Visual Displays of Information and the Practice of Science Pragmatic approaches

1. Centro de Filosofia das Ciências da Universidade de Lisboa January 15, 2008 Workshop2 Visual Displays of Information and the Practice of SciencePragmatic approaches Valeria Giardino Università di Roma ‘La Sapienza’ Institut Jean Nicod valeria.giardino@gmail.com http://valeria.giardino.googlepages.com/

2. Diagrams and (history of) science

3. Outline • I. The dynamics of science: against logical empiricism • II. Two proposals • III. A case study: Faraday • IV. Some remarks on science and art • Questions for the discussion

4. I. Capturing the dynamics of science: beyond logical empiricism

5. “The primary mode of scientific representation for a logical empiricist is linguistic. [...]. This cognitive authority resonates in standard portraits of the relationships between technology and science” Baigrie (1996)

6. Logical empiricist image of science • Scientific knowledge consists primarly of what is encapsulated in scientific theories, which are ideally to be thought of as interpreted axiomatic systems; • scientific reasoning has the general character of a logic (linguistic entities). Giere (1996)

7. Kuhn (1965) • The relative evaluation of rival paradigms is not something that can be reduced to any sort of logic but a matter of choice by scientists acting as individuals within a scientific community • Naturalistic account: explaining science in terms of naturalistic categories (psychological make-ups of individual scientists and social interaction)

8. Nevertheless... • no emphasis on the role of visual or other non propositional model of representation in science • no talk about representation • his picture of science as a puzzle-solving activity was meant to be an alternative to the view of science as producing truth BUT representations are still thought of in propositional terms (see the emphasis on incommensurability in linguistic terms) thus leading immediately to the concept of truth Giere (1996)

9. II. How to approach science and the role of the different representations used by scientist:two proposals.

10. Giere (1996) Model-based view of theories A common way of describing it: Two different sorts of linguistic entities • Predicates (quite elaborate internal structure) (ex. ‘pendulum’, ‘two-body Newtonian gravitational system’) • Statements of the form ‘X is P’ (X = real system, P = one of the predicate) (ex. ‘The system earth moon is a Newtonian gravitational system’)

11. Giere’s criticism and proposal This way of formulating the statement and the model-based views still overemphasizes linguistic aspects. His proposal: The predicate ‘pendulum’, as it appears in classical mechanics, does not apply directly to real-world objects but to a family of idealized models.

12. the idealized model pendulum in classical mechanics real swinging weights a prototype things sufficiently similar to the prototype to be classified as of that type Representational devices: language, models, and objects in the real world. The representational relationship is not the truth of a statement relative to the facts, or the applicability of a predicate to an object, but the similarity of a prototype to putative instances (two NON-LINGUISTIC entities)

13. One example A family of models of pendulums radiating out from the model of a simple pendulum The sketch at the top is a particular embodiment of the abstract model of a simple pendulum It too can serve as a prototype in judging the similarity of a particular real pendulum to the classical model

14. Visual presentations of both models and data can be used in crucial decisions about which models best represent the real world • A case study: 20th century geology (stabilism vs. mobilism) • Visual models as an organizing template for whatever other potentially relevant information the agent may possess, regardless of how that information was encoded

15. Nersessian (1996) Scientists’s problem solving strategies and the representational practices developed over the course of history of science: very sofisticated and refined outgrowths of ordinary reasoning and representational processes

16. Beyond the separation between the context of justification (philosophers) and context of discovery (historians and psychologists) Cognitive-historical analysis A new context : development Dynamic processes (long period of time and social context) through which a vague speculation gets articulated into a new scientific theory, gests communicated to other scientists, and comes to replace existing representations of a domain.

17. Ultimate goal: to reconstruct scientific thinking by means of cognitive theories. At present, cognitive theories are largely uninformed by scientific representational and problem-solving practices: the fit cognitive theories/scientific practices still to be determined!

