1. The reductionist blind spot: Russ Abbott Department of Computer Science California State University, Los Angeles higher-level entities and the laws they obey

2. Living matter, while not eluding the ‘laws of physics’ … is likely to involve ‘other laws,’ [which] will form just as integral a part of [its] science. [Starting with the basic laws of physics] it ought to be possible to arrive at … the theory of every natural process, including life, by means of pure deduction. All of nature is the way it is … because of simple universal laws, to which all other scientific laws may in some sense be reduced. There are no principles of chemistry that simply stand on their own, without needing to be explained reductively from the properties of electrons and atomic nuclei, and … there are no principles of psychology that are free-standing. [Starting with the basic laws of physics] it ought to be possible to arrive at … the theory of every natural process, including life, by means of pure deduction. — Einstein Living matter, while not eluding the ‘laws of physics’ … is likely to involve ‘other laws,’ [which] will form just as integral a part of [its] science. — Schrödinger All of nature is the way it is … because of simple universal laws, to which all other scientific laws may in some sense be reduced. There are no principles of chemistry that simply stand on their own, without needing to be explained reductively from the properties of electrons and atomic nuclei, and … there are no principles of psychology that are free-standing. — Weinberg The ability to reduce everything to simple fundamental laws [does not imply] the ability to start from those laws and reconstruct the universe. — The ability to reduce everything to simple fundamental laws [does not imply] the ability to start from those laws and reconstruct the universe. — Anderson

3. Why is there anything except physics? The reductionist challenge If a higher level explanation can be related to physical processes, it becomes redundant since the explanatory work can be done by physics. — Maurice Schouten and Huib Looren de Jong, The Matter of the Mind, 2007 Why is there anything except physics? — Fodor, 1998 Well, I admit that I don’t know why. I don’t even know how to think about why. I expect to figure out why there is anything except physics the day before I figure out why there is anything at all. The point of this talk is to show why this isn’t so.

4. Emergence Phenomena that arise from and depend on some more basic phenomena yet are simultaneously autonomous from that base. The very idea of emergence seems opaque, and perhaps even incoherent. When we finally understand what emergence truly is [we will know] whether there are any genuine examples of emergence. How should emergence be defined? … irreducibility, unpredictability, conceptual novelty, ontological novelty, supervenience? In what ways are emergent phenomena autonomous from their emergent bases? … irreducible to their bases, inexplicable from them, unpredictable from them, supervenient on them, multiply realizable in them? Does emergence necessarily involve novel causal powers, especially powers that produce “downward causation?” Emergence … is simultaneously palpable and confusing. Paul HumphreysMark Bedau Backup slide Emergence, 2008

5. It’s not all that mysterious Do higher-level entities exist?  Game of Life Turing Machines and biological entities. Do higher-level entities obey autonomous higher level laws?  Turing machines are subject to the theory of computability, which is independent of the rules of the Game of Life.  Biological entities are subject to evolution through natural selection, which is defined independently of the underlying physics. Is this surprising?  Higher level entities are built by imposing constraints on lower level elements. A constrained system implements additional laws/mechanisms. Is this trivial?  Higher level entities and laws/mechanisms are causally reducible but ontologically real, resolving the reductionist challenge.  Reducing away higher level entities and the laws/mechanisms they implement creates a reductionist blind spot and is bad science.  Corollary: the principle of ontological emergence. Backup slide Do higher-level entities exist? Yes. Higher level entities are “real.”  Game of Life Turing Machines and biological entities. Do higher-level entities obey autonomous higher level laws? Yes.  Turing machines are subject to the theory of computability, which is independent of the rules of the Game of Life.  Biological entities are subject to evolution through natural selection, which is defined independently of the underlying physics. Is this surprising? No.  Higher level entities are built by imposing constraints on lower level elements. A constrained system implements additional laws/mechanisms. Is this trivial? Yes, but it has significant implications.  Higher level entities and laws/mechanisms are causally reducible but ontologically real, resolving the reductionist challenge.  Reducing away higher level entities and the laws/mechanisms they implement creates a reductionist blind spot and is bad science.  Corollary: the principle of ontological emergence. Too audacious?

