Noise and Morphogenesis Uncertainty, Randomness and Control Miguel Ramón Prado Casanova A thesis submitted in partial fulfilment of the requirements of the University of the West of England, Bristol for the degree of Doctor of Philosophy Faculty of Health and Applied Sciences, University of the West of England, Bristol April 2021 1 Abstract This thesis presents a processual ontology of noise by virtue of which morphogenesis (in its most general understanding as the processes by which order/form is created) must be instantiated. Noise is here outlined as the far from equilibrium environment out of which metastable temporary ‘solutions’ can emerge as the system transitions through the pre- individual state space. While frequently addressed by humanities and arts studies on the basis of its supposed disruptive character (often in terms of aesthetics), this thesis aims to thoroughly examine noise’s conceptual potencies. To explore and amplify the epistemic consequences not merely of the ineliminability of noise but of its originative power as well as within the course of the elimination of givenness by epistemology. This philosophical work is informed by many different fields of contemporary science (namely: statistical physics, information theory, probability theory, 4E cognition, synthetic biology, nonlinear dynamics, complexity science and computer science) in order to assess and highlight the problems of the metascientific and ideological foundations of diverse projects of prediction and control of uncertainty. From algorithmic surveillance back to cybernetics and how these rendered noise “informationally heretical”. This conveys an analysis of how contemporary prediction technologies are dramatically transforming our relationship with the future and with uncertainty in a great number of our social structures. It is a philosophico-critical anthropology of data ontology and a critique of reductive pan-info- computationalism. Additionally, two practical examples of noise characterised as an enabling constraint for the functioning of complex adaptive systems are presented. These are at once biophysical and cognitive, : 1) interaction-dominance constituted by ‘pink noise’ and 2) noise as a source of variability that cells may exploit in (synthetic) biology. Finally, noise is posited as an intractable active ontological randomness that limits the scope of determinism and that goes beyond unpredictability in any epistemological sense due to the insuperability of the situation in which epistemology finds itself following the critique of the given. Word count: 78,441. Contents 2 Acknowledgments 5 Introduction 6 Chapter 1: (ᾰ̓)history of Noise 13 1.1: Introduction to the Chapter 13 1.2: Atomism and Brownian Motion 16 1.3: Noise as a Fundamental Limitation on Measurements 20 1.4: A Profane Thermal Transubstantiation 23 1.5: Applied Demonology 24 1.6: Thermodynamic Entropy and Its Relation to Probability 26 1.7: Turning Juggling into Information Theory 30 1.8: Cybernetic Warfare 36 1.9: Algorithmic Information Theory: The Role of Randomness and Complexity. 39 1.10: Dynamical Systems and Order Through Noise 42 1.11: Groupe des Dix 46 1.12: Conclusion 51 Chapter 2: The Riddle of the Sphinx 53 2.1: Introduction to the Chapter 54 2.1.1: Randomness and Probability 56 2.2: Applied Demonology 2: Laplacian Origins 58 2.3: Epistemic Probability 63 2.4: Physical probability 67 2.4.1: Frequentism 67 2.4.2: Propensity Theory 68 2.4.3: Spencer–Brown’s Probability 72 2.4.4: Best System Account 76 2.5: Wolfram’s Ungrounded Ground of True Randomness 78 2.6: 1-Randomness 80 2.7: Ontic Randomness 84 2.7: Conclusion 88 Chapter 3: Noxiogenesis 89 3.1: Introduction to the Chapter 89 3.2.1: Simondon’s Theory of Information 92 3.2.2: Transduction 94 3.3: Individuation and Self-organisation 96 3.4: Pre-individual: potential for emergence and organisation 106 3.5: Conclusion 109 Chapter 4: Conjuring Chance: Digital Omens and Platforms of Prediction 110 4.1: Introduction to the Chapter 111 4.2: A World Devoid of Chance? 115 3 4.3: Prescient Machines? 123 4.4: Calculation of “futurability” 125 4.5: A Whole New Riddle? 128 4.6: From Markov to Autocomplete 130 4.6.1: Pitfalls of Big Data Correlations 132 4.6.2: Normative Production of Prediction: is this it? 136 4.7: Conclusion: Neotechnical Sacrifice 139 Chapter 5: The Over-Extended Mind? Pink Noise and the Ethics of Interaction- dominant Systems 141 5.1: Introduction to the Chapter 142 5.2.: Cognitive Coupling 144 5.3: The Terms of Engagement 146 5.4: Pink Noise and Interaction-Dependent Systems 149 5.4.1: Extended Cognition and Sensory Substitution Devices 149 5.4.2: Pink Noise 150 5.5: Computer mouse experiments 152 5.6: The ready-to-hand computer mouse 154 5.7: Pink noise as the evidence of an extended cognitive system 156 5.8: The Many Virtues of Noise: Heuristic, Epistemic and Ethical 157 Chapter 6: Noise and Synthetic Biology: How to Deal with Stochasticity? 