Abstract
The paper examines Marcello Barbieri’s (2007) Introduction to Biosemiotics. Highlighting debate within the biosemiotic community, it focuses on what the volume offers to those who explain human intellect in relation to what Turing called our ‘physical powers.’ In scrutinising the basis of world-modelling, parallels and contrasts are drawn with other work on embodied-embedded cognition. Models dominate biology. Is this a qualitative fact or does it point to biomechanisms? In evaluating the 18 contributions, it is suggested that the answers will shape the field. First, they will decide if biochemistry and explanatory reduction can be synergised by biosemantics. Second, they will show if our intellectual powers arise from biology. Does thinking use—not a language faculty—but what Markoš and colleagues call semiosis by the living? Resolution of such issues, it is suggested, can change how we view cognition. Above all, if the biomechanists win the day, cultural models can be regarded as extending natural meaning. On such a view, biomechanisms prompt us to act and perceive as we model our own natural models. This fits Craik’s vision: intellect gives us the alphanumerical ‘symbols’ that allow thoughts to have objective validity. For the biomechanist, this is explained—not by brains alone—but, rather, by acting under the constraints of historically extended sensoria.
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Notes
After Turing abandoned the goal of developing O-machines (ones returning the value of functions that are not Turing computable), he decided that “mental processes, conceptualized as distinct from matter, could be understood in machine-based terms” (Boden 2006: 168).
On this view ‘conceptual structure arises from sensorimotor experience and the neural structures that give rise to it’ (Lakoff and Johnson 1999: 77).
This contrasts with viewing language as based on ‘non-natural meaning’ or using the human intellect as a basis for signaling and construing intentions.
Clark’s (2006) ‘cognitive niche’ is said to exploit ‘material symbols’. If these are independent of agents, they are inert objects. As Clowes (2007) notes, it is hard to imagine how living beings could learn from such entities. By contrast, if we posit semiotics by the living, such objections fall away.
Instead of seeking foundational propositions, a coherentist approach to science adopts explanatory reduction or what Rescher (1974) called a network model. As Bechtel (2002) puts it, one decomposes behaviour into subtasks and, later, seeks explanations in lower level mechanisms and properties. Where successful, this permits progressive integration of predictions and applications into an established knowledge system.
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Cowley, S.J. Meaning in Nature: Organic Manufacture?. Biosemiotics 1, 85–98 (2008). https://doi.org/10.1007/s12304-008-9003-7
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DOI: https://doi.org/10.1007/s12304-008-9003-7