6. By suitably arranging Game of Life patterns, one can simulate a Turing machine.  The GoL can compute any computable function. Its halting problem is undecidable. By suitably arranging Game of Life patterns, one can simulate a Turing machine.  The GoL can compute any computable function. Its halting problem is undecidable. Turing machines and the Game of Life http://www.ibiblio.org/lifepatterns/ A 2-dimensional cellular automaton. The Game of Life rules determine everything that happens on the grid. A dead cell with exactly three live neighbors becomes alive. A live cell with either two or three live neighbors stays alive. In all other cases, a cell dies or remains dead. The “glider” pattern A proxy for physics Nothing really moves. Just cells going on and off.

7. A GoL Turing machine … … is an entity.  Like a glider, it is recognizable; it has reduced entropy; it persists and has coherence—even though it is nothing but patterns created by cells going on and off. … obeys laws from the theory of computation. … is a GoL phenomenon that obeys laws that are independent of the GoL rules while at the same time being completely determined by the GoL rules. Reductionism holds. Everything that happens on a GoL grid is a result of the application of the GoL rules and nothing else. Computability theory is independent of the GoL rules. Just as Schrödinger said.

8. Not surprising A constrained system is likely to obey special rules How can you use two tablespoons of water to break a window? Russ Abbott 4. Hurl the “water stone” at the window. 2. Freeze the water, thereby constraining its molecules into a rigid lattice structure. 3. Remove the frozen water from the tray. 1. Spoon the water into an ice cube tray.

10. Not surprising A constrained system is likely to obey special rules So if we constrain the GoL to act like a TM, it shouldn’t be surprising that it is governed by TM laws. How can you use two tablespoons of water to break a window? Russ Abbott 4. Hurl the “water stone” at the window. 2. Freeze the water, thereby constraining its molecules into a rigid lattice structure. 3. Remove the frozen water from the tray. Phase transitions often signal the imposition or removal of a constraint. 1. Spoon the water into an ice cube tray. Frozen water implements a solid. It can be used like a solid, and it obeys the laws of solids. (That’s because it is a solid— which is an abstraction.) Is this a trivial observation? Is it just common sense?

11. Causally reducible; ontologically real GoL Turing machines are causally reducible but ontologically real.  You can reduce them away without changing how a GoL run will proceed.  Yet they exist as higher level entities and obey laws not derivable from the GoL rules.  They come into being as a result of constraints imposed on an underlying system.  This is the essence of software. Software constrains a computer to behave like something else—such as a slide projector. oI can’t use it to add 2+2 when I’m showing slides.  All executing software applications are causally reducible yet ontologically real. Reducing everything to the level of the GoL rules results in a blind spot regarding higher level entities and the laws/mechanisms that govern them.

12. Evolution is to Physics as Computability is to the Game of Life Namely, autonomous. Evolution is about populations of abstract entities; the mutation and combination of abstract properties that make those abstract entities more or less suited to their abstract environment; the influence of that suitability on the ability of those abstract entities to survive and reproduce—thereby generating more abstract enti ties. Evolution is an abstract process that operates on abstract entities. E.g., evolutionary computing generates solutions to difficult optimization and design problems. Biology is physical. Let’s stipulate that it’s possible to reduce biology to physics … that nature builds biological entities from elementary particles; that it’s (theoretically) possible to trace how any state of the world— including the biological organisms in it—came about by tracking elementary particle wave functions— along with quantum randomness. This parallels the fact that it’s possible to trace the operation of a GoL Turing machine by tracking GoL cell transitions.

13. Recognize biological entities as real and apply the abstraction of evolution to them. Deny the reality of biological entities. Reduce biology to physics. Biology’s options In doing so, Darwin and Wallace implicitly predicted that biological entities must have a way of transmitting information about properties. DNA proved them right. This is simply bad science. Throw away evolution and biological entities — and hence biology — creating another reductionist blind spot.

