is a number of elements pertaining to ontology (i.e. what kinds of things we think exist in the world) and pertaining to language as well, and I’d like to explore this relationship in my next post.  This link can be found here.

“The Brothers Karamazov” – A Moral & Philosophical Critique (Part III)

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In the first two posts that I wrote in this series (part I and part II) concerning some concepts and themes mentioned in Dostoyevksy’s The Brothers Karamazov, I talked about moral realism and how it pertains to theism and atheism (and the character Ivan’s own views), and I also talked about moral responsibility and free will to some degree (and how this related to the interplay between Ivan and Smerdyakov).  In this post, I’m going to look at the concept of moral conscience and intuition, and how they apply to Ivan’s perspective and his experiencing an ongoing hallucination of a demonic apparition.  This demonic apparition only begins to haunt Ivan after hearing that his influence on his brother Smerdyakov led him to murder their father Fyodor.  The demon continues to torment Ivan until just before his other brother Alyosha informs him that Smerdyakov has committed suicide.  Then I’ll conclude with some discussion on the concept of moral desert (justice).

It seems pretty clear that the demonic apparition that appears to Ivan is a psychosomatic hallucination brought about as a manifestation of Ivan’s overwhelming guilt for what his brother has done, since he feels that he bears at least some of the responsibility for his brothers actions.  We learn earlier in the story that Zosima, a wise elder living at a monastery who acts as a mentor and teacher to Alyosha, had explained to Ivan that everyone bears at least some responsibility for the actions of everyone around them because human causality is so heavily intertwined with one person’s actions having a number of complicated effects on the actions of everyone else.  Despite Ivan’s strong initial reservations against this line of reasoning, he seems to have finally accepted that Zosima was right — hence him suffering a nervous breakdown as a result of realizing this.

Obviously Ivan’s moral conscience seems to be driving this turn of events and this is the case whether or not Ivan explicitly believes that morality is real.  And so we can see that despite Ivan’s moral skepticism, his moral intuitions and/or his newly accepted moral dispositions as per Zosima, have led him to his current state of despair.  Similarly, Ivan’s views on the problem of evil — whereby the vast amount of suffering in the world either refutes the existence of God, or shows that this God (if he does exist) must be a moral monster — betray even more of Ivan’s moral views with respect to how he wants the world to be.  His wanting the world to have less suffering in it, along with his wishing that his brother had not committed murder (let alone as a result of his influence on his brother), illustrates a number of moral “oughts” that Ivan subscribes to.  And whether they’re simply based on his moral intuitions or also rational moral reflection, they illustrate the deeply rooted psychological aspects of morality that are an inescapable facet of the human condition.

This situation also helps to explain some of the underlying motivations behind my own reversion back toward some form of moral realism, after becoming an atheist myself, initially catalyzed by my own moral intuitions and then later solidified and justified by rational moral reflection on objective facts pertaining to human psychology and other factors.  Now it should be said that moral intuitions on their own are only a generally useful heuristic as they are often misguiding (and incorrect) which is why it is imperative that they are checked by a rational assessment of the facts at hand.  But, nevertheless, they help to illustrate how good and evil can be said to be real (in at least some sense), even to someone like Ivan that doesn’t think they have an objective foundation.  They may not be conceptions of good and evil as described in many religions, with supernatural baggage attached, but they are real nonetheless.

Another interesting point worth noting is in regard to Zosima’s discussion about mutual moral responsibility.  While I already discussed moral responsibility in the last post along with its relation to free will, there’s something rather paradoxical about Dostoyevsky’s reasoning as expressed through Zosima that I found quite interesting.  Zosima talks about how love and forgiveness are necessary because everyone’s actions are intertwined with everyone else’s and therefore everyone bears some responsibility for the sins of others.  This idea of shared responsibility is abhorrent to those in the story that doubt God and the Christian religion (such as Ivan), who only want to be responsible for their own actions, but the complex intertwined causal chain that Zosima speaks of is the same causal chain that many determinists invoke to explain our lack of libertarian free will and how we can’t be held responsible in a causa sui manner for our actions.

