Running head: A MODULE IS A MODULE Published as: Grossi, G. (2014). A Module is a module is a module: Evolution of modularity in Evolutionary Psychology. Dialectical Anthropology, DOI: 10.1007/s10624-014-9355-0. A Module is a Module is a Module: Evolution of Modularity in Evolutionary Psychology Giordana Grossi State University of New York at New Paltz Address and correspondence Giordana Grossi Department of Psychology, SUNY New Paltz 600 Hawk Drive, New Paltz, NY 12561 ph: (845) 257-2674 fax: (845) 257-3474 email: [email protected] Acknowledgments: Many thanks to Alison Nash, Suzanne Kelly, Gowri Parameswaran, and two anonymous reviewers for their thoughtful comments and suggestions on an earlier version of this manuscript. 1 Abstract The concept of modularity has been central in behavioral and neural sciences since the publication of Fodor’s The Modularity of Mind (1983). Fodor strived to explain the functional architecture of the mind based on the distinction between modular and central systems. Modular systems were deemed to have certain architectural features, such as automaticity, encapsulation, and domain-specificity. Evolutionary psychologists have adopted the concept to characterize purportedly evolved human adaptations. In an influential paper, Barrett and Kurzban (2006) proposed a definition of modules purely in terms of functional specialization. It is here argued that such strategy marks a shift in Evolutionary Psychology’s theoretical emphasis, as it trivializes the investigation of proximate causes in evolutionary theorizing; furthermore, it leaves the door open to too much flexibility on what counts as evidence for purportedly evolved modules. 2 History and definition of modularity Modularity is a central concept in the cognitive and neural sciences. Generally speaking, modularity is the idea that the mind and the brain are organized in systems that are specialized to process specific types of information and that are functionally independent (Coltheart, 1999). The concept became predominant in psychology after the publication of Fodor’s The Modularity of Mind (1983). Fodor’s (1983) hypothesis about the functional architecture of the mind was proposed to explain the types of psychological mechanisms underlying the different facts of mental life (e.g., sensation, perception, volition, and learning). In his account, the architecture of the mind is divided into modular and central systems. Modular systems include perceptual (or input) and linguistic mechanisms, whereas central systems pertain to decision-making systems, knowledge, and beliefs. The latter systems were deemed not to be modular and cut across a variety of cognitive domains. Without clearly defining the term “module,” Fodor associated modular systems with specific characteristics, such as automaticity, informational encapsulation, and domain-specificity: - Automaticity: A system was conceptualized as automatic if its mechanisms are to be “obligatorily applied” (p. 53), such as those involved in spoken word recognition in native speakers of a language: even when participants are asked to focus on low-level (acoustic-phonetic) characteristics of speech, it is impossible to turn off word recognition mechanisms. 3 - Informational encapsulation: A system was deemed to be encapsulated if it is less permeable to background information, contextual factors, or beliefs than other systems. Fodor illustrated this property by discussing the mechanisms responsible for visual illusions. In the Müller-Lyer illusion, the line flanked by two arrow tails looks longer than the line flanked by two arrowheads. This perception persists even after the viewer is informed that the two lines are identical in length. - Domain-specificity: Modules are specialized, in the sense that only a restricted class of stimuli has access to them. For example, the input systems involved in recognizing speech are different from the auditory systems involved in the recognition of non- speech sounds (Fodor, 1983). Modular systems tend to have other related characteristics, such as being hardwired (i.e., “associated with specific, localized, and elaborately structured neural systems,” p. 37) and innate (i.e., they “develop according to specific, endogenously determined patterns under the impact of environmental releasers”, p. 100). According to Fodor, modules needed not share all these characteristics; furthermore, modularity is a matter of degree. Fodor’s speculative view of the mind, born within philosophy, prompted a considerable amount of research and discussion among cognitive psychologists and neuroscientists. Much of the empirical research focused on determining how perceptual and linguistic systems function and whether they exhibit characteristics such as encapsulation, automaticity, and