1. Great work built on weak foundation (science) Hope I can learn and help (shake things up) The problem of Fractal Wrongness

2. Fractal wrongness Emergence Risk

3. Fractal wrongness Much (most?) of what many (most?) believe is obviously false. Emergence Risk Sustainability Autocatalysis Global !#%&!?!? Evolution Technology Markets, finance, … … Robustness Efficiency Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability …

4. Wrongness everywhere, every scale, “truthiness” Involving anything “complex”… Wild success: religion, politics, consumerism, … Debates focused away from real issues… Even if erased, sustainability challenges remain Hopeless if it persists I’ll set aside all of this for now, and “zoom in” on the world of PhD research/academic scientists BTW, excellent case study in infectious hijacking Fractal wrongness

5. Fractal wrongness (PhDs only) Much (most?) of what many (most?) believe is obviously false. Emergence Risk Sustainability Autocatalysis Global !#%&!?!? Evolution Technology Markets, finance, … … Robustness Efficiency Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability …

6. …Extinction simulations have already been performed in a variety of network contexts, including the World Wide Web (WWW) [2], metabolic networks [26], protein networks [25],… [2] R. Albert, H. Jeong, and A.-L. Barabasi. Error and attack tolerance of complex networks. Nature, 406:378{382, 2000. [25] H. Jeong, S. P. Mason, A.-L. Barabasi, and Z. N. Oltvai. Lethality and centrality in protein networks. Nature, 411:41, 2001. [26] H. Jeong, B. Tombor, R. Albert, Z. N. Oltvai, and A.-L. Barabasi. The large-scale organization of metabolic networks. Nature, 407:651{654, 2000.

7. “Wrongness” everywhere, every scale Involving “complexity” Wild success: high impact journals, funding agencies, popular science, policy… Debates shifted away from real issues… Even if erased, huge challenges remain Hopeless if it persists? BTW, excellent case study in infectious hijacking Fractal wrongness (PhDs only)

8. “Wrongness” everywhere, every scale Involving “complexity” Wild success: high impact journals, funding agencies, popular science, policy… Debates shifted away from real issues… Even if erased, huge challenges remain Hopeless if it persists? I’ll set this aside for now, and “zoom in” to a small spot (within science) with a solid foundation (but a huge spot in math and engineering) Fractal wrongness (PhDs only)

9. Rigorous foundations Emergence Risk Autocatalysis Global !#%&!?!? Evolution Technology Markets, finance, … … Robustness Efficiency Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability …

10. A source of fractal wrongness we need to remove Large, thin, nonconvex

11. Software Hardware Digital Analog “solution sets” (a la Marder, Prinze, etc) large, thin, nonconvex All systems Functional

12. Meaning Syntax Words Letters Layered language? large, thin, nonconvex

13. Letters and words 9 letters: adeginorz 9!= 362,880 sequences of 9 letters Only “organized” is a word 1<< (# words) << (# non-words) large thin Meaning Syntax Words Letters

14. Language? Almost all grammatical sentences are meaningless sequences of words are ungrammatical sequences of letters are not words collections of symbols are not letters Meaning Syntax Words Letters

15. large, thin, nonconvex # of order parameters   with  tuning, Watson beat humans at Jeopardy What are the protocols and architecture? Meaning Syntax Words Letters Almost all grammatical sentences are meaningless sequences of words are ungrammatical sequences of letters are not words collections of symbols are not letters

16. large thin 1 << # toys << # piles toys pile

17. large thin 1 << # toys << # piles pile “order for free?” emergence edge of chaos self-organized criticality scale-free ??? statistical physics random ensembles minimally tuned phase transitions bifurcations

18. large thin 1 << # toys << # piles toys pile “order for free?” nonconvex

19. Computer programs Almost any computer language Large # of working programs  larger # of non-programs “Nonconvex” = simple mashups of working programs don’t work Need architecture to organize working programs 1<< (# programs) << (# non-programs) large thin Software Hardware Digital Analog

20. Computer programs Software is not an emergent property of hardware morphodynamics and “top-down causality” ? teleodynamics? Software Hardware Digital Analog

21. Meaning Syntax Words Letters Software Hardware Digital Analog digital All “code” functional software large, thin, nonconvex

22. This paper aims to bridge progress in neuroscience involving sophisticated quantitative analysis of behavior, including the use of robust control, with other relevant conceptual and theoretical frameworks from systems engineering, systems biology, and mathematics. Doyle, Csete, Proc Nat Acad Sci USA, JULY 25 2011 Trivial examples

23. Universal “laws” (constraints) Some constraints on bio & tech rise “bottom up” from physics/chemistry –Gravity –Speed of light –Energy –Carbon –Other small moieties (e.g. redox, …)… more later? Emergence?

24. Components Physical laws as constraints on components Gravity Speed of light Energy Carbon Other small moieties (e.g. redox, …)… more later

25. Components Emergent phenomena? Biology & technology not emergent in any useful sense Dissipation, friction Liquids, gases, fluid dynamics Phase transitions, homogeneous turbulence, etc etc Huge gap

26. Components Emergent phenomena? Biology & technology not emergent in any useful sense Huge gap Dissipation, friction Liquids, gases, fluid dynamics Phase transitions etc Risk not emergent in any useful sense? Gap?

27. Components Emergent phenomena? Biology & technology not emergent in any useful sense Huge gap Dissipation, friction Liquids, gases, fluid dynamics Phase transitions etc Risk not emergent in any useful sense? Gap?

