Surfing uncertainty pdf free download

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Need an account? Click here to sign up. Download Free PDF. Daniel Williams. A short summary of this paper. Craik died at the age of 31 before he could develop this idea in any detail. If the central message of Clark is along the right lines, however, it turns out he was extremely prescient. When recapitulated up the hierar- chical structure of the neocortex, this process of prediction error minimization is supposed to account for - well, just about everything.

Drawing mostly on the fascinating work of Karl Friston and his group of collaborators, Clark advances the minimization of prediction error as the fundamental operating principle of cognition. On first reading this can seem absurd. A single principle underlying all neuronal operations? Biological systems seem to exhibit a mishmash of operations and func- tions, woven together in a way that reflects what happened to be adaptive in their idiosyncratic ancestral environments and the particularities of their developmental context.

And prediction? What could the minimization of prediction error have to do with motivation, action, sequential reasoning, language-use, long-term planning, social coordination, and so on?

Clark marshals a huge body of suggestive evidence in its favour, carefully identifies its many theoretical virtues, and points the reader towards a large and growing body of its applications in cognitive neuroscience, computational psychiatry, robotics, and more. The result is a truly impressive book: extremely ambitious, beautifully written, admirably clear, and -in most cases, at least - compelling. No review could do justice to the sheer range of material that Clark covers.

Instead, I offer a skeletal outline of the core structure and contents of the book, before raising a general worry. How do they accomplish this miraculous feat?

According to PP, by harnessing this sensory input as ongoing feedback to internally generated top-down predictions. In an inversion of traditional wisdom and commonsense, the only infor- mation that then propagates up through the perceptual systems is prediction error, the discrepancy between the sensory data predicted and received.

Crucially, this process requires hierarchical representation of the sort familiar from deep learning models in contemporary machine learning, extracting hidden causes latent variables at multiple levels of spatial and temporal scale.

In practice, this means that the cortical model that underlies perception is decomposed into a hierarchy of levels trafficking in representations at different levels of abstraction, with each level attempting to predict activity at the level below.

In this way brains identify the set of interacting worldly causes that best explains their evolving sensory inputs by striving to minimize the hierarchically distributed error signals in their predictions of these inputs. Despite the attractions of this picture, I wish Clark had gone a bit deeper into how it is supposed to work. For example, he repeatedly states e. Fodor and Pylyshyn is not with the ability of non-symbolic architectures to represent structure as such, but with their ability to flexibly recombine the elements implicated in such structured representations in systematic and productive ways.

For example, on the assumption that priors are given by predictions, are likelihoods also explicitly encoded? When does the brain redistribute probabilities over predictive hypotheses perception and when does it update the hypothesis space itself learning?

Chapter 2 turns to the role of precision-weighting and attention in PP. Precision- weighting is the process by which the brain evaluates its sensory uncertainty, assigning differential weight to prediction errors throughout the perceptual hierarchy in accor- dance with their estimated reliability.

Following others e. Hohwy , Clark contends that this process of precision-weighting realises the functional role of attention, and it plays a pivotal role throughout the book. Be- cause predictive brains are fundamentally in the business of endogenously constructing virtual versions of the sensory data they receive from the environment, perception and 3 Clark seems to acknowledge this in a footnote , fn. Williams D. Following Friston, Clark argues that action is just a different means of minimizing prediction error: instead of updating top- down predictions to bring them into alignment with the incoming signal perception , action arises as a means of bringing sensory input into alignment with top-down predictions.

Motor control, for example, is a matter of first predicting the proprioceptive sensory inputs implied by a desired action, and then activating classical reflex arcs to minimize the resultant error signals conditioned by the absence of that action.

Where do such desires or goals come from? Clark suggests that they are just further, higher- level predictions. Greater elaboration on this point would have been helpful, however.

In the conceptual framework of folk psychology, at least, what one wants and what one expects to do are orthogonal categories that often come apart. With the core account of learning, perception, attention, and action on the table, Clark turns to elaborations and applications of the basic story to other phenomena.

Chapter 5 deals among many other fascinating topics with how predictive minds can harness their generative machinery for the purposes of social coordination, and how precision-weighting can reconfigure the distribution of cognitive influence within the brain in flexible ways.

This made me wonder why Clark worries so much about the words he uses throughout the book. And so on. Chapter 7 turns to the vexed issue of consciousness from the perspective of PP, which Clark addresses both through fascinating models of various psychopathologies and through an exploration of interoceptive prediction in the construction of emotional experience. The final two chapters of the book then focus on embodied cognition and human uniqueness within the context of PP.

Chapter 8 argues that the apparent tension between PP and work in embodied cognition is illusory, and that the former can - indeed must - straightforwardly assim- ilate the core theoretical lessons of the latter. Chapter 9 is a fascinating but heavily speculative answer to a worry one might have with PP: if the theory correctly characterises at least the neurocomputational archi- tecture of the mammalian cortex, what accounts for the seemingly novel kinds of cognition exhibited by human beings?

In an enthralling gesture towards future research, Clark identifies numerous ways in which predictive brains might be augmented and transformed in the idiosyncratic environment of shared cultural practices and flexible symbol systems characteristic of human life. This skeletal overview should give some indication of the ambition of the book: from the beginnings of a brain attempting to learn about the world from its sensory effects, Clark traverses the whole spectrum of psychological phenomena that make up the mind, in each case showcasing how prediction-based mechanisms offer illuminat- ing and often surprising explanations.

The upshot is an exhilarating reading experience, and anyone interested in cognitive science - indeed, anyone interested in the mind - should buy a copy of the book immediately.

Despite this, I came away with a nagging concern: it is not always clear which theory Clark is defending. This seems disingenuous, however, for two reasons.