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Direct perception and the predictive mind


Predictive approaches to the mind claim that perception, cognition, and action can be understood in terms of a single framework: a hierarchy of Bayesian models employing the computational strategy of predictive coding. Proponents of this view disagree, however, over the extent to which perception is direct on the predictive approach. I argue that we can resolve these disagreements by identifying three distinct notions of perceptual directness: psychological, metaphysical, and epistemological. I propose that perception is plausibly construed as psychologically indirect on the predictive approach, in the sense of being constructivist or inferential. It would be wrong to conclude from this, however, that perception is therefore indirect in a metaphysical or epistemological sense on the predictive approach. In the metaphysical case, claims about the inferential properties of constructivist perceptual mechanisms are consistent with both direct and indirect solutions to the metaphysical problem of perception (e.g. naïve realism, representationalism, sense datum theory). In the epistemological case, claims about the inferential properties of constructivist perceptual mechanisms are consistent with both direct and indirect approaches to the justification of perceptual belief. In this paper, I demonstrate how proponents of the predictive approach have conflated these distinct notions of perceptual directness and indirectness, and I propose alternative strategies for developing the philosophical consequences of the approach.

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  1. For a representative sample, see Clark (2012, 2013a, b, 2016), Hohwy (2007, 2013, 2014), Shand (2014), Macpherson (2015), Gladziejewski (2016) and Burr and Jones (2016).

  2. For neuroscientific uses of predictive coding, see e.g. Friston (2002) and Friston and Kiebel (2009).

  3. For more on empirical Bayes and the predictive approach, see Hohwy (2013, 33) and Clark (2013b, 185).

  4. Throughout this paper I will be following proponents of the predictive approach in focusing solely on visual perception.

  5. It is common to find computational models of visual perception such as Marr’s (1982) account described as inferential, despite the fact that the perceptual states being processed are not explicit representations, but rather embodied or hard-wired within the visual system. Pylyshyn denies that such approaches are genuinely inferential, are suggests that these processes are “best viewed as the wired-in regularities such as any mechanism must possess” (Pylyshyn 2006, 38–39, n. 8).

  6. Orlandi (2014) argues that predictive approaches to perception are not genuinely constructivist theories because the bulk of the information processing is top-down rather than bottom-up. I take it, however, that construction processes in general are not essentially ‘bottom-up’: suspensions bridges are a case in point. I maintain that predictive approaches to perception are constructivist because they are inferential, and indirect as a result.

  7. Orlandi (2014, 89) argues that the tools of Bayesian analysis can describe and predict the behaviour of non-inferential mechanisms, and shows how an instrumentalist understanding of Bayesian inference can support the predictive approach as an ecological theory of perception.

  8. Kiefer (2017) outlines and defends a model of inference according to which neural networks perform statistical inference according to Bayes Rule. See also Gładziejewski (2016), who argues that the predictive approach posits genuinely representational structures.

  9. I don’t consider adverbialism in what follows, on the grounds that proponents of the predictive approach have made no claims about the relation between their theory and adverbialism.

  10. To say that an experience fundamentally consists in something is to say that it is that in virtue of which it has all the other psychological properties it does. See Logue (2011) for elaboration.

  11. I am grateful to Anil Gomes for discussion of the role played by transcendental arguments in philosophy of perception.

  12. For a spectrum of relevant views on naturalistic metaphysics, see Ross et al. (2013).

  13. See Schrenk (2005) for a discussion of the different ways that natural necessity and laws of nature can relate.

  14. For an exploration of the relation between natural kinds and nomological necessity, see Collier (1996).

  15. There’s a further concern for naturalistic metaphysics regarding the theoretical virtues of the predictive approach. Naturalistic conclusions about metaphysical possibilities should be guided by the appropriate sort of theories: theories which show the hallmarks of success such as “empirical adequacy, simplicity, novel predictions, novel explanations, unification, consilience and more” (Callender 2011, 45). It is far from clear that the predictive approach offers such a theory. It has been criticized for being ad-hoc and scarcely supported by empirical studies (Egner and Summerfield 2013, 210–211), and Clark himself acknowledges that “[d]irect neuroscientific testing of the hierarchical predictive coding model […] remains in its infancy” (Clark 2013b, 191) and that the predictive approach “leaves much unspecified” (Clark 2013b, 200).

  16. I am grateful to Mary Leng for discussion of the role played by inference to the best explanation in scientific metaphysics.