28. Components Emergent phenomena? Big gap HUGE gap Top down causality (Juarrero) Morphodynamics (Deacon) Teleodynamics (Deacon)

29. wasteful fragile Laminar Turbulent efficient robust Laminar Turbulent ? Needs active Active Passive Classical Quantum Lumped Distribute Passive Lossless  coherent story here, but haven’t figured out best way to explain… working on it…

30. Emergence?

31. “New sciences” of “complexity” and “networks”? worse Edge of chaos Self-organized criticality Scale-free “networks” Creation “science” Intelligent design Financial engineering Risk management “Merchants of doubt” … Science as Pure fashion Ideology Political Evangelical Nontech trumps tech

32. simple enzyme Fragility Enzyme amount complex enzyme Theorem! z and p functions of enzyme complexity and amount Savageaumics

33. Fragility hard limits simple Overhead, waste complex General Rigorous First principle Domain specific Ad hoc Phenomenological Plugging in domain details ?

34. ControlComms Physics Wiener Bode Kalman Heisenberg Carnot Boltzmann robust control Fundamental multiscale physics Foundations, origins of – noise – dissipation – amplification – catalysis General Rigorous First principle ? Shannon

35. What I’m not going to talk much about It’s true that most “really smart scientists” think almost everything in these talks is nonsense Why they think this Why they are wrong Time (not space) is our problem, as usual Don’t have enough time for what is true, so have to limit discussion of what isn’t No one ever changes a made up mind (almost) But here’s the overall landscape

36. Stat physics Complex networks Physics Heisenberg Carnot Boltzmann ControlComms Compute “New sciences” of complexity and networks edge of chaos, self-organized criticality, scale-free,… Wildly “successful”

37. D. Alderson, NPS37 Popular but wrong

38. Complex systems? Fragile Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Even small amounts can create bewildering complexity

39. Complex systems? Fragile Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Robust

40. Complex systems? Resources Controlled Organized Structured Extreme Architected … Robust complexity Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence …

41. These words have lost much of their original meaning, and have become essentially meaningless synonyms e.g. nonlinear ≠ not linear Can we recover these words? Idea: make up a new word to mean “I’m confused but don’t want to say that” Then hopefully we can take these words back (e.g. nonlinear = not linear) Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence … Fragile complexity

42. New words Fragile complexity Emergulent Emergulence at the edge of chaocritiplexity Scale Dynamics Nonlinearity Nonequlibrium Open Feedback Adaptation Intractability Emergence …

43. doesn’t work Stat physics Complex networks Alderson & Doyle, Contrasting Views of Complexity and Their Implications for Network-Centric Infrastructure, IEEE TRANS ON SMC, JULY 2010 “New sciences” of complexity and networks edge of chaos, self-organized criticality, scale-free,…

44. Stat physics Complex networks Physics Heisenberg Carnot Boltzmann ControlComms Compute Complex systems? Jean Carlson, UCSB Physics

45. Stat physics Complex networks Physics Heisenberg Carnot Boltzmann Control Alderson &Doyle, Contrasting Views of Complexity and Their Implications for Network-Centric Infrastructure, IEEE TRANS ON SMC, JULY 2010 Sandberg, Delvenne, & Doyle, On Lossless Approximations, the Fluctuation- Dissipation Theorem, and Limitations of Measurement, IEEE TRANS ON AC, FEBRUARY, 2011

46. Stat physics, Complex networks Physics Heisenberg Carnot Boltzmann fluids, QM “orthophysics” From prediction to mechanism to control Fundamentals! Sandberg, Delvenne, & Doyle, On Lossless Approximations, the Fluctuation- Dissipation Theorem, and Limitations of Measurement, IEEE TRANS ON AC, FEBRUARY, 2011 “The last 70 years of the 20 th century will be viewed as the dark ages of theoretical physics.” (Carver Mead)

47. accessible accountable accurate adaptable administrable auditable autonomy available compatible composable configurable correctness customizable debugable determinable demonstrable dependable deployable discoverable distributable durable effective evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable portable precision predictable producible recoverable relevant reliable repeatable reproducible resilient responsive safety scalable serviceable supportable securable stable survivable tailorable testable timely traceable upgradable Lumping requirements into simple groups robust A system can be efficient using a resource or producing waste A system can be efficient using a resource or producing waste But can be inefficient for different resources or waste But can be inefficient for different resources or waste

48. Efficiency tradeoffs efficient with resource 1 wasteful with resource 1 efficient with resource 2 wasteful with resource 2 Ideally Achievable Not

49. Efficiency tradeoffs efficient wasteful efficient wasteful Not? Distance running digesting raw vegs humans cattle chimps pronghorn?

50. accessible accountable accurate adaptable administrable auditable autonomy available compatible composable configurable correctness customizable debugable determinable demonstrable dependable deployable discoverable distributable durable effective evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable portable precision predictable producible recoverable relevant reliable repeatable reproducible resilient responsive safety scalable serviceable supportable securable stable survivable tailorable testable timely traceable upgradable Lumping requirements into simple groups robust A system can be robust for a property and a perturbation A system can be robust for a property and a perturbation But can be fragile for a different property or perturbation But can be fragile for a different property or perturbation

51. Robustness tradeoffs robust to  1 fragile to  1 robust to  2 fragile to  2 Ideally Achievable Not

52. Robustness tradeoffs robust fragile fast slow Not Sprinting Tree climbing humans chimps cheetahs leopards

53. Robustness/efficiency tradeoffs robust fragile efficient Inefficient Not Distance running Tree climbing humans chimps kangeroos

54. Robustness tradeoffs robust to  1 fragile to  1 robust to  2 fragile to  2 Ideally Achievable Not