Levels, Reduction vs. emergence

1. Levels,Reduction vs. emergence

2. Any science - theories at each of several levels because most complex systems observed - constructed in a hierarchy of levels • Interaction between elements at any single level - described without specifying any but very general properties of the elements at the next level below, and without considering dynamics at the next level above. • Ex - A car: Mechanisms, Sub-mechanisms, quantum level (Herbet Simon 2007)

3. Levels • Explanation of cognition in micro- (neural states) and macro-levels (mental phenomena) • 2 types of interactions: • Intralevel (horizontal) interactions - components at same level • Interlevel (vertical) interactions - the relationship between levels • “Levels”: ontological, organizational (mechanisms or systems), epistemological or description or analysis.

4. David Marr - Three Levels of Description • Computational level - What information is computed and why • What the system is capable of doing • Deep Blue and Kasparov – equivalent (Dawson 2007) • Representation and algorithm (software) - What program is used • What are the symbols, how are processed • Deep Blue and Kasparov - different • Hardware

5. Ex: Linguistic understanding • Task: Identify syntax and meaning corresponding to speech sounds. • Algorithm: What kind of computation and mental representations? • Implementation: Which part of the brain?

6. Ontological levels - radical E • Organizational levels – modest E • Levels of analysis - specific value E - Analytical levels partially depend upon viewing nature as organized into parts andwholes. (McCauley 07)

7. 3-levels versus more-levels • Understanding cognition = Understanding brain at different levels = Levels of organization (Gordon Shepherd) Levels of the brain: • Whole brain • Large systems and pathways in the brain (e.g. sensory pathways) • Properties of specific centers + local circuits properties of neurons (single cell recording) structures within neurons (dendrites/axons) • Individual synapses + molecular properties of membranes and ion channels (Dawson 2007)

8. Using principles of organization and scale, Churchland and Sejnowski [1992] 7 sub-levels within neuroscience • molecules • synapses • neurons • networks • maps • sub-systems • central nervous system overall

9. Ontologically different levels + radical E → Dualism – Rejected ↔ Anomalies → • Humans = Limited knowledge (McGinn 89) • Distinction ontology-epistemology (levels of analysis and epistemic emergence - weak and strong) • Organizational levels (related to layered view of nature)

10. Smolensky (88) - Connectionism • 3 levels of analysis: conceptual (symbolic, subconceptual, neuronal) • Relationship between sub-symbolic-symbolic levels (similar to relationship between micro-macro): - Conceptual phenomena – necessary conceptual (symbolic) level = Macro-description of cognition - Sub-conceptual phenomena – necessary sub-conceptual level = micro-description of cognition

11. “Mental Rs + Processes: Not supported by the same formal entities • Nets - 2 levels: 1) Formal, algorithmic specification of processing mechanisms 2) Semantic interpretation → Must be done at 2 levels of description (Smolensky 1991)

12. “1 nivel: Procesele mentale reprezentate de nivelul de descriere numerice a unit-lor, legat-lor, ecuatii de evolutie activarilor (NU interpretare semantica) (Smolensky) • “2 nivel: Activitati la nivel larg permit interpretari, dar patt-le astfel fixate nu sunt descrieri clare a procesarii” • “Metrica semantica a sistemului impune o similaritate pt. continut acolo unde exista o similaritate pt. vehicul (=patter-ri similare).” (Clark)

13. Each hidden unit = Microfeature • Microfeature=Unintelligible (‘interpretation’ depends upon its context = other microf-s simultaneously present) • A collection of microfeatures (number of different hidden units) can represent a concept that could be represented by a symbol in a symbolic model • Symbolic account of a network is only an approximate account (Dawson 2007)

14. The ‘‘Massive Redeployment Hypothesis’’ (Horst 2007, p. 164) • Localism - meta-analysis of over one hundred fMRI studies by Michael Anderson (forthcoming) • Neural correlates of performance of some cognitive task and identified, through subtraction analysis, areas of brain that were differentially active during task

15. Authors: Regions identified were ‘‘memory regions,’’ ‘‘attention regions,’’ depending on nature of task studied • Anderson: • Most regions studied - utilized in multiple tasks, and indeed multiple types of tasks (e.g., attention and memory) • Most tasks involved multiple Brodmann areas (see Table 8.2).

16. → ‘‘Cognitive tasks’’ not stand in a one-to-one relation with Brodmann areas, but in a many-to-many relationship (Figure 8.3). ↔ A ‘‘massive redeployment’’ of preexisting brain areas to obtain new functionality. • Anderson: Evolutionary history, brain areas redeployed (originally modular units) • Evolution - a new strategy for acquiring new functionality = Redeploying existing functionality in ensembles of neural areas working together (Not genetical mutations)

17. 2. Reduction (R) vs. Emergence (E) • The history of E[1]complicated, many interpretations[2] • E = Vertical relationships low-level + high-level properties • Reduction or emergence- what is reduced or emerge to what: property or level [1] Kim: “Since around 1990, the idea of emergence has been making a big comeback, from decades of general neglect and disdain - analytic philosophy.” [2] Kim: “‘Emergence’ is very much a term of philosophical trade; it can pretty much mean whatever you want to mean…”

18. Reduction (R) (van Gulick 2001) Ontological R (objects, properties, events ...) • elimination • identity • composition • supervenience • realization