Thus, if someone dies and there is in fact an afterlife, by Zosima’s own reasoning that person should not be judged as an individual solely responsible for their actions either.  That person should instead receive unconditional love and forgiveness and be redeemed rather than punished.  But this idea is anathema to standard Christian theology where one is supposed to be judged and given eternal paradise or eternal torment (with vastly disproportionate consequences given the finite degree of one’s actions).  It’s no surprise that Zosima isn’t looked upon as a model clergyman by some of his fellow monks in the monastery because his emphatic preaching about love and forgiveness undermines the typical heavy-handed judgemental aspects of God within Christianity.  But in any case, if God exists and understood that people were products of their genes and their environment which is causally interconnected with everyone else’s (i.e. libertarian free will is logically impossible), then a loving God would grant everyone forgiveness after death and grant them eternal paradise based on that understanding.  And oddly enough, this also undermines Ivan’s own reasoning that good and evil can only exist with an afterlife that undergoes judgement, because forgiveness and eternal paradise should be granted to everyone in the afterlife (by a truly loving God) if Zosima’s reasoning was taken to it’s logical conclusions.  So not only does Zosima’s reasoning seem to undermine the justification for unequal treatment of souls in the afterlife, but it also undermines the Christian conception of free will to boot (which is logically impossible regardless of Zosima’s reasoning).

And this brings me to the concept of moral desert.  In some ways I agree with Zosima, at least in the sense that love (or more specifically compassion) and forgiveness are extremely important in proper moral reasoning. And once one realizes the logical impossibility of libertarian free will, this should only encourage one’s use of love and forgiveness in the sense that people should never be trying to punish a wrongdoer (or hope for their punishment) for the sake of retributive justice or vengeance.  Rather, people should only punish (or hope that one is punished) as much as is necessary to compensate the victim as best as the circumstances allow and (more importantly) to rehabilitate the wrongdoer by reprogramming them through behavioral conditioning.  Anything above and beyond this is excessive, malicious, and immoral.  Similarly, a loving God (if one existed) would never punish anyone in the afterlife beyond what is needed to rehabilitate them (and it would seem that no punishment at all should really be needed if this God had the power to accomplish these feats on immaterial souls using magic), and if this God had no magic to accomplish this, then at the very least, it would still mean that there should never by any eternal punishments, since punishing someone forever (let alone torturing them forever), not only illustrates that there is no goal to rehabilitate the wrongdoer, but also that this God is beyond psychopathic and malevolent.  Again, think of Zosima’s reasoning as it applies here.

Looking back at the story with Smerdyakov, why does the demonic apparition disappear from Ivan right around the time that he learns that Smerdyakov killed himself?  It could be because Ivan thinks that Smerdyakov has gotten what he deserved, and that he’s no longer roaming free (so to speak) after his heinous act of murder.  And it could also be because Ivan seemed sure at that point that he would confess to the murder (or at least motivating Smerdyakov to do it).  But if either of these notions are true, then once again Ivan has betrayed yet another moral disposition of his, that murder is morally wrong.  It may also imply that Ivan, deep down, may in fact believe in an afterlife, and that Smerdyakov will now be judged for his actions.

It no doubt feels good to a lot of people when they see someone that has wronged another, getting punished for their bad deeds.  The feeling of justice and even vengeance can be so emotionally powerful, especially if the wrongdoer took the life of someone that you or someone else loved very much.  It’s a common feeling to want that criminal to suffer, perhaps to rot in jail until they die, perhaps to be tortured, or what-have-you.  And these intuitions illustrate why so many religious beliefs surrounding judgment in the afterlife share many of these common elements.  People invented these religious beliefs (whether unconsciously or not) because it makes them feel better about wrongdoers that may otherwise die without having been judged for their actions.  After all, when is justice going to be served?  It is also a motivating factor for a lot of people to keep their behaviors in check (as per Ivan’s rationale regarding an afterlife requirement in order for good and evil to be meaningful to people).  Even though I don’t think that this particular motivation is necessary (and therefore Ivan’s argument is incorrect) — due to other motivating forces such as the level of fulfillment and personal self-worth in one’s life, gained through living a life of moral virtue, or the lack thereof by those that fail to live virtuously — it is still a motivation that exists with many people and strongly intersects with the concept of moral desert.  Due to its pervasiveness in our intuitions and how we perceive other human beings and its importance in moral theory in general, people should spend a lot more time critically reflecting on this concept.

In the next part of this post series, I’m going to talk about the conflict between faith and doubt, perhaps the most ubiquitous theme found in The Brothers Karamazov, and how it ties all of these other concepts together.