18. Different modeling activities (except for (1), rarely present in the philosophical literature) • Analogical reasoning • Imagistic reasoning • Thought experiment • Limiting case analysis

19. Representational and constructive practices of scientists as part of the scientific method • Developing criteria for evaluating good and bad uses of heuristics • philosophical investigation Reasoning comprises more then algorithms The new problem: how scientists, individually and collectively, combine their cognitive abilities (their biology)together with the acquired conceptual resources

20. III. A case study: Faraday

21. Gooding (2002) Faraday's notebooks : • a rich mixture of sketches, diagrams and text

22. The story of the ‘constructive method’ • Oersted’s discovery that a current-carrying wire has magnetic properties • Many of Faraday’s experiments as showing a temporal slice - a ‘snapshot’- of the effect of some more complex but hidden, physical process • Electrical and magnetic effects are mixed in a way that the eye simply cannot see

23. By September 1821: Faraday and Davy had developed experimental methods of integrating discrete experimental events (or rather, of integrating the images depicting them) • Accumulation: “they combined discrete images obtained over time into a single geometrical structure. Conversely they also created a physical structure of sensors with which to record the effects of a single event at different points of space.”

24. A typical procedure • Positioning one or more needles in the region of a wire, connecting the circuit to a battery and observing the effect on the needle(s) • Similarly, continuous exploration of the space around the wire would produce a pattern made up of many discrete observations of needle positions • These results into a single model, a three-dimensional representation of the magnetic effects of the current • A structure of needles arranged in a spiral around the wire and examined after discharging a current through it, gave a three-dimensional magnetic ‘snapshot’ of the magnetizing effect of the current • Another setup, a horizontal disc with needles arranged around its perimeter, emerged from a set of temporally distinct observations, which this setup integrates into a single spatial array

25. Gooding’s model 2-D pattern >> 3-D structure >> 4-D process >> inference or material derivation

26. Faraday’s sketches • not simple records of observations, rather working notes • tools for thinking, not images of its outcomes • what they purport to represent both complex and dynamic • each image itself stands for an accumulation of practical and theoretical knowledge

27. Interpretative images • cognitive (generative) and social (communicative) functions are inestricably linked • CONSTRUALS or MANIPULATIVE ABDUCTIONS • proto-representationswhich merge images and words in tentative interpretations of novel experiences

28. Other examples of ‘scribbles’ as ‘artifacts’

29. Galilei’s first notes on the parabolic path of projectiles

30. Leonardo’s sketch of ball-bearings

31. Darwin’s third tree of nature diagram

32. IV. Some remarks on art and science

33. Focus on processes: art and science • Distinction emerged during the Renaissance (science domain of fact /arts domain of expression and interpretation) • Yet many of the technologies of art influenced representational practices in the sciences

34. One possible way out of this distinction: focus on processes • The 'two cultures' do not express fundamentally different aspects of human cognitive capability; rather, they express differences between the cultures in which particular cognitive capacities are applied

35. Topper (1996) Scientific illustration is customarily viewed as a form of art (supremacy of written words for recording and conveying information) Only recently illustrations are studied as a means to convey information.

36. A series of issues • the nature of scientific illustration itself – theory-ladenness and empirical content • the nature of all types of illustration and imagery • the demarcation of science, pseudo-science, and art • the very nature of what we mean by them • An artistic or scientific ‘reading’ of a picture is fundamentally a matter of context, not content: one example.

37. The work of the eighteenth-century Dutch artist and anatomist Petrus Camper. His work on physical anthropology later formed the basis of craniometry and, in particular, the racist theory of the so-called facial angle.

38. Petrus Camper’s aim: to show artists how to have a schematic means for drawing Africans correctly (not as black Europeans, as it was usually done), especially the black Magus in Nativity scenes. • Racist (pseudo-)scientists interpreted this artistic artifact as (pseudo-)scientific, expressing the intellectual ranking of human types (in which – not surprisingly – white Europeans were closer to the ideal beauty of Greek sculpture and Africans closer to apes.

39. Questions for the discussion • A (very serious) methodological issue: from case studies to general frameworks? • Philosophy of science: truth or reasoning processes (and technology)? • Are scientific images used (1) to represent some object or (2) differently? • If (1), what is a difference between different kind of images (e.g. A photography vs. a sketch)? If (2), how are they used?

40. References Baigre (1996), Introduction of Picturing Knowledge Giere (1996), Visual Models and Scientific Judgement Gooding (2002), Visualization, Inference and Explanation in the Science Kuhn (1962), The Structure of Scientific Revolutions Nersessian (1996), How do Scientists think? Topper (1996), Towards an Epistemology of Scientific Illustrations