Category: Complexity
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“CAUSEME” to benchmark causal methods
The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the…
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HUMAN DEVELOPMENT REPORT 2021-22
The latest Human Development Report, “Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World”, launched September 8 by UNDP, argues that layers of uncertainty are stacking up and interacting to unsettle life in unprecedented ways. The last two years have had a devastating impact for billions of people around the world, when crises…
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Take your time to consider the possibilities and options
Representations of possible actions pervade human high-level cognition, and shape how we plan, attribute causal responsibility, comprehend language, and make moral judgments.There are too many ‘possible actions’ for us to consider them all. Recent studies offer a strikingly convergent picture of how we call to mind a limited, useful set of possible actions to consider.This…
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Statistical inference links data and theory in network science
The number of network science applications across many different fields has been rapidly increasing. Surprisingly, the development of theory and domain-specific applications often occur in isolation, risking an effective disconnect between theoretical and methodological advances and the way network science is employed in practice. . In this work, we will focus on three intimately related…
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Information theory: A foundation for complexity science
Amos Golan and John Harte published a perspective paper, consolidating the insights and research on knowledge and models from incomplete information in complex environments, based on MaxEnt Modeling and inference are central to most areas of science and especially to evolving and complex systems. Critically, the information we have is often uncertain and insufficient, resulting…
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Technology readiness levels for machine learning systems
The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards…
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Statistics: Are you Bayesian or Frequentist?
Cats bring success – they are ket part of the internet traffic and enjoyment. So let me show a great pic: The real purpose of the cats-pics (delivered by a dog person) is the great video and article from Cassie Kozyrkov What is the difference between Bayesian and Frequentist statistics? (demonstrated with one single coin…
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Cynefin – Sensemaking
Het Cynefin® framework werd als “sensemaking” door Dave Snowden ontwikkeld vanuit een natuur-wetenschappelijke insteek, met als een doel projecten te laten evolueren vanuit de bestaande toestand, en de mogelijke evoluties in te schatten, in plaats van een vooraf gedefinieerd einddoel te fixeren. Cynefin® is in wezen een beslissingsondersteunend kader (framework), geen methode of model.Het is…
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Beslissen: FEP, AI, Bayes
“We sample the world to ensure our predictions become a self-fulfilling prophecy.” Karl Friston De beslissingswetenschappen en neurowetenschappen werden recent verrijkt door het principe van vrije energie (Free Energy Principle / FEP) van Karl Friston. FEP is misschien wel het meest allesomvattende idee sinds de theorie van natuurlijke selectie van Charles Darwin. Samenvattend is het…
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Inquisitive but not discerning
Deprivation curiosity is associated with excessive openness to inaccurate information. New psychology research reveals a dark side of curiosity states: “highly deprivation curious people have an excessive openness to information. More deprivation curious people are more likely to see meaning in meaningless gibberish sentences, and they are more likely to entertain pretty blatant disinformation”. “So…
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Rethinking Computational Approaches to the Mind
Rethinking Computational Approaches to the Mind Fundamental Challenges and Future Perspectives One-day Online Symposium21st October 2022 REGISTER HERE This one-day online event will bring together researchers with expertise in various areas such as complexity science, machine learning & artificial intelligence, information theory & data science, as well as computational/theoretical neuroscience & philosophy to explore different computational approaches…
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Begin with the decision-maker
I enjoyed the article “The first step in AI might surprise you” on AI, ML, Data Science from Cassie so much, I decided to steal some quotes: Leaders, figure out who’s calling the shots. If it’s you, then let’s designate you “The Decision-Maker“ for this project. Otherwise, delegate the position to someone else and ask them to read the…
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The curse of knowledge
Experts are poorer communicators in their own domain than nonexperts, MIT Sloan’s Miro Kazakoff says, and he offers ways to reverse that curse. “One of the critical challenges of professional communication is to recognize and internalize the variety of ways that people decode things,” “When we see a pattern or recognize something or know something,…