“The Brothers Karamazov” – A Moral & Philosophical Critique (Part II)

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In my last post in this series, concerning Dostoyevsky’s The Brothers Karamazov, I talked about the concept of good and evil and the character Ivan’s personal atheistic perception that they are contingent on God existing (or at least an afterlife of eternal reward or punishment).  While there may even be a decent percentage of atheists that share this view (objective morality being contingent on God’s existence), I briefly explained my own views (being an atheist myself) which differs from Ivan’s in that I am a moral realist and believe that morality is objective independent of any gods or immortal souls existing.  I believe that moral facts exist (and science is the best way to find them), that morality is ultimately grounded on objective facts pertaining to human psychology, biology, sociology, neurology, and other facts about human beings, and thus that good and evil do exist in at least some sense.

In this post, I’m going to talk about Ivan’s influence on his half-brother, Smerdyakov, who ends up confessing to Ivan that he murdered their father Fyodor Pavlovich, as a result of Ivan’s philosophical influence on him.  In particular, Smerdyakov implicates Ivan as at least partially responsible for his own murderous behavior since Ivan successfully convinced him that evil wasn’t possible in a world without a God.  Ivan ends up becoming consumed with guilt, basically suffers a nervous breakdown, and then is incessantly taunted by a demonic apparition.  The hallucinations continue up until the moment Ivan comes to find out, from his very religious brother Alyosha, that Smerdyakov has hung himself.  This scene highlights a number of important topics beyond the moral realism I discussed in the first post, such as moral responsibility, free will, and even moral desert (I’ll discuss this last topic in my next post).

As I mentioned before, beyond the fact that we do not need a god to ground moral values, we also don’t need a god or an afterlife to motivate us to behave morally either.  By cultivating moral virtues such as compassion, honesty, and reasonableness, and analyzing a situation using a rational assessment of as many facts as are currently accessible, we can maximize our personal satisfaction and thus our chances of living a fulfilling life.  Behavioral causal factors that support this goal are “good” and those that detract from it are “evil”.  Aside from these labels though, we actually experience a more or less pleasing life depending on our behaviors and therefore we do have real-time motivations for behaving morally (such as acting in ways that conform to various cultivated virtues).  Aristotle claimed this more than 2000 years ago and moral psychology has been confirming it time and time again.

Since we have evolved as a particular social species with a particular psychology, not only do we have particular behaviors that best accomplish a fulfilling life, but there are also various behavioral conditioning algorithms and punishment/reward systems that are best at modifying our behavior.  And this brings me to Smerdyakov.  By listening to Ivan and ultimately becoming convinced by Ivan’s philosophical arguments, he seems to have been conditioned out of his previous views on moral responsibility.  In particular, he ended up adopting the belief that if God does not exist, then anything is permissible.  Since he also rejected a belief in God, he therefore thought he could do whatever he wanted.

One thing this turn of events highlights is that there are a number of different factors that influence people’s behaviors and that lead to their being reasoned into doing (or not doing) all sorts of things.  As Voltaire once said “Those who can make you believe absurdities can also make you commit atrocities.  And I think what Ivan told Smerdyakov was in fact absurd — although it was a belief that I once held as well not long after becoming an atheist.  For it is quite obviously absurd that anything is permissible without a God existing for at least two types of reasons: pragmatic considerations and moral considerations (with the former overlapping with the latter).  Pragmatic reasons include things like not wanting to be fined, incarcerated, or even executed by a criminal justice system that operates to minimize illegal behaviors.  It includes not wanting to be ostracized from your circle of friends, your social groups, or your community (and risking the loss of beneficial reciprocity, safety nets, etc.).  Moral reasons include everything that detracts from your overall psychological well-being, the very thing that is needed to live a maximally fulfilling life given one’s circumstances.  Behaving in ways that degrade your sense of inner worth, your integrity, self-esteem, and that diminish a good conscience, is going to make you feel miserable compared to behaving in ways that positively impact these fundamental psychological goals.

Furthermore, this part of the story illustrates that we have a moral responsibility not only to ourselves and our own behavior, but also in terms of how we influence the behavior of those around us, based on what we say, how we treat them, and more.  This also reinforces the importance of social contract theory and how it pertains to moral behavior.  If we follow simple behavioral heuristics like the Golden Rule and mutual reciprocity, then we can work together to obtain and secure common social goods such as various rights, equality, environmental sustainability, democratic legislation (ideally based on open moral deliberation), and various social safety nets.  We also can punish those that violate the social contract, as we already do with the criminal justice system and various kinds of social ostracization.  While our system of checks is far from perfect, having some system that serves such a purpose is necessary because not everybody behaves in ways that are ultimately beneficial to themselves nor everyone else around them.  People need to be conditioned to behave in ways that are more conducive to their own well being and that of others, and if all reasonable efforts to achieve that fails, they may simply need to be quarantined through incarceration (for example psychopaths or other violent criminals that society needs to be protected from, and that aren’t responding to rehabilitation efforts).