  17. Notice that epistemological disjunctivism does not require metaphysical disjunctivism. The representationalist could hold that they have justification in the veridical case that they lack in the non-veridical case, despite the two perceptual experiences being of the same metaphysical kind. See Logue (2011) for discussion.

  18. See Fumerton (2006, 680–681).

  19. Naïve realists claim that their theory allows for superior epistemic contact with the world on the grounds that perceptual experience is constituted by its worldly objects, but this distinction between naïve realism and representationalism is not generally framed in terms of inferences.

  20. There is no reason to think the situation would be different on an externalist approach to justification or evidence. On a reliabilist approach, for example, inferential perceptual processes would provide justification in so far as they are reliably truth-conducive: it’s hard to see what further relevant epistemic role would be played by their inferential nature. I am grateful to Alistair Isaac for discussion of this point.

  21. See Siegel (2017), however, for discussion of the idea that perceptual inferences can play a justificatory role.

  22. Stich (1978) distinguishes between beliefs and subdoxastic states, where the latter are belief-like states that are consciously inaccessible to the believer. I discuss Stich’s distinction in Drayson (2012, 2014, 2017a, b).

  23. I discuss Hohwy’s notion of an evidentiary boundary as it relates to the cognitive architecture of predictive processing in Drayson (2017a, b).

  24. Notice that Cartesian skepticism affects metaphysically direct as well as indirect approaches, because even metaphysical disjunctivism allows that our veridical experiences are subjectively indistinguishable from the relevant non-veridical experience.

  25. Hohwy proposes that the predictive approach is (vehicle) internalist by way of contrast to (vehicle) externalist approaches such as enactive and extended views. The standard responses to Cartesian skepticism are externalist with respect to content, justification, or knowledge, none of which require a commitment to externalism about vehicles.


  • Boghossian, P., (2014). What is inference? Philosophical Studies, 169(1), 1–18.

    Article  Google Scholar 

  • Burr, C., & Jones, M. (2016). The body as laboratory: Prediction-error minimization, embodiment, and representation. Philosophical Psychology, 29(4), 586–600.

    Article  Google Scholar 

  • Callender, C. (2011). Philosophy of science and metaphysics. In S. French & J. Saatsi (Eds.), Continuum companion to the philosophy of science (pp. 33-54). Continuum.

  • Clark, A. (2012). Dreaming the whole cat: generative models, predictive processing, and the enactivist conception of perceptual experience. Mind, 121, 753–771.

    Article  Google Scholar 

  • Clark, A. (2013a). Expecting the world: perception, prediction, and the origins of human knowledge. Journal of Philosophy, 110(9), 469–496.

    Article  Google Scholar 

  • Clark, A. (2013b). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36, 181–253.

    Article  Google Scholar 

  • Clark, A. (2016). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Collier, J. (1996). On the necessity of natural kinds. In B. Rigg (Ed.), Natural kinds, laws of nature and scientific methodology (pp. 1–10). Berlin: Springer.

    Google Scholar 

  • Colombo, M., & Series, P. (2012). Bayes in the brain—On Bayesian modelling in neuroscience. British Journal for the Philosophy of Science, 63(3), 697–723.

    Article  Google Scholar 

  • Drayson, Z. (2012). The uses and abuses of the personal/subpersonal distinction. Philosophical Perspectives, 26(1), 1–18.

    Article  Google Scholar 

  • Drayson, Z. (2014). The personal/subpersonal distinction. Philosophy Compass, 9(5), 338–346.

    Article  Google Scholar 

  • Drayson, Z. (2017a). Psychology, personal and subpersonal. In Routledge encyclopedia of philosophy. Taylor and Francis. Retrieved Oct 23, 2017. doi:10.4324/9780415249126-V044-1.

  • Drayson, Z. (2017b). Modularity and the predictive mind. In T. Metzinger & W. Weise (Eds.), Philosophy and predictive processing. Frankfurt am Main: MIND Group. doi:10.15502/9783958573130

    Chapter  Google Scholar 

  • Egan, F. (1998). Vision. In Routledge Encyclopedia of Philosophy. London: Routledge, Web. (July 19, 2016). doi:10.4324/9780415249126-W047-1.

  • Egner, T., & Summerfield, Christopher. (2013). Grounding predictive coding models in empirical neuroscience research. Behavioral and Brain Sciences, 36(3), 210–211.

    Article  Google Scholar 

  • Fish, W. (2004). The direct/indirect distinction in contemporary philosophy of perception. Essays in Philosophy, 5(1), 1–13.