162 6.1: Introduction to the Chapter 162 6.2: What We Are Talking About when We Talk About Noise and (Synthetic) Biology 164 6.2: Case Studies on Noise and Synthetic Biology 165 6.2.1: Distinction Between Intrinsic/Extrinsic Noise and Stochastic Pulsing 167 6.3: The “Information Metaphor Falsehood” and the Glorification of Noise 169 6.4: Where Is Noise Located? 172 6.5: Final Remarks on the Definitional Spectrum of Noise 174 Chapter 7: Seize the Means of Complexity: A Critique of Pancomputationalism 176 7.1: Introduction to the Chapter 177 7.2: Myriad Complexities 181 7.3: Eruption of Information in the Semiosphere: Eigentümlichkeit and Constraints 185 7.3.1: Eruption of Information in the Semiosphere: Relevance and Meaning 187 7.4: Measures of Complexity: Noise’s Irreducibility to Discreteness 190 7.5: Complex Dynamical Behaviour 193 7.5.1: Processes Exhibiting Chaotic Behaviours 194 7.5.2: Context Sensitive Enabling Constraints: Noxiopoiesis 196 7.6: Computational Metaphors (and their Limits) 199 7.6.1 Hierarchical Order 199 7.6.2: Heterarchical Processes 203 7.7. Conclusion 212 4 7.7.1 Heterarchy, Complexity and Process 212 7.7.2: Ethical Prognosis of the Discretization of Complexity 214 Conclusion 217 Bibliography 221 Acknowledgments I would like to express my deepest gratitude to my supervisors: Dr Sean Watson, Dr Iain Hamilton Grant and Dr Darian Meacham for their trust and constant support, for their always insightful and challenging remarks and for their radical and rigorous intellectual enthusiasm. All their enlightening comments are somehow reflected in this thesis. 5 Prof. Ray Brassier, Dr Eleni Ikoniadou and Dr Emiliano Trizio, who accepted to participate in the jury, are also warmly thanked for a challenging and insightful Viva. I would like to thank the whole team of the UWE philosophy department (Alison Assiter, Charlotte Alderwick, Dagmar Wilhelm, Francesco Tava, Katherina Mitcheson), our fantastic philosophy students, Oriane Petteni (visiting research fellow in 2018) as well as Emma Brannlund and Suwita Hani Randhawa from the politics department. They all make UWE for me a intellectually rewarding and socially joyous place to be. I express particular gratitude to my great friends Mattin and Patricia Fraga, as well as the friends made along the course of the research presented here: Cecile Krummel Malaspina, Inigo Wilkins and Sonia de Jager for camaraderie in the field of noise, their constant feedback and the many hours of discussion and joy in different places and contexts. I would like to thank also Giuseppe Longo for his critical guidance, and Tobias Myland, Lisa-marie Lombardi and Jonathan Anderson for extensive proof reading. Special thanks to Patricia G. Pin and my parents Carmen Casanova and Manuel Prado for their constant support, for their love and bearing my absorbedness and for having heartily encouraged and often freed me to work on this thesis. I cannot thank them enough for the sacrifices they made so that I could pursue my interests. Introduction 6 [A]s all the signals collapse into noise, a sub-primordial chaos entity will arrive. Ccru Channel Zero (2017: 135) [T]he dream that leads to an eventual actual noise that wakens the dreamer. Goodman (1978: 81) In 1931 Karl Jansky, a Bell Labs radio engineer, was assigned the job of investigating sources of static that might interfere with radio voice transmission and maximise the signal to noise ratio for the short-wave transatlantic radiotelephone. Jansky discovered that most of the static was caused by tropical thunderstorms, but additionally, he noted a continuous interference which changed direction over the course of the day. Listening to the static with headphones, Jansky described it as a hissing sound “that can hardly be distinguished from the receiver noise” (Hockey et al., 2014: 587). He found not just a clear instance of “noise in noise”, but an ‘extraterrestrial noise’ that inaugurated radio astronomy and revolutionised our ideas of the universe. In 1964, Arno Penzias and Robert Wilson, also engineers with Bell Labs tasked with tracking down radio noise, discovered the smoking gun of the Big Bang, the Cosmic Microwave Background (CMBR), in the process gathering the first experimental evidence that established the Big Bang model of the origin of the universe. This shattering reverberates through the ages down to the present day. The only thing we have left from the origin of the universe is the CMBR as a faint background noise. A sonic fossil, nearly 14 billion years old, echoing through the cosmos as a huge, magnetic recording of the ‘foundational’ explosion, each echo transformed by its new environment. If order and life counter chaos, they are nevertheless conceived from it. This is the aporia of all structure and life, not only in the noisy perturbation in our antennas, but in the very 7 “cosmological perturbation”1 as such, for what is the universe but an endless self-reproducing chaotic process, in which forces thrust back and forth with abrasive efficiency, gravity binds together hundreds of galaxies as if they were silk gauzes moved by the wind, while dark energy accelerates the expansion of a universe that, according to some, “wipes out [the] traces of its own origins” (Krauss and Scherrer, 2008: 47).