In any case, we do have a responsibility to others and that means we need to be careful what we say, such as the case with Ivan and his brother.  And this includes how we talk about concepts like free will, moral responsibility, and moral desert (justice).  If we tell people that all of their behaviors are determined and therefore don’t matter, that’s not a good way to get people to behave in ways that are good for them or for others.  Nor is telling them that because a God doesn’t exist, that their actions don’t matter.  In the case of deterministic nihilism, it’s a way to get people to lose much if not all of their motivation to put forward effort in achieving useful goals.  And both deterministic and atheistic moral nihilism are dangerous ideas that can get some people to commit heinous crimes such as mass shootings (or murdering their own father as Smerdyakov did), because they simply cause people to think that all behaviors are on equal footing in any way that matters.  And quite frankly, those nihilistic ideas are not only dangerous but also absurd.

While I’ve written a bit on free will in the past, my views have become more refined over the years, and my overall attitude towards the issue has been co-evolving alongside my views on morality.  The main crux of the free will issue is that libertarian free will is logically impossible because our actions are never free from both determinism and indeterminism (randomness) since one or the other must underlie how our universe operates (depending on which interpretation of Quantum Mechanics is correct).  Neither option from this logical dichotomy gives us “the freedom to have chosen to behave differently given the same initial conditions in a non-random way”.  Therefore free will in this sense is logically impossible.  However, this does not mean that our behavior isn’t operating under some sets of rules and patterns that we can discover and modify.  That is to say, we can effectively reprogram many of our behavioral tendencies using various forms of conditioning through punishment/reward systems.  These are the same systems we use to teach children how to behave and to rehabilitate criminals.

The key thing to note here is that we need to acknowledge that even if we don’t have libertarian free will, we still have a form of “free will” that matters (as philosophers like Daniel Dennett have said numerous times) whereby we have the ability to be programmed and reprogrammed in certain ways, thus allowing us to take responsibility for our actions and design ways to modify future actions as needed.  We have more degrees of freedom than a person who is insane for example, or a child, or a dog, and these degrees of freedom or autonomy — the flexibility we have in our decision-making algorithms — can be used as a rough guideline for determining how “morally responsible” a person is for their actions.  That is to say, the more easily a person can be conditioned out of a particular behavior, and the more rational decision making processes are involved in governing that behavior, the more “free will” this person has in a sense that applies to a criminal justice system and that applies to most of our everyday lives.

In the end, it doesn’t matter whether someone thinks that their behavior doesn’t matter because there’s no God, or because they have no libertarian free will.  What needs to be pointed out is the fact that we are able to behave in ways (or be conditioned to behave in ways) that lead to more happiness, more satisfaction and more fulfilling lives.  And we are able to behave in ways that detract from this goal.  So which behaviors should we aim for?  I think the answer is obvious.  And we also need to realize that as a part of our behavioral patterns, we need to realize that ideas have consequences on others and their subsequent behaviors.  So we need to be careful about what ideas we choose to spread and to make sure that they are put into a fuller context.  If a person hasn’t given some critical reflection about the consequences that may ensue from spreading their ideas to others, especially to others that may misunderstand it, then they need to keep those ideas to themselves until they’ve reflected on them more.  And this is something that I’ve discovered and applied for myself as well, as I was once far less careful about this than I am now.  In the next post, I’m going to talk about the concept of moral desert and how it pertains to free will.  This will be relevant to the scene described above regarding Ivan’s demonic apparition that haunts him as a result of his guilt over Smerdyakov’s murder of their father, as well as why the demonic apparition disappeared once Ivan heard that Smerdyakov had taken his own life.

“The Brothers Karamazov” – A Moral & Philosophical Critique (Part I)

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I wanted to write some thoughts on Dostoyevsky’s The Brothers Karamazov, and I may end up writing this in several parts.  I’m interested in some of the themes that Dostoevsky develops, in particular, those pertaining to morality, moral responsibility, free will, moral desert, and their connection to theism and atheism.  Since I’m not going to go over the novel in great detail, for those not already familiar with this story, please at least read the plot overview (here’s a good link for that) before pressing on.

