“…human life and life in general on this planet will die out in due course: it is merely a flash in the pan; it is a stage in the decay of the solar system; at a certain stage of decay you get the sort of conditions and temperature and so forth which are suitable to protoplasm, and there is life for a short time in the life of the whole solar system.”
"Why I am Not a Christian"
July 20, 2009
Human cognition as a chance-seeker system
The research on vision that Gibson made public during the 1960s falls within the context of an ‘ecological approach to perception.’ According to Gibson, the organism that perceives is better understood as an active agent that is capable of coordinating their own capacities for action (or movement) with the information available in the immediate environment. Since this potential for action differs in organisms with different bodies, different organisms will be able to select different aspects of the environment. This is how the notion of affordance qua opportunities for action arises.
In very broad terms, the affordances of the environment are said to be what this environment offers to the organism, for better or worse, especially if we consider the case where the animal’s survival depends on the appropriate and rapid selection of the opportunities afforded by the immediate environment. Gibson’s approximation to these ‘affordances’ have been characterized as biological-environmental, as compared to Norman’s perceptual approximation (Norman, 1998). According to this latter cognitive psychologist, even though perceptual affordances may also involve a conventional component, they are just as important as the other type of “external resources.”
Norman has played an instrumental role in transferring the notion of affordance into the research field of Human-Computer Interaction (HCI). In this context, he has helped to develop a methodological framework for the design of “human-centred technologies.” The challenges that Gibson and Norman’s contribution posed to technology design can be summarized as that of designing technologies that present immediate opportunities for action which are aimed at inferring “the best interaction”.
The idea of “inference to the best interaction” partially derives, among other sources, from the idea of “inference to the best explanation” proposed by Gilbert Harman (1965), which, in turn, has developed from Peirce’s ideas on Abduction. Following Niiniluoto (2000), Peirce characterized abduction as reasoning “from effect to cause”, and as “the operation of adopting an explanatory hypothesis.” It is important to consider that these transitions have gone hand in hand with a varied experimental enterprise that has pursued evidence for new paradigms of cognition that have challenged the standard symbolic/representational paradigm –the one that has dominated main stream Cognitive Science. Gibson’s ecological approach has thus been a suitable anti-individualistic experimental background for the new attempts to establish (the basis for) a logic of scientific discovery, in particular, and a logic of new hypothesis generation, in general. Hence, an anti-individualistic logic for scientific discovery can be better understood within the context of a theory of reasoning that is in the service of reasoners (qua cognitive agents), and, therefore, their cognitive objectives. According to Woods (2007), this latter requirement is made manifest in the study of fallacious arguments, on the understanding that the errors of reasoning, and therefore abductive reasoning, depends on the standards of achievement of the cognitive agent’s objectives, rather than on logico-deductive validity standards. In fact, one of the central premises proposed by this logician is that abductive arguments are purposively made by the cognitive agent because they act as rational basis for provisional action.
The notion of inference to the best interaction, in turn, is based not only on Gibson’s ecological approach, but also on the notion of “ecological engineers.” According to this conception, animals like us are capable of building up their own niches, which conveys evolutionary significance. The traditional idea of evolution through natural selection is that this is a process by means of which organisms change in order to better adapt to the environment. Alternatively, it has been proposed (Sterelny, 2004) that this traditional view neglects the way organisms act in order to modify the physical challenges posed by the environment. This is a process that has been labelled as “niche construction.’ This capacity to construct niches is part of a process through which organisms transform the effects of natural selection both on the ecological engineers and their descendants. As a result of this, it is not only the environment that constrains the organism’s adaptation, but also the very organism and his modifying action of the environment.
Peirce’s second characterization of abduction previously mentioned (i.e. the operation of adopting an explanatory hypothesis) has been extended to certain types of ecological actions that enable the agent to unearth additional “information” by means of the agent’s “best interaction” with the environment. The central issue behind this extension is that the abductive arguments that cognitive agents deploy just to “licence the conjecture of a conclusion” (Woods, 2007) –rather than to derive the conclusion- hold a continuous reciprocal interaction with those ecological actions. To put it in terms of a known methodological distinction, this interplay can be understood as a continuous reciprocal interaction between on-line and off-line processes. Such interplay is said to be regulated by a natural tendency to act opportunistically, which is present in most organisms, but which has evolved even further in our case. This is how Magnani (2008) has characterized the concept of opportunistic ecological engineers [chance-seekers]:
“[…] humans like other creatures do not simply live their environment, but they actively shape and change it looking for suitable chances. In doing so, they construct cognitive niches through which the offerings provided by the environment in terms of cognitive possibilities are appropriately selected and/or manufactured to enhance their fitness as chance seekers. Hence, this ecological approach aims at understanding cognitive systems in terms of their environmental situatedness. Within this framework, chances are that “information” which is not stored internally in memory or already available in an external reserve but that has to be “extracted” and then picked up upon occasion.” (p. 2)
According to this characterization, the agent’s modification of the environment creates cognitive niches as part of an action that is aimed at creating further opportunities for additional information. The environment offers opportunities for action, and the organism can act as ecological engineer in order to provide himself with additional information. Such information is not previously stored, but it has to be actively unearthed “on the run” depending on the circumstances. Accordingly, “new ways of inferring” are generated, which should be understood within the broader context of “distribution and delegation” of cognitive functions to the environment (e.g. semiotic disembodiment of mind, and creation of epistemic mediators, in Magnani, 2007).
This opportunistic tendency to seize and create fleeting opportunities to uncover information as “new ways of inferring” would eventually make manifest a conception of human beings as chance-seeker systems. These systems are such because they are continuously engaged in a process of creation and extraction of latent possibilities to unearth new sources of information and knowledge.
Harman, G. (1965). “The Inference to the Best Explanation” Phil Review 74: 88-95
Magnani, L. (2008). Chances, affordances, niche construction, in I. Lovrek, R. J. Howlett, and L. C. Lakhmi (eds.), Knowledge-Based Intelligent Information and Engineering Systems, 11th International Conference, KES 2007, Vietri sul Mare, Italy, September 12-14, 2007, Proceedings, Part II, Series: Lecture Notes in Computer Science LNCS/LNAI 4693, pp. 917-926. Available form the author at http://www-1.unipv.it/webphilos_lab/papers/creating.pdf
Magnani, L. (2007). Semiotic brains and artificial minds. How brains make up material cognitive systems, in: R. Gudwin and J. Queiroz, eds., Semiotics and Intelligent Systems Development, Idea Group Inc., Hershey, PA, pp. 1-41
Niiniluoto, I. (2000). “Defending Abduction,” Phil Sci 66 (Proceedings) S436-S451
Norman, D. (1988). The Design of Everyday Things. Addison Wesley, New York
Sterelny, Kim (2004). “Epistemic Artefact and the Extended Mind.” In The Externalist Challenge. Berlin: Walter de Gruyter, edited by Richard Schantz.
Woods, J. (2007). The concept of Fallacy is Empty. A Resource –Bound Apporach to Error. En Magnani, L and Li, P., (Eds.), Model-Based Reasoning in Science, Technology, and Medicine. Springer-VerlagBerlinHeidelberg.