Date and time: July 16, Tuesday, 11:30 a.m.

Location: Carlos Santamaría Building, Room B14.

Speaker: Miguel A. Sepúlveda-Pedro (Université de Montréal)

Title: Opening the ecological dimension of the enactive approach: Umwelt, normativity, and form

Abstract:

The enactive approach is an alternative approach to cognition that challenges many fundamental assumptions of mainstream cognitive science. One of the most fundamental assumptions of traditional cognitive science is that the objective World is a ready-made reality that we access via our cognitive capacities, thus cognition essentially consist in getting information about this objective reality. In this classical picture, we need to reconstruct or represent the outside world in our heads, given the limited capacities of our senses. From the beginning, the enactive approach has challenged this conception of cognition by positing that the world we live, in our cognitive lives, is enacted thanks to the interactions of a living agent and its surroundings. Therefore, it is suggested that the world that a cognitive agent experience is not an objective reality but a dimension that acquires meaning and value according to the skills and concerns of living agents. Thompson, in his Mind in Life, loosely refer to this enactment of a meaningful world as an Umwelt. Uexküll coined the concept of Umwelt to define the world as it is lived by animals, according to their biological needs. However, Uexküll statements was sometimes explicitly linked to Kant’s transcendental philosophy. One of the problems of Kant’s transcendental philosophy is that it encloses the subject in its own domain, meanwhile an objective unknowable reality remains the source of materials that acquire form thanks to the mental capacities of the subject. In this Kantian background, the enactment of an Umwelt will be analogous to the constitution of a meaningful world by the capacities of the subject alone. This interpretation of the Umwelt is deeply problematic, and it does not reflect the claims of the enactive approach. This approach, like phenomenology, offers an account that entails a deep entanglement between the body and the environment, not an enclosed form of subjectivity. Nevertheless, many criticisms on the enactive approach seems to interpret the enactment of an Umwelt in the Kantian sense, so they claim that the enactive approach entails some form of subjectivism. In my view, many of these criticism are unfounded due to misinterpretations of the claims of the enactive approach, nonetheless, their criticisms push us to have a more specific account of the Umwelt, one that remains coherent with the claims of the enactive approach, but that also avoids the problems that have been usually attributed to the enactive approach. Thus, I will suggest that conceptually the notion of interanimality and the metaphor of animal melodies, in Merleau-Ponty’s philosophy of nature, offer us a better way to understand the characteristics of the Umwelt, from the perspective of the enactive approach. Moreover, I will also suggest that an account of what I call structural emergence needs to be also explicitly added to the theory of biological autonomy, to open the domain of embodied subjectivity to a deeper ecological dimension of emplaced intercorporeality.

Date and time: February 12, Tuesday, 11:30 a.m.

Location: Carlos Santamaría Building, Room B14.

Speaker: Jean-Francois Moreau (University Hospital of Bordeaux)

Title: Aging as a metaphor of the importance of spatial organization in multicellular organisms

Date and time: February 19, Tuesday, 11:30 a.m.

Location: Carlos Santamaría Building, Room B14.

Speaker: Iñaki San Pedro (UPV/EHU)

Title: Degrees of Epistemic Opacity

Abstract:

The paper distinguishes two senses of “epistemic opacity” in computer simulations, namely a qualitative sense and a quantitative sense, and explores their relation to actual simulating and modelling practices.

From a qualitative point of view, the notion of “epistemic opacity“ in computer simulation seems to have the same significance and implications for any computer simulations. That is, from a qualitative point of view, computer simulations seem to be equally opaque —i.e. we open the black box, and find it (always) dark! In this sense “epistemic opacity” expresses the fact that when a computer simulation is performed there is an “epistemic leap” associated to it. This kind of epistemic leap is characteristic rather than of a specific model or simulation, of the fact that a simulation is performed.

On the other hand, “epistemic opacity” can also be approached from a quantitative point of view. The questions to be asked then are rather different, e.g. is the “epistemic leap” noted above always of the same size? or are all computer simulations equally opaque, i.e. when we open the back box and find it dark, is it always as dark? The paper argues that (from this quantitative point of view), computer simulations display degrees of “epistemic opacity” (with the limit of non-opacity set in analycity). I will not discuss here whether these degrees of “epistemic opacity” can be measured (i.e. exactly quantified), or attempt provide a method for doing that. I will claim nevertheless that actual degrees of “epistemic opacity” are tightly related to what we can call the “complexity of the computational process”, which is associated for instance to the particular design of the computing software at work, specific computer settings, or to hardware limitations. With this idea of complexity in mind, I will claim, the more complex a computational process is, the more (quantitatively) epistemically opaque will the simulation result.

I will note finally that a good deal of methodological decisions taken by scientist and modellers when performing computer simulations —i.e. typical tricks-of-the-trade such as parametrisation, use of expert knowledge, scaling, etc.—, which constitute an important part of current scientific practices in the field, are precisely aimed at reducing such complexity. I will conclude thus that actual scientific practices (or part of these, at least) in fact reduce (quantitative) “epistemic opacity.” This opens new and interesting questions such as whether actual scientific practices can manage to reduce “epistemic opacity” to the limit of analycity (thus eliminating “epistemic opacity” also in a qualitative sense), whether specific scientific practices can be said to reduce in some (qualitative) sense some of the uncertainties that computer simulations involve, or whether they have an impact on the reliability or confidence of specific computer simulations (possibly of the very same system).