One of the main characters in this story, Ivan, is an atheist, as I am (though our philosophies differ markedly as you’ll come to find out as you read on).  In his interactions and conversation with his brother Alyosha, a very religious man, various moral concepts are brought up including the dichotomy of good and evil, arguments against the existence of God (at least, against the existence of a loving God) such as the well-known Problem of Evil, and other ethical and religious quandaries.  I wanted to first talk about Ivan’s insistence that good and evil cannot exist without God, and since Ivan’s character doesn’t believe that God exists, he comes to the conclusion that good and evil do not exist either.  Although I’m an atheist, I disagree with Ivan’s views here and will expand on why in a moment.

I’ve written a bit on my blog, about various arguments against the existence of God that I’ve come across over the years, some of which that I’ve formulated on my own after much reflection – and that were at least partially influenced by my former religious views as a born-again Protestant Christian.  Perhaps ironically, it wasn’t until after I became an atheist that I began to delve much deeper into moral theory, and also into philosophy generally (though the latter is less surprising).  My views on morality have evolved in extremely significant ways since my early adult years.  For example, back when I was a Christian I was a moral objectivist/realist, believing that morals were indeed objective but only in the sense that they depended on what God believed to be right and wrong (even if these divine rules changed over time or seemed to contradict my own moral intuitions and analyses, such as stoning homosexuals to death).  Thus, I subscribed to some form of Divine Command Theory (or DCT).  After becoming an atheist, much like Ivan, I became a moral relativist (but only temporarily – keep reading), believing as the character Ivan did, that good and evil couldn’t exist due to their resting on a fictitious or at least non-demonstrable supernatural theological foundation and/or (perhaps unlike Ivan believed) that good and evil may exist but only in the sense that they were nothing more than cultural norms that were all equally valid.

Since then, I’ve become a moral realist once again (as I was when I was a Christian), after putting the philosophy of Ivan to the test (so to speak).  I realized that I could no longer justify the belief that any cultural moral norm had as equal of a claim to being true as any other cultural norm.  There were simply too many examples of moral prescriptions in various cultures and religions that couldn’t be justified.  Then I realized that many of the world’s cultural moral norms, though certainly not all of them, were largely universal (such as prohibitions against, at least certain forms of, stealing, killing, and others) which suggested a common human psychological component underlying many of them.

I also realized that as an atheist, much as Nietzsche realized, I now had to ground my own moral views on something that didn’t rely on Divine Command Theory, gods, Christian traditions, or any other foundation that I found to be invalid, illogical, unreasonable, unjustified, or not sufficiently demonstrated to be true.  And I had to do this if I was to find a way out of moral relativism, which simply didn’t sit well with me as it didn’t seem to be coherent with the bulk of human psychology and the more or less universal goals that humans strive to achieve in their lives.  It was ultimately the objective facts pertaining to human psychology that allowed me to resubscribe to an objectivist/realist morality — and now my views of morality were no longer contingent on merely the whim or dictates of some authoritarian god (thus bypassing the Euthyphro dilemma), but rather were contingent on objective facts about human beings, what makes us happy and fulfilled and what doesn’t (where these facts often disagree with moral prescriptions stemming from various religions and Divine-Command-Theory).

After dabbling with the teachings of various philosophers such as Aristotle, Kant, Mill, Rawls, Foot, and others, I came to accept a view of morality that was indeed coherent, sensible, sufficiently motivating to follow (which is a must), and which subsumed all the major moral theories into one framework (and which therefore had the best claim to being true since it was compatible with all of them –  virtue ethics, deontology, and consequentialism).   Now I’ve come to accept what can be described as a Goal Theory of Ethics, whereby morality is defined as “that which one ought to do above all else – when rational and maximally informed based on reason and evidence – in order to increase one’s personal life fulfillment and overall level of preference satisfaction”.  One could classify this as a subset of desire utilitarianism, but readers must be warned that this is NOT to be confused with traditional formulations of utilitarianism – such as those explicitly stated by J.S. Mill, Peter Singer, etc., as they are rife with problems resulting from not taking ALL consequences into account (such as consequences pertaining to one’s own character and how they see themselves as a person, as per the wisdom of Aristotle and Kant).

So how can good and evil exist without some God(s) existing?  That is to say, if a God doesn’t exist, how can it not be the case that “anything is permissible”?  Well, the short answer is – because of human psychology (and also social contract theory).

