1. Bits don’t have error bars Russ Abbott Department of Computer Science California State University, Los Angeles

2. Is there anything besides physics? “[L]iving 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.” Erwin Schrödinger, What is Life?, 1944. “At each level of complexity entirely new properties appear. … The whole becomes not only more than but very different from the sum of its parts. Philip Anderson, “More is Different,” 1972. [The] workings of all the animate and inanimate matter of which we have any detailed knowledge are all … controlled by the same set of fundamental laws [of physics]. … [W]e must all start with reductionism, which I fully accept. Philip Anderson, “More is Different,” 1972. 2/18/20162Abbott - WPE 2007 - Delft

3. Computer science is applied philosophy Can everything be reduced to physics? Engineers are grounded in physics. ◦Ultimately there is nothing besides physics—even though engineers build things that have very different properties from their components. Computer scientists live in a world of abstractions. ◦Physics has very little to do with our worlds. ◦There is more than physics—but we may have a hard time saying what it is. 2/18/2016Abbott - WPE 2007 - Delft3 Engineering is applied physics

4. Intellectual leverage: Engineering Engineering gains intellectual leverage through mathematical modeling and functional decomposition. ◦Models approximate an underlying reality (physics). ◦Models are judged by the width of their error bars. ◦Models don’t create ontologically independent entities. No reliable floor. Engineering is both cursed and blessed by its attachment to physicality. ◦“Engineering systems often fail … because of [unanticipated interactions among well designed components] that could not be identified in isolation from the operation of the full systems.” National Academy of Engineering, Design in the New Millennium, 2000. But if a problem arises engineers, like scientists, can dig down to a lower level to solve it. 2/18/2016Abbott - WPE 2007 - Delft4

5. Intellectual leverage: CS Computer science gains intellectual leverage by building levels of abstraction. New types and operations—externalized thoughts. Operationally reducible to a pre-existing substrate. What Searle (Mind, 2004) calls causal but not ontological reducibility. The bit provides a symbolic floor, which limits realistic modeling, e.g., no good models of evolutionary arms races. 2/18/2016Abbott - WPE 2007 - Delft5

6. Turning dreams into reality Engineering and Computer Science both transform ideas—which exist only as subjective experience—into (material) phenomena. ◦Taking mind and mental constructs as given. ◦Scientists turn reality into ideas. ◦Humanists turn reality into dreams. ◦Mathematicians turn coffee into theorems. CS turns ideas into a symbolic reality. ◦A realized conceptual model. Engineering turns ideas into a material reality. ◦A car is a material object. It’s capabilities aren’t— although once built we use it for our purposes. 2/18/2016Abbott - WPE 2007 - Delft6

7. Externalizing thought The first step in turning ideas into reality is to externalize subjective experience (ideas) in a form that allows it to be examined and explored. Computer languages enable executable externalized thought—different from all other forms of externalized thought throughout history. There is nothing comparable in engineering—or any other field. ◦All other forms of externalized thought require a human being to interpret them. ◦A computer program operates in the world on its own. 2/18/2016Abbott - WPE 2007 - Delft7

8. Abstractions are real Game of Life. The rules correspond to the laws of physics. Gliders can implement Turing Machines. ◦Both are (epiphenomenal) levels of abstraction. ◦Causally but not ontologically reducible. Turing Machines obey computability theory—Schrödinger’s “new laws.” Downward entailment: halting problem for GoL is undecidable. 2/18/2016Abbott - WPE 2007 - Delft8

9. Reductionist blind spot Levels of abstractions are constraints. ◦Software constrains the instruction sequences a computer may execute. ◦And thereby implements new “conservation laws”—suggested (unintentionally) by Alfred Hübler. ◦A form of “broken symmetry,” a theme from Anderson. Of course constraints impose new laws. The new laws are not expressible other than in terms of the level of abstraction. 2/18/2016Abbott - WPE 2007 - Delft9

10. Principle of emergence Extant levels of abstraction—naturally occurring or man-made, static (at equilibrium) or dynamic (far from equilibrium)—are those whose implementations have materialized and whose environments support their persistence. 2/18/2016Abbott - WPE 2007 - Delft10

11. Summary With its gift of the bit, Engineering created a world that is both real and symbolic. Computer Science, native-born to that world, developed the level-of-abstraction— an example of computational thinking. Computational thinking enabled the solution to a fundamental philosophical problem: emergence as the reality of epiphenomenal abstractions. 2/18/2016Abbott - WPE 2007 - Delft11