domain-specificity. Empirical findings revealed a complex picture in which not even perceptual systems turned out to exhibit some of the 4 defining characteristics of modularity. For example, some charged that input systems do not exhibit strict encapsulation because their functioning is modulated by attention (e.g., Wojciulik, Kanwisher, & Driver, 1998) or higher-level cognitive processes (Farah, 1994). Furthermore, behavioral studies had already shown that perceptual mechanisms are modulated by contextual factors and information from other sensory modalities. For example, in the McGurk effect (McGurk & MacDonald, 1976), the auditory perception of a syllable (e.g., /ba/) changes when the syllable is visually presented with the face of a person pronouncing another sound (e.g., /ga/): in this case, participants hear /da/. These and other empirical results led to a more refined understanding of how the brain is organized and functions, as I will discuss later. Evolutionary Psychology1 and modularity In the late 1980s, the concept of modularity was borrowed by a group of evolutionary psychologists (e.g., John Tooby, Leda Cosmides, Steven Pinker, David Buss) and reframed in terms of evolved adaptations. In their view, the human mind is comprised of numerous specialized modules (or “mini-computers”) that have evolved under selective pressure to solve recurrent problems in humans’ ancestral past (Cosmides & Tooby, 1997, p. 11). Therefore, the Evolutionary Psychology (EP henceforth) version of modules rests on the assumptions that they are supported by dedicated neural circuits, shaped by natural selection, and genetically specified (Pinker, 1997, p. 21). Examples of 1 The term “Evolutionary Psychology” will be used in this paper to denote the thought of an influential group of researchers including, among others, Leda Cosmides, John Tooby, David Buss, and Steven Pinker. It is not to be confused with “evolutionary psychology” as the general field of inquiry. Please see the Introduction to this issue for more information. 5 modules include face recognition, tool-use, fear, social-exchange, kin-oriented motivation, child-care, social-inference, sexual-attraction, friendship, grammar acquisition, and theory of mind (Tooby & Cosmides, 1992, p. 113). A number of assumptions are made regarding these modules. For example, they are domain-specific, that is, “relatively well-engineered for solving ancestral adaptive problems” (Cosmides & Tooby, 1994, p. 88). This assumption relies on the claim that such problems cannot be solved by domain-general mechanisms. Evolutionary psychologists argue that different problems require sensitivity to different types of information and different solutions. For example, selecting food and selecting a mate typically lead to different solutions; therefore, they rely on different, and specialized, mechanisms (Confer et al., 2010). Another assumption is that the number of specialized modules has increased in humans, compared to other primates and mammals, and this increase ensures humans’ flexible and complex behavior. In this context, modules are “pre-specified” structures, as they contain information about the world: “The more a system initially "knows" about the world and its persistent characteristics, and the more evolutionarily proven "skills" it starts out with, the more it can learn, the more problems it can solve, the more it can accomplish.” (Tooby & Cosmides, 1992, p. 113) Evolutionary psychologists’ focus is on a computational, or functional, analysis of behavior, based on Marr’s distinction between levels of description (Cosmides & Tooby, 2003; Tooby & Cosmides, 1994). In his influential book Vision (1982/2010), Marr 6 posited that informational systems can be analyzed at three different levels of description: computational, or functional (what a system does and why; the problem that the system solves); algorithmic/representational (how a system does what it does, what representations and processes it uses), and implementational (how a system is neurally/physically implemented). Marr considered the three levels of description “rather loosely related” (2010, p. 25) and constrained by different issues (independence among levels)2. For this reason, for some phenomena, there might be no unitary theory connecting all three levels. By privileging a computational analysis of behavior, evolutionary psychologists adopt reverse engineering to identify traits that have been advantageous (in terms of reproductive fitness) during human evolution in “ancestral times”. These “design features” are identified based on hypotheses concerning the problems faced by our ancestors and speculations about the ancestral environments in which they lived. Design features, which characterize evolved