When people talk about behaving morally, what they really mean (when we peel back all the layers of cultural and religious rhetoric, mythology, narrative, etc.) is behaving in a way that maximizes our personal satisfaction – specifically our sense of life fulfillment.  Ask a Christian, or a Muslim, or a Humanist, why ought they behave in some particular way, and it all can be shown to break down to some form of human happiness or preference satisfaction for life fulfillment (not some hedonistic form of happiness).  They may say to behave morally “because then you can get into heaven, or avoid hell”, or “because it pleases God”, or what-have-you.  When you ask why THOSE reasons are important, it ultimately leads to “because it maximizes your chance of living a fulfilled life” (whether in this life or in the next, for those that believe in an afterlife).  I don’t believe in any afterlife because there’s no good evidence or reason to have such a belief, so for me the life that is most important is the one life we are given here on earth – which therefore must be cherished and not given any secondary priority to a hypothetical life that may or may not be granted after death.

But regardless, whether you believe in an afterlife (as Alyosha does) or not (as in Ivan’s case), it is still about maximizing a specific form of happiness and fulfillment.  However, another place where Ivan seems to go wrong in his thinking is his conclusion that people only behave morally based on what they believe will happen to them in an afterlife.  And therefore, if there is no afterlife (immortal souls), then there is no reason to be moral.  The fact of the matter is though, in general, much of what we tend to call moral behavior actually produces positive effects on the quality of our lives now, as we live them.  People that behave immorally are generally not going to live “the good life” or achieve what Aristotle called eudaimonia.  On the other hand, if people actually cultivate virtues of compassion, honesty, and reasonableness, they will simply live more fulfilling lives.  And people that don’t do this or simply follow their immediate epicurean or selfish impulses will most certainly not live a fulfilling life.  So there is actually a naturalistic motivating force to behave morally, regardless of any afterlife.  Ivan simply overlooked this (and by extension, possibly Dostoyevsky as well), likely because most people brought up in Christianized cultures often focus on the afterlife as being the bearer of ultimate justice and therefore the ultimate motivator for behaving as they do.

In any case, the next obvious question to ask is what ways of living best accomplish this goal of life fulfillment?  This is an empirical question which means science can in principle discover the answer, and is the only reliable (or at least the most reliable) way of arriving at such answers.  While there is as of yet no explicit “science of morality”, various branches of science such as psychology, sociology, anthropology, and neuroscience, are discovering moral facts (or at least reasonable approximations of these facts, given what data we have obtained thus far).  Unless we as a society choose to formulate a science of morality — a laborious research project indeed — we will have to live with the best approximations to moral facts that are at our disposal as per the findings in psychology, sociology, neuroscience, etc.

So even if we don’t yet know with certainty what one ought to do in any and all particular circumstances (no situational ethical certainties), many scientific findings have increased our confidence in having discovered at least some of those moral facts or approximations of those facts (such as that slavery is morally wrong, because it doesn’t maximize the overall life satisfaction of the slaveholder, especially if he/she were to analyze the situation rationally with as many facts as are pragmatically at their disposal).  And to make use of some major philosophical fruits cultivated from the works of Hobbes, Locke, Rousseau, Hume, and Rawls (among many others), we have the benefits of Social Contract Theory to take into consideration.  In short, societies maximize the happiness and flourishing of the citizens contained therein by making use of a social contract – a system of rules and mutual expectations that ought to be enforced in order to accomplish that societal goal (and which ought to be designed in a fair manner, behind a Rawlsian veil of ignorance, or what he deemed the “original position”).  And therefore, to maximize one’s own chance of living a fulfilling life, one will most likely need to endorse some form of social contract theory that grants people rights, equality, protection, and so forth.

In summary, good and evil do exist despite there being no God because human psychology is particular to our species and our biology, it has a finite range of inputs and outputs, and therefore there are some sets of behaviors that will work better than others to maximize our happiness and overall life satisfaction given the situational circumstances that we find our lives embedded in.  What we call “good” and “evil” are simply the behaviors and causal events that “add to” or “detract from” our goal of living a fulfilling life.  The biggest source of disagreement among the various moral systems in the world (whether religiously motivated or not), are the different sets of “facts” that people subscribe to (some beliefs being based on sound reason and evidence whereas others are based on irrational faith, dogma, or emotions) and whether or not people are analyzing the actual facts in a rational manner.  A person may think they know what will maximize their chances of living a fulfilling life when in fact (much like with the heroin addict that can’t wait to get their next fix) they are wrong about the facts and if they only knew so and acted rationally, would do what they actually ought to do instead.

In my next post in this series, I’ll examine Ivan’s views on free will and moral responsibility, and how it relates to the unintended consequence of the actions of his half-brother Smerdyakov (who murders their father, Fyodor Pavlovich, as a result of Ivan’s influence on his moral views).