tag > Systems
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Phase-encoded information is elusive: no single wave holds meaning. It’s the alignment, the relationship, that reveals it. It dominates in systems across nature where precision, interference, or efficiency matter.
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Exapt, Adapt, Disrupt: A Conceptual Framework for Systemic Innovation - by Jacqueline Fendt
Abstract: How do breakthroughs emerge in unpredictable environments? This paper develops a unified framework for systemic innovation by integrating eight key concepts: exaptation, serendipity, emergence, co-optation, bricolage, affordances, recombinant innovation, and effectuation. By synthesizing insights from complexity science, sociology, and entrepreneurship, we reveal how creativity flourishes when innovators repurpose existing elements, harness uncertainty, and leverage unexpected affordances. Unlike conventional models that emphasize structured problem-solving, this framework captures the nonlinear, adaptive, and systemic nature of creativity in innovation ecosystems. We illustrate its applicability across diverse cases—from the exaptation of mRNA vaccines to the recombinant innovation of AI-driven drug discovery, the co-optation of gig work by tech giants, and the emergence of decentralized finance. Our findings suggest that transformative creativity is not a solitary act, but an emergent systems-level process shaped by adaptive recombination and strategic improvisation. By shifting the focus from predictive planning to creative adaptation, this study provides a novel roadmap for navigating uncertainty and fostering systemic change. It offers both scholars and practitioners an actionable lens to harness creativity, unlock latent affordances, and scale innovation in complex environments.
#Complexity #Science #ML #Creativity #Systems #KM #Generative #Augmentation
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This passage from Deb Chachra's "How Infrastructure works" is a truth that often gets forgotten or ignored on the hunt for profit. It's a familiar and recurring theme in resilience engineering texts and research.
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From Artefacts to Experiences and Transformations
#Comment: If you want to know what A.I will automate first, follow this spectrum from left to right.
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A systems model of creativity
Image Sources: Csikszentmihalyi in Simonton (ed) 2014 p. 538 - Csikszentmihalyi in Henry: Creative Management, 2006 - Revised systems model of creativity incorporating creative practice. (Kerrigan p.114)
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Quotes from "Creativity: Flow & the Psychology of Discovery and Invention" by M.Csikszentmihalyi
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Climate Scientists Encounter Limits of Computer Models, Bedeviling Policy (WSJ)
"Supercomputer simulations are running up against the complex physics of programming thousands of weather variables such as the extensive impact of clouds."
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Quantum superposition principle in the legal system: Is the Law Inherently Paradoxical?
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AI rivals average human competitive coder?
A journalist asked me to comment on the story "DeepMind AI rivals average human competitive coder". My comments ended up in the CNBC story "Machines are getting better at writing their own code. But human-level is ‘light years away’". Here are my comments in full length:
Every good computer programmer knows, that it is essentially impossible to create "perfect code" and that all programs are flawed and will eventually fail in unforeseeable ways, due to Hacks, Bugs or Complexity. Hence, computer programming in most critical contexts is fundamentally about building "fail safe" systems that are "accountable". In a 1979 presentation, IBM made the statement: "A computer can never be held accountable. Therefore a computer must never make a management decision". Besides all the recent hype around "AI Coder outperforming humans", the question of the accountability of code remains largely ignored. Has anything changed since IBM made that statement? Do we really want hyper-complex, in-transparent, non-introspectable, so called "autonomous" systems that are essentially incomprehensibly to most and unaccountable to all, to run our critical infrastructure, such as the finance system, food supply chain, Nuclear power plants, weapon systems or space ships?
#ML #Augmentation #Complexity #InfoSec #Robot #Systems #Comment
