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. 2/19/20162Abbott - WPE 2007 - Delft

3. Engineers are from physics; computer scientists are from philosophy Can everything be reduced to physics? Two different worlds. 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 their worlds. ◦There is more than physics—but we may not be sure what. 2/19/2016Abbott - WPE 2007 - Delft3

4. Intellectual leverage: Engineering Engineering gains intellectual leverage through mathematical modeling and functional decomposition. ◦Both approximate an underlying reality (physics). ◦Neither creates 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. If a problem arises, engineers, like scientists, can dig down to a lower level to investigate. 2/19/2016Abbott - 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. 2/19/2016Abbott - 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. CS turns ideas into a symbolic reality. ◦A realized conceptual model; externalized thought. 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. A difference between requirements (“the system shall”) and a specification (“the system is”)? 2/19/2016Abbott - 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. ◦Scientists turn reality into ideas. ◦Humanists turn reality into dreams. ◦Mathematicians turn coffee into theorems. 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. 2/19/2016Abbott - 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. 2/19/2016Abbott - WPE 2007 - Delft8

9. Reductionist blind spot Of course constraints impose new laws. 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 Not expressible other than in terms of the level of abstraction. 2/19/2016Abbott - 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. 2/19/2016Abbott - 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. 2/19/2016Abbott - WPE 2007 - Delft11