19. Epistemological R (concepts, theories, models, frameworks) • Replacement • Theoretical–Derivational (Logical Empiricist) • A priori Conceptual Necessitation • Expressive Equivalence • Teleo–Pragmatic Equivalence

20. Ernest Nagel [‘61/’79] + Logical empiricists • Reduction of scientific theories + whole sciences • Logical derivation + bridge principles • Constraint (1): “Derivability” of reduced theory from reducing theory • Constraint (2): “Connectability” • “Homogeneous” R of a theory and “heterogeneous” reduction of a theory or a science

21. Wisatt (76) • “Intralevel” relations = Relations over time between successive theories in some science vs. • “Inter level” relations = Cross-scientific relations between theories that reign at the same time at different analytical levels in science → Methodological + ontological implications for theories and sciences contrast vs. • Anti-R: Multiple realizability + irreducibility of conscious experience (McCauley 07)

22. van Gulick: E = “’Xs are more than just Ys’ and that ‘Xs are something over and above Ys.’” • E features - beyond the features of parts from which they emerge = “metaphysical E” (it refers to the relation between real things) or “epistemic E” (cognitive explanatory relations about real world items). (van Gulick 2001) • Ontological and epistemological E - people many times conflate them. (Silberstein and McGeever 1999; O’Connor and Wong 2002)

23. Some properties = combinations of parts at same level. • E properties - different from ∑ parts → Novelty • Crane: novel properties of object- “determinable properties whose determinates are not had by all of the object’s parts.” Ex: Surface colour and wetness Or E properties of whole - supervenient properties of parts • Such properties = “over and above" physical properties

24. 2.1 Ontological emergence (1) Specific value E = Whole and parts - features of same kind, different specific subtypes/values (Ex: A bronze statue + molecular parts - common property = Mass) (2) Modest kind E: “whole - features different in kind from those of its parts …” (Ex: Color, life) (3) Radical kind E: “The whole - features Different in kind from parts Of kind whose nature and existence is not necessitated by the features of its pars + macro-laws influence micro-laws/entities (van Gulick)

25. Ontological E - world = Layered view of nature • Ontologically emergent properties are not determined or reducible to basic properties.(ex. QM) • Ontological E - Controversial

26. Strong E property = “High-level phenomenon arises from a low-level domain, but truths concerning that phenomenon - not deducible even in principle from truths in low-level domain.” (Chalmers 2006) • If strong E phenomena - Not deducible from laws of physics ↔ New laws of nature for consciousness • Colorblind scientist + zombies • Consciousness - supervenes on neural states

27. Epistemological E • Epistemic E - Incapacity explain/predict property of whole system in terms of its parts • Property of whole - determined by properties of parts • Epistemic E - Weak and strong E (Gulick) • Property = Epistemological E - determined to/deducible from intrinsic properties of fundamental entities that compose objects

28. Difficult to explain/predict such a property in terms of its fundamental constituents • “Epistemologically E properties - novel at level of description” • High-level phenomenon = Weak E to low-level when that phenomenon is “unexpected” in accord with laws from low-level (Chalmers 2006) • “Unexpected” - E properties - somehow deductible from low-level properties

29. Ex: “Game of life”, connectionist networks, evolution (for intelligent creatures), high-level patterns CA. • Weak E • High-level properties of system are not of any of its parts • Deductibility without reducibility

30. O’Connor and Wong (2002) • Predictive: E properties = Features of complex systems - not predicted despite knowledge of features + laws of parts • Irreducible-Pattern: E properties + laws = Features of complex systems governed by true, lawlike generalizations within a special science • = Irreducible to fundamental physical theory for conceptual reasons • Macroscopic patterns - Not captured in concepts + laws physics

31. Stephan (2002, 1998): Weak, synchronic, and diachronic E • Weak E: Properties of system - E if they belong to the system as a whole, but not to the parts of that system ↔ Property reductionism • System as a whole=∑parts + organization Ex.: Connect. nets + self-organization and artificial intelligence

32. Diachronic E: Novelty + unpredictability of the system that evolves • Difference weak-diachronic E = Unpredictability of properties • Difference diachronic-synchronic E = Irreducibility of properties • If one property/entity not existed before and suddenly comes into existence ↔ Diachronically new

33. Synchronic novelty is time independent • These 2 irreducibilities → Downward causation or epiphenomenalism Irreducible property • Does not follow from the behavior of the system’s parts that has this property • Does not follow from the behavior of the system’s parts in constellations simpler than the system • Ex: Qualia = Synchronic E properties

35. Nonreductive physicalism (Davidson, 1970; Putnam, 1972; 1978; Fodor, 1974; Boyd, 1980; Searle, 1992; Van Gulick, 1992) (in Gulick 2001) vs. • Left (dualists - Chalmers, 1996; Hasker 1999) and right (reductive physicalists such as Kim, 1989) • Fodor – “autonomy of the special sciences” vs. • Old unity of science view (Oppenheim and Putnam, 1958): all true theories must ultimately be translatable into language of physics - rejected

36. CURRENT OPTIONS ON MIND/BODY PB. • Reduction: 10 versions (see Figure 3) • Emergence: 10 versions (see Figure 7) • Other Options: • Mainstream: Nonreductive physicalism • More radical: Fundamental Dualism - Property - Substance • Pan (Proto-) Psychism • Dual Aspect Monism (Spinoza, Strawson) • Multi-Revolutions View (Penrose, McGinn)