In economics, Knightian uncertainty is a lack of any quantifiable knowledge about some possible occurrence, as opposed to the presence of quantifiable risk (e.g., that in statistical noise or a parameter's confidence interval). The concept acknowledges some fundamental degree of ignorance, a limit to knowledge, and an essential unpredictability of future events. Knightian uncertainty is named after University of Chicago economist Frank Knight (1885–1972), who distinguished risk and uncertainty in his 1921 work Risk, Uncertainty, and Profit: "Uncertainty must be taken in a sense radically distinct from the familiar notion of Risk, from which it has never been properly separated.... The essential fact is that 'risk' means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far-reaching and crucial differences in the bearings of the phenomena depending on which of the two is really present and operating.... It will appear that a measurable uncertainty, or 'risk' proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all." In this matter Knight's own views were widely shared by key economists in the 1920s and 1930s who played a key role distinguishing the effects of risk from uncertainty. They were particularly concerned with the different impact on human behavior as economic agents. Entrepreneurs invest for quantifiable risk and return; savers may mistrust potential future inflation. Whilst Frank Knight's seminal book elaborated the problem, his focus was on how uncertainty generates imperfect market structures and explains actual profits. Work on estimating and mitigating uncertainty was continued by G. L. S. Shackle who later followed up with Potential Surprise Theory.However, the concept is largely informal and there is no single best formal system of probability and belief to represent Knightian uncertainty. Economists and management scientists continue to look at practical methodologies for decision under different types of uncertainty. (Wikipedia).
Robustness of G-Expectation under Knightian Uncertainty - Prof. Shige Peng
A workshop to commemorate the centenary of publication of Frank Knight’s "Risk, Uncertainty, and Profit" and John Maynard Keynes’ “A Treatise on Probability” This workshop is organised by the University of Oxford and supported by The Alan Turing Institute. For further details and regular
From playlist Uncertainty and Risk
Matteo Burzoni: Viability and arbitrage under Knightian uncertainty
Abstract: We provide a general framework to study viability and arbitrage in models for financial markets. Viability is intended as the existence of a preference relation with the following properties: It is consistent with a set of preferences representing all the plausible agents trading
From playlist Probability and Statistics
What Is The Uncertainty Principle?
Subscribe to our YouTube Channel for all the latest from World Science U. Visit our Website: http://www.worldscienceu.com/ Like us on Facebook: https://www.facebook.com/worldscienceu Follow us on Twitter: https://twitter.com/worldscienceu
From playlist Science Unplugged: Quantum Mechanics
What Heisenberg's Uncertainty Principle *Actually* Means
Let's talk about one of the most misunderstood but awesome concepts in physics. The Heisenberg uncertainty principle. Or maybe it should be the Heisenberg 'fuzziness' principle instead? Would that confuse less people?
From playlist Some Quantum Mechanics
Classical and Quantum Subjectivity
Uncertainty is a major component of subjective logic beliefs. We discuss the cloud of uncertainty across Markov networks, insights from computational irreducibility, and negative quantum quasiprobabilities and beliefs.
From playlist Wolfram Technology Conference 2022
Uncertainty Principle - Klim Efremenko
Klim Efremenko Tel-Aviv University; Member, School of Mathematics April 23, 2013 Informally, uncertainty principle says that function and its Fourier transform can not be both concentrated. Uncertainty principle has a lot of applications in areas like compressed sensing, error correcting c
From playlist Mathematics
What is the Uncertainty Principle?
The Heisenberg uncertainty principle - in a nutshell! Tweet it - http://bit.ly/pagxNi Facebook it - http://on.fb.me/pzzfqM minutephysics is now on Google+ - http://bit.ly/qzEwc6 And facebook - http://facebook.com/minutephysics Minute Physics provides an energetic and entertain
From playlist Quantum Physics
Waves and Particles C2 The Heisenberg Uncertainty Principle
The Heisenberg uncertainty principle.
From playlist Physics - Wave Particle Duality
Underwood Uncertainty Principle
We work through the details of the uncertainty principle between the position-squared operator and the momentum operator - a modified version of the Heisenberg Uncertainty Principle.
From playlist Quantum Mechanics Uploads
Heisenberg's Uncertainty Principle with @MichaelPennMath
University of Oxford Mathematician Dr Tom Crawford derives Heisenberg's Uncertainty Principle in Quantum Mechanics with assistance from @MichaelPennMath. This is the second video in the short series - part 1 on Lie Algebras here: https://www.youtube.com/watch?v=Sxy4WDIUs6M The video begi
From playlist Collaborations
Percent Uncertainty In Measurement
This video tutorial provides a basic introduction into percent uncertainty. It also discusses topics such as estimated uncertainty, absolute uncertainty, and relative uncertainty. This video provides an example explaining how to calculate the percent uncertainty in the volume of the sphe
From playlist New Physics Video Playlist
Uncertainty and Propagation of Errors
A discussion of how to report experimental uncertainty, and how to calculate propagation of errors. Based on the nice video by paulcolor: https://youtu.be/V0ZRvvHfF0E, with some personal edits.
From playlist Experimental Physics
DIRECT 2021 14 Tuning Deep Learning Models Maldonado-Cruz
DIRECT Consortium at The University of Texas at Austin, working on novel methods and workflows in spatial, subsurface data analytics, geostatistics and machine learning. This is Tuning Ensemble Machine Learning Uncertainty Models by Eduardo Maldonado-Cruz. Join the consortium for access
From playlist DIRECT Consortium, The University of Texas at Austin
DSI | A Biased Tour of the Uncertainty Visualization Zoo | By Matthew Kay
Uncertain predictions permeate our daily lives (“will it rain today?”, “how long until my bus shows up?”, “who is most likely to win the next election?”). Fully understanding the uncertainty in such predictions would allow people to make better decisions, yet predictive systems usually com
From playlist DSI Virtual Seminar Series
Frank H. Knight and Risk, Uncertainty and Profit - Prof. Ross Emmett
Speaker Ross Emmett, Professor of Economic Thought, School of Civic and Economic Thought and Leadership, and Director, Center for the Study of Economic Liberty, Arizona State University Abstract Frank Knight’s Risk, Uncertainty and Profit was published in 1921, and has remained in publi
From playlist Uncertainty and Risk
Heisenberg uncertainty principle | Physical Processes | MCAT | Khan Academy
Visit us (http://www.khanacademy.org/science/healthcare-and-medicine) for health and medicine content or (http://www.khanacademy.org/test-prep/mcat) for MCAT related content. These videos do not provide medical advice and are for informational purposes only. The videos are not intended to
From playlist Physical processes | MCAT | Khan Academy
IB Chemistry 17.1 Experimental determination of Keq
IB Chemistry 17.1 Experimental determination of Keq Experimental calculations for Topic 7 Equilibrium HL practical. How to determine the Equilibrium Constant taking you through all the calculations including Beer's Law, RICE diagrams, percent error and uncertainty propagation. Good experim
From playlist Topic 7/17 Equilibrium
Heisenberg's Uncertainty Principle Explained In Less Than ONE Minute!!! #Quantum #Mechanics #Physics #Theory #NicholasGKK #Shorts
From playlist Quantum Mechanics
Texas Groundwater Uncertainty Keynote July, 2021
My keynote talk for the Texas Groundwater Conference, on 'Geostatistical Subusrface Uncertainty Methods to Support Groundwater Modeling'. My motivation, to share educational resources, modeling concepts and practical workflows to support professional development. I have links for anyone
From playlist Random Talks