14. Level of abstraction A collection of entities and relationships that can be described independently of their implementation. A Turing machine; biological entities; every computer application, e.g., PowerPoint. When implemented, a level of abstraction is causally reducible to its implementation. You can look at the implementation to see how it works. Its independent description makes it ontologically real. How it behaves depends on its description at its level of abstraction, which is independent of its implementation. The description can’t be reduced away to the implementation without losing information. If the level of abstraction is about nature, reducing it away is bad science. Two backup slides

15. Does nature use levels of abstraction? Given the imposition of some (random) constraints, what entities result? Two possibilities.  There are none, or they don’t persist. Back to nature’s drawing board.  They persist and by their interaction create a new level of abstraction.  Nature then asks: what can I build on top of that? (Think James Burke’s Connections.) Software developers do the same thing. It’s all very bottom-up—and in nature’s case random. Each new level of abstraction creates a range of possible laws/mechanisms that didn’t exist before and that could not have been “deduced” from lower levels—except by exhaustive enumeration.

16. The principle of ontological emergence Extant entities and levels of abstraction are those whose implementations have materialized and whose environments enable their persistence.

17. Is that it? Does this resolve the problem of reductionism vs. the special sciences? Does it explain emergence? Is it too easy?

18. Three kinds of material entities Static: atoms, molecules, solar systems, most engineered artifacts.  Persist within energy wells. Energy is required to destroy them.  Supervenience works well.  Less mass than the aggregate of their components. Dynamic: biological and social entities, hurricanes.  Extract energy from the environment to persist. May be destroyed by cutting off energy supply.  Since dynamic entities supervene over constantly changing collections of lower level elements, supervenience doesn’t work well. The atoms and molecules making up our bodies change daily. The members of most social units (a country, a corporation, a club, etc.) change.  More mass than the aggregate of their components. Symbolic: software entities.  Persist within a symbolic support framework: computers. May be destroyed by destroying the framework. No individual energy issue.  Since symbolic entities supervene over (potentially unbounded numbers) of bits supervenience, doesn’t work well. Debugging can be hard.  No mass issue. Real: objectively observableAll have reduced entropy: persistent patterns. Distinctive mass properties.

19. Is it strange that the unsolvability of the TM halting problem entails the unsolvability of the GoL halting problem? We import a new and independent theory into the GoL and use it to draw conclusions about the GoL. Downward causation? This is called “reduction” in Computer Science. We reduce the question of GoL unsolvability to the question of TM unsolvability by constructing a TM within a GoL universe. Downward causation entailment

20. Levels of abstraction Used by scientists to characterize how some aspect of nature, i.e., some groups of entities, operates.  How can I describe the level of abstraction that nature is implementing—e.g., evolution in biology? Used by mathematicians as axioms for a mathematical subfield—e.g., Peano’s axioms for the natural numbers.  What are the logical consequences of this level of abstraction? Used by computer scientists to create new applications.  This level of abstraction characterizes the entities and operations that we want the software to implement.  This level of abstraction is cool.

21. Abstract data types & levels of abstraction void push(stack: s, : e) pop(stack: s) top(stack: s) top(push(stack: s, : e)) = e pop(push(stack: s, : e) = s Stack 1.Zero is a number. 2.If A is a number, the successor of A is a number. 3.Zero is not the successor of a number. 4.Two numbers of which the successors are equal are themselves equal. 5.(Induction axiom) If a set S of numbers contains zero and also the successor of every number in S, then every number is in S. Peano’s axioms. A collection of “types” (categories/kinds), operations that may be applied to entities of those types, and often constraints that are required to hold. Simple examples: stack, naturals. Every computer program, e.g., PowerPoint, implements a level of abstraction—typically including a number of abstract data types.  The things you can manipulate.  What you can (and can’t) do with them.

22. What’s different? This is an bottom-up, platform-based, implementation view rather than a top-down analysis view.  Yes, there is multiple realization, but what matters is what functionality gets created, not whether there are multiple ways to realize it.  The eye may or may not have evolved multiple times. What matters is that it added (some sort of) vision each time it did. Software developers (and engineers) ask:  How can I implement some (higher) level of abstraction using what currently exists as a platform?  The higher level is no more derived from the implementation than a painting is derived from the palette. In both cases it’s a creative process.  Once done, we ask: what I can build using this as a building block? In nature, there is no advance specification—other than the implicit specification implied by the environment. Once created, each new entity class adds new abstraction possibilities.