    Google Scholar 

  • Fodor, J. (2000). A science of tuesdays. Review of The threefold cord: Mind, body and world by H. Putnam,  London review of books, 22(14), 21–22. Available from Accessed July 19, 2016.

  • Friston, K. (2002). Functional integration and inference in the brain. Progress in Neurobiology, 68, 113–143.

    Article  Google Scholar 

  • Friston, K., & Kiebel, S. (2009). Predictive coding under the free-energy principle. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1521), 1211–1221.

    Article  Google Scholar 

  • Fumerton, R. (2006). Direct realism, introspection, and cognitive science. Philosophy and Phenomenological Research, 73(3), 680–695.

    Article  Google Scholar 

  • Gibson, J. J. (1967). New reasons for realism. Synthese, 17(1), 162–172.

    Article  Google Scholar 

  • Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton Mifflin.

    Google Scholar 

  • Gładziejewski, P. (2016). Predictive coding and representationalism. Synthese, 193(2), 1–24.

    Article  Google Scholar 

  • Harman, G. (1986). Change in view: Principles of reasoning. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Hatfield, G. (2002). Perception as unconscious inference. In D. Heyer (Ed.), Perception and the physical world (pp. 113–143). London: Wiley.

    Google Scholar 

  • Helmholtz, H. (1878). The origin and meaning of geometrical axioms. Mind, 3(10), 212–225.

    Article  Google Scholar 

  • Hohwy, J. (2007). Functional integration and the mind. Synthese, 159(3), 315–328.

    Article  Google Scholar 

  • Hohwy, J. (2013). The predictive mind. Oxford: OUP.

    Book  Google Scholar 

  • Hohwy, J. (2014). The self-evidencing brain. Noûs. doi:10.1111/nous.12062.

    Article  Google Scholar 

  • Kiefer, A. (2017). Literal perceptual inference. In T. Metzinger & W. Wiese (Eds.), Philosophy and predictive processing. Frankfurt am Main: MIND Group. doi:10.15502/9783958573185.

    Chapter  Google Scholar 

  • Logue, H. (2011). The skeptic and the naïve realist. Philosophical Issues, 21(1), 268–288.

    Article  Google Scholar 

  • Lyons, J. (2016). Epistemological problems of perception. In Edward N. Zalta (ed.), Stanford encyclopedia of philosophy (Winter 2016 Edition).

  • Macpherson, F. (2015). Cognitive penetration and predictive coding: A commentary on Lupyan. Review of Philosophy and Psychology, 6(4), 571–584.

    Article  Google Scholar 

  • Mandelbaum, E. (2016). Attitude, inference, association: On the propositional structure of implicit bias. Noûs, 50(3), 629–658.

    Article  Google Scholar 

  • Marr, D. (1982). Vision. New York: Freeman.

    Google Scholar 

  • McDowell, J. (1986) Singular thought and the extent of inner space. In P. Pettit & J. McDowell (Eds.), Subject, thought, and context (pp. 137–168). Oxford: Clarendon Press.

    Google Scholar 

  • McDowell, J. (1998). Meaning, knowledge, and reality. Cambridge: Harvard University Press.

    Google Scholar 

  • Orlandi, N. (2014). The innocent eye: Why vision is not a cognitive process. Oxford: OUP.

    Book  Google Scholar 

  • Putnam, H. (1999). The threefold cord: mind, body and world. New York: Columbia University Press.

    Google Scholar 

  • Pylyshyn, Z. W. (2006). Seeing and visualizing: It’s not what you think. A Bradford Book.

  • Ross, D., Ladyman, J., & Kincaid, H. (Eds.). (2013). Scientific metaphysics. Oxford: Oxford University Press.

    Google Scholar 

  • Schrenk, M. (2005). The Bookkeeper and the Lumberjack. Metaphysical vs. Nomological Necessity. In G. Abel (Ed.), Kreativität. XX. Deutscher Kongress für Philosophie. Sektionsbeiträge Band 1.Universitätsverlag der Technischen Universität.

  • Shand, J. (2014). Predictive mind, cognition, and chess. Analysis, 74(2), 244–249.

    Article  Google Scholar 

  • Siegel, S. (2017). The Rationality of Perception. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Stich, S. P. (1978). Beliefs and subdoxastic states. Philosophy of Science, 45, 499–518.

    Article  Google Scholar 

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Correspondence to Zoe Drayson.

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Drayson, Z. Direct perception and the predictive mind. Philos Stud 175, 3145–3164 (2018).

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  • Direct perception
  • Indirect perception
  • Cognitive architecture
  • Predictive coding
  • Bayesian computation
  • Perceptual inference