IAS-Research Talk by Iñaki San Pedro: Degrees of Epistemic Opacity

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


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).

Reading group on Evolution and Cognition


1. Objectives: 

  • Introduce basic notions of evolutionary biology and physiology of the nervous system.
  • Understand current discussion on the evolution of human cognition.
  • Discuss the role of the interaction between organism and environment in the evolution of the nervous system.

2. Format

Eleven reading seminars lasting 1.5h around different authors and topics that aim to explain the evolution of the nervous system and cognition in human beings. In each session, one participant will shortly (20min) present the topic in order to facilitate the discussion. After every session, this participant will prepare a summary of the discussion. The final transcript will be evaluated for feedback by the coordinator.

3. Schedule, topics, and readings

Seminars will take place from January to June 2019, on alternate Thursdays from 15:00 to 16:30h, open to online and in-person participation at the Carlos Santamaría Center Seminar 14.

Session Date Topic Bibliography
1. January, 10 Introduction Moreno, A., & Lasa, A. (2003). From basic adaptivity to early mind. Evolution and Cognition, 9(1).

Rosslenbroich, B. (2014). On the origin of autonomy: a new look at the major transitions in evolution (Vol. 5). Springer Science & Business Media. Chapters 8, 10.1 y 10.2

2. January, 24 Evolution of the nervous system I. Dynamic Systems Barandiaran, X., & Moreno, A. (2006). On what makes certain dynamical systems cognitive: A minimally cognitive organization program. Adaptive Behavior, 14(2), 171-185.
3. February, 7 Evolution of the nervous system II. Plant and animal cognition Calvo Garzón, P., & Keijzer, F. (2011). Plants: Adaptive behavior, root-brains, and minimal cognition. Adaptive Behavior, 19(3), 155-171.

Keijzer, F. (2015). Moving and sensing without input and output: Early nervous systems and the origins of the animal sensorimotor organization. Biology & Philosophy, 30, 311–331

4. February, 21 Evolution and Agency Barandiarán, X. (2008). Mental Life. A naturalized approach to the autonomy of cognitive agents. [Thesis Capítulos 5 y 6]
5. 7 March The 4 dimensions of evolution Jablonka, E., & Lamb, M. J. (2007). Précis of evolution in four dimensions. Behavioral and Brain Sciences, 30(4), 353-365.
6. March, 21 Cognitive functions: working memory and the frontal lobe Damasio, El error de Descartes. capítulos 2,3 y 4.

Frederick L. Coolidge, Thomas Wynn. 2009.The Rise of Homo Sapiens, The Evolution of Modern Thinking [capítulo 3]

7. April, 4 Evolution and reproduction Gruss, L. T., & Schmitt, D. (2015). The evolution of the human pelvis: changing adaptations to bipedalism, obstetrics and thermoregulation. Phil. Trans. R. Soc. B, 370(1663), 20140063.
8. April, 18 Cultural Evolution I Portin, P. (2015). A comparison of biological and cultural evolution. Journal of genetics, 94(1), 155-168.

Lewens, T. (2015). Cultural evolution: conceptual challenges. OUP Oxford (capítulo 1)

9. May, 2 Cultural Evolution II Dunbar, R. I. (2009). The social brain hypothesis and its implications for social evolution. Annals of human biology, 36(5), 562-572.

Laland, K., Matthews, B., & Feldman, M. W. (2016). An introduction to niche construction theory. Evolutionary ecology, 30(2), 191-202.

10. May, 16 Evolution and 4E Cognition Barrett, L. The evolution of cognition: a 4E perspective. The Oxford Handbook of 4e Cognition. New York: Oxford UP.

Malafouris, L. Bringing things to mind. In The Oxford Handbook of 4E Cognition.

11. May, 30
Congress July, 10-14 4E Cognition Theories

4. Coordination and more information

In order to join the reading group or request further information, please contact the coordinators:

Enara Garcia (enara.garcia.otero@gmail.com)

Guglielmo Militello (guglielmo.militello@ehu.eus)

Alejandra Martínez Quintero (alejandra.mtz.quintero@gmail.com)

December 18, IAS-Research Talk by Charles Wolfe (Ghent University): Philosophy of biology before biology: a methodological provocation

Date and time: December 18, Tuesday, 11:30 a.m.

Location: Carlos Santamaría Building, Room B14.

Speaker: Charles Wolfe (Ghent University)

Title: “Philosophy of biology before biology”: a methodological provocation


Basing myself on work forthcoming in a volume entitled Philosophy of Biology before Biology (coedited w. C. Bognon-Küss), I argue for a conception I term ‘philosophy of biology before biology’, focusing on the theoretical ‘world’ or ‘context’ out of which the science ultimately called ‘biology’ emerged. This historico-philosophical approach to biology’s genesis is neither internalist study of biological doctrines, nor a reconstruction of the role philosophical concepts might have played in the constitution of biology as science; it looks more at the interplay between metaphysical and empirical issues. This study does not just have implications for understanding the relations between philosophy and biology in the mid- to late 18th century; it should also have an impact on our present understanding of philosophy of biology, given that it is necessarily conditioned by a very specific history and historiography (particularly evolution-centred). Further, ‘philosophy of biology before biology’ sheds a different light on our understanding of how biology as a science of life became unified.