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

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Presentation on theme: "The reductionist blind spot: Russ Abbott Department of Computer Science California State University, Los Angeles higher-level entities and the laws they."— Presentation transcript:

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. Why is there anything except physics? — Fodor [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 Why is there anything except physics? — Fodor

3 The reductionist blind spot Do higher-level entities exist? Yes.  Game of Life Turing Machines and biological entities. Do higher-level entities obey independent 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 will obey laws that don’t hold when the system is not constrained. Ice and water act differently. Is this trivial? Yes, but it has significant implications.  Higher level entities and laws are causally reducible but ontologically real.  Reducing away higher level entities and the laws they obey creates a reductionist blind spot.  Corollary: the principle of ontological emergence

4 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.

5 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.

6 Not surprising A constrained system will very likely behave differently from one that isn’t constrained. People in a three legged race run differently than if they weren’t tied together. Their tied legs are synchronized—if they’re lucky. Ice and water behave differently. As ice, the H 2 O molecules form a rigid block. As water they flow. So if we constrain the GoL to act like a TM, it shouldn’t be surprising that it is governed by TM laws. Is this a trivial observation?

7 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. It constrains a computer to behave like something else—such as a slide projector.  So I can’t use it to add 2+2.  All executing software applications are causally reducible and ontologically real Reducing everything to the level of the GoL rules—results in a blind spot regarding higher level entities and the laws that govern them.

8 Evolution is about biological entities Let’s stipulate that it’s possible to reduce biology to physics. Nature builds biological entities from elementary particles. It’s (theoretically) possible to trace how any state of the world—including the biological organisms in it—came about by tracking elementary particles plus quantum randomness.  This parallels the fact that it’s possible to trace the operation of a GoL Turing machine by examining the GoL cell transitions. Nevertheless, evolution is about the evolution of biological entities. One explains evolution by talking about: populations of biological entities, the survival and reproduction of biological entities, the mutation and combination of properties that make biological entities more or less suited to their environment. Biological entities must be understood to exist in order for this to make sense. Biology may be causally reducible to physics, but to do so is to throw away the biological entities—and hence the biology.

9 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 specification makes it ontologically real. What it does depends on the specification at the level of abstraction, which is independent of its implementation. The specification can’t be reduced away to the implantation without losing information.

10 Levels of abstraction Used by scientists to characterize how some aspect of nature, i.e., some groups of entities, operate.  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 number theory.  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.

11 Does nature use levels of abstraction? Given the imposition of some random constraints, what are the resulting entities? Two possibilities.  There are none, or they don’t persist. Back to nature’s drawing board.  The entities persist and by their interaction create a new level of abstraction. Like software developers, nature then asks: What can I build on top of that? (Think James Burke’s Connections.) It’s all very bottom-up—and in nature’s case random. But each new level of abstraction creates a range of possibilities that didn’t exist before and could not have been “deduced” from lower levels—except by exhaustive enumeration. Extant levels of abstraction are those whose implementations have materialized and whose environments enable their persistence. The principle of ontological emergence

12 What was in that Kool Aid?

13 If there’s time which there probably won’t be

14 Three kinds of material entities Static: atoms, molecules, solar systems, most engineered artifacts.  Persist within energy wells. Energy is required to destroy them. Dynamic: biological and social entities, hurricanes.  Extract energy from the environment to persist. May be destroyed by cutting off energy supply.  Dynamic entities supervene over constantly changing collections of lower level elements. The atoms and molecules making up our bodies change daily. The members of most social units (a country, a corporation, a club, etc.) change frequently. Symbolic: software entities, ideas.  Persist within a symbolic support framework: computers and our minds. May be destroyed by destroying the framework.

15 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

16 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), operations that may be applied to entities of those types, and often constraints that are required to hold. Typical 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 do (and can’t) do with them

17 What’s different? This is an bottom-up, implementation view rather than a top-down analysis view. Software developers (and engineers) ask:  How can I implement some (higher) level of abstraction using elements from a given level of abstraction? How can I turn my dream into reality?  Once that’s done, we ask: What I can build using this as a building block? The specification of the higher level is not derived from the implementation. The challenge is to find some way to implement a given specification—or fantasy.


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