A user’s guide to the evolutionary argument against naturalism

Alvin Plantinga has famously argued that metaphysical naturalism is self-defeating, and cannot be rationally accepted. I distinguish between two different ways of understanding this argument, which I call the "probabilistic inference conception", and the "process characteristic conception". I argue that the former is what critics of the argument usually presuppose, whereas most critical responses fail when one assumes the latter conception. To illustrate this, I examine three standard objections to Plantinga's evolutionary argument against naturalism: the Perspiration Objection, the Tu Quoque Objection, and the "Why Can't the Naturalist Just Add a Little Something?" Objection. I show that Plantinga's own responses to these objections fail, and propose counterexamples to his first two principles of defeat. I then go on to construct more adequate responses to these objections, using the distinctions I develop in the first part of the paper.     

Epistemic instrumentalism,exceeding our grasp

In the concluding chapter of Exceeding our Grasp Kyle Stanford outlines a positive response to the central issue raised brilliantly by his book, the problem of unconceived alternatives. This response, called "epistemic instrumentalism", relies on a distinction between instrumental and literal belief. We examine this distinction and with it the viability of Stanford's instrumentalism, which may well be another case of exceeding our grasp.     

Model structure adequacy analysis: selecting models on the basis of their ability to answer scientific questions

Models carry the meaning of science. This puts a tremendous burden on the process of model selection. In general practice, models are selected on the basis of their relative goodness of fit to data penalized by model complexity. However, this may not be the most effective approach for selecting models to answer a specific scientific question because model fit is sensitive to all aspects of a model, not just those relevant to the question. Model Structural Adequacy analysis is proposed as a means to select models based on their ability to answer specific scientific questions given the current understanding of the relevant aspects of the real world.     

The error statistical philosopher as normative naturalist

We argue for a naturalistic account for appraising scientific methods that carries non-trivial normative force. We develop our approach by comparison with Laudan’s (American Philosophical Quarterly 24:19–31, 1987, Philosophy of Science 57:20–33, 1990) “normative naturalism” based on correlating means (various scientific methods) with ends (e.g., reliability). We argue that such a meta-methodology based on means–ends correlations is unreliable and cannot achieve its normative goals. We suggest another approach for meta-methodology based on a conglomeration of tools and strategies (from statistical modeling, experimental design, and related fields) that affords forward looking procedures for learning from error and for controlling error. The resulting “error statistical” appraisal is empirical—methods are appraised by examining their capacities to control error. At the same time, this account is normative, in that the strategies that pass muster are claims about how actually to proceed in given contexts to reach reliable inferences from limited data.     

Using category structures to test iterated learning as a method for identifying inductive biases

Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases—assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed data. This article explores a novel experimental method for identifying the biases that guide human inductive inferences. The idea behind this method is simple: This article uses the responses produced by a participant on one trial to generate the stimuli that either they or another participant will see on the next. A formal analysis of this "iterated learning" procedure, based on the assumption that the learners are Bayesian agents, predicts that it should reveal the inductive biases of these learners, as expressed in a prior probability distribution over hypotheses. This article presents a series of experiments using stimuli based on a well-studied set of category structures, demonstrating that iterated learning can be used to reveal the inductive biases of human learners.     

Action understanding as inverse planning

Humans are adept at inferring the mental states underlying other agents’ actions, such as goals, beliefs, desires, emotions and other thoughts. We propose a computational framework based on Bayesian inverse planning for modeling human action understanding. The framework represents an intuitive theory of intentional agents’ behavior based on the principle of rationality: the expectation that agents will plan approximately rationally to achieve their goals, given their beliefs about the world. The mental states that caused an agent’s behavior are inferred by inverting this model of rational planning using Bayesian inference, integrating the likelihood of the observed actions with the prior over mental states. This approach formalizes in precise probabilistic terms the essence of previous qualitative approaches to action understanding based on an “intentional stance” [Dennett, D. C. (1987). The intentional stance. Cambridge, MA: MIT Press] or a “teleological stance” [Gergely, G., Nádasdy, Z., Csibra, G., & Biró, S. (1995). Taking the intentional stance at 12 months of age. Cognition, 56, 165-193]. In three psychophysical experiments using animated stimuli of agents moving in simple mazes, we assess how well different inverse planning models based on different goal priors can predict human goal inferences. The results provide quantitative evidence for an approximately rational inference mechanism in human goal inference within our simplified stimulus paradigm, and for the flexible nature of goal representations that human observers can adopt. We discuss the implications of our experimental results for human action understanding in real-world contexts, and suggest how our framework might be extended to capture other kinds of mental state inferences, such as inferences about beliefs, or inferring whether an entity is an intentional agent.     

Beyond perceptual symbols: A call for representational pluralism

Recent evidence from cognitive neuroscience suggests that certain cognitive processes employ perceptual representations. Inspired by this evidence, a few researchers have proposed that cognition is inherently perceptual. They have developed an innovative theoretical approach that rests on the notion of perceptual simulation and marshaled several general arguments supporting the centrality of perceptual representations to concepts. In this article, I identify a number of weaknesses in these arguments and defend a multiple semantic code approach that posits both perceptual and non-perceptual representations.     

Orientation perception in Williams Syndrome: Discrimination and integration

Williams Syndrome (WS) is a rare neurodevelopmental disorder, which stems from a genetic deletion on chromosome 7 and causes a profound weakness in visuospatial cognition. Our current study explores how orientation perception may contribute to the visuospatial deficits in WS. In Experiment 1, we found that WS individuals and normal 3–4 year olds had similar orientation discrimination thresholds and had similar prevalence of mirror-reversal errors for diagonal targets (±45 deg). In Experiment 2, we asked whether this immaturity in orientation discrimination would also be reflected in a task requiring integration of oriented elements. We found that sensitivities of WS individuals for detecting orientation-defined contours were higher than sensitivities of normal 3–4 year olds, and were not significantly different from sensitivities of normal adults. Together, these results suggest that orientation discrimination and orientation integration have different maturational trajectories in normal development and different susceptibilities to damage in WS. These may reflect largely separate visuospatial mechanisms.     

Perception with compensatory devices: from sensory substitution to sensorimotor extension

Sensory substitution devices provide through an unusual sensory modality (the substituting modality, e.g., audition) access to features of the world that are normally accessed through another sensory modality (the substituted modality, e.g., vision). In this article, we address the question of which sensory modality the acquired perception belongs to. We have recourse to the four traditional criteria that have been used to define sensory modalities: sensory organ, stimuli, properties, and qualitative experience ( Grice, 1962 ), to which we have added the criteria of behavioral equivalence ( Morgan, 1977 ), dedication ( Keeley, 2002 ), and sensorimotor equivalence ( O'Regan & Noë, 2001 ). We discuss which of them are fulfilled by perception through sensory substitution devices and whether this favors the view that perception belongs to the substituting or to the substituted modality. Though the application of a number of criteria might be taken to point to the conclusion that perception with a sensory substitution device belongs to the substituted modality, we argue that the evidence leads to an alternative view on sensory substitution. According to this view, the experience after sensory substitution is a transformation, extension, or augmentation of our perceptual capacities, rather than being something equivalent or reducible to an already existing sensory modality. We develop this view by comparing sensory substitution devices to other "mind-enhancing tools" such as pen and paper, sketchpads, or calculators. An analysis of sensory substitution in terms of mind-enhancing tools unveils it as a thoroughly transforming perceptual experience and as giving rise to a novel form of perceptual interaction with the environment.