Risk, Uncertainty, and Profit¶
Knight, F. H. (1921). Risk, Uncertainty, and Profit. Houghton Mifflin.
Cited by¶
7 citations across 7 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Epistemic Humility
- Epistemic humility asks: "What is the appropriate level of confidence for this role and context?" not "Should I be certain or uncertain?"—a distinction between deep uncertainty and risk that Knight (1921) introduced in his foundational analysis of decision under unknown probabilities.
This sourceFoundational distinction between measurable 'risk' (assignable probability distributions) and genuine 'uncertainty' (probabilities not capable of measurement). SUPPORTS marker 219 (distinction between deep uncertainty and risk; decision under unknown probabilities).
- Epistemic humility asks: "What is the appropriate level of confidence for this role and context?" not "Should I be certain or uncertain?"—a distinction between deep uncertainty and risk that Knight (1921) introduced in his foundational analysis of decision under unknown probabilities.
- Optionality
- Conversely, hiding optionality (committing publicly, burning bridges, removing exit pathways) can signal confidence and build trust but eliminates the optionality itself—a tension Knight (1921) anticipated in distinguishing measurable risk from genuine uncertainty, where commitment under the latter forecloses the very flexibility a rational agent would price.
This sourceFoundational distinction between measurable "risk" (well-characterized probability distributions) and genuine "uncertainty" (situations in which probabilities cannot be assigned); the epistemic basis for separating wild-card territory (articulable but uncertain) from black-swan territory (unarticulable).
- Conversely, hiding optionality (committing publicly, burning bridges, removing exit pathways) can signal confidence and build trust but eliminates the optionality itself—a tension Knight (1921) anticipated in distinguishing measurable risk from genuine uncertainty, where commitment under the latter forecloses the very flexibility a rational agent would price.
- Risk
- This is the Knightian fork that Frank Knight (1921) drew between risk and uncertainty: where probabilities are assignable we have risk; where they are not we have uncertainty.
This sourceFoundational distinction between measurable "risk" (well-characterized probability distributions) and genuine "uncertainty" (situations in which probabilities cannot be assigned); the epistemic basis for separating wild-card territory (articulable but uncertain) from black-swan territory (unarticulable).
- This is the Knightian fork that Frank Knight (1921) drew between risk and uncertainty: where probabilities are assignable we have risk; where they are not we have uncertainty.
- Uncertainty
- The essential commitment is to distinguish what is known from what is not known, and — within the unknown — to separate kinds of unknowing that call for different responses: aleatoric uncertainty (noise that cannot be reduced by more information), epistemic uncertainty (ignorance that can be reduced), and deep uncertainty (unknown unknowns, where even the space of possibilities is not fully characterized).
This sourceFoundational distinction between measurable "risk" (well-characterized probability distributions) and genuine "uncertainty" (situations in which probabilities cannot be assigned); the epistemic basis for separating wild-card territory (articulable but uncertain) from black-swan territory (unarticulable).
- The essential commitment is to distinguish what is known from what is not known, and — within the unknown — to separate kinds of unknowing that call for different responses: aleatoric uncertainty (noise that cannot be reduced by more information), epistemic uncertainty (ignorance that can be reduced), and deep uncertainty (unknown unknowns, where even the space of possibilities is not fully characterized).
- Wild Cards
- The core operating assumption is epistemic accessibility: a wild card can be articulated specifically enough to enter a watchlist, withstand scrutiny, and support mechanism analysis, whereas true black swans by definition exceed the organization's capacity to articulate them in prospect — a distinction Knight (1921) anticipated in separating measurable risk from genuinely unmeasurable uncertainty.
This sourceFoundational distinction between measurable "risk" (well-characterized probability distributions) and genuine "uncertainty" (situations in which probabilities cannot be assigned); the epistemic basis for separating wild-card territory (articulable but uncertain) from black-swan territory (unarticulable).
- The core operating assumption is epistemic accessibility: a wild card can be articulated specifically enough to enter a watchlist, withstand scrutiny, and support mechanism analysis, whereas true black swans by definition exceed the organization's capacity to articulate them in prospect — a distinction Knight (1921) anticipated in separating measurable risk from genuinely unmeasurable uncertainty.
Domain-specific¶
- Random Variable
- A random variable can be sharply peaked, skewed, or nearly deterministic; the word marks that it has a distribution, not that its values are evenly or unpredictably spread. Not applicable wherever there is "uncertainty." The construct requires a genuine probability space — an Ω, an event sigma-algebra, and a measure P. Under Knightian uncertainty, scenario planning, or possibility theory there is no such measure, so the apparatus (expectation, variance, quantiles) does not engage at all
This sourceThe source of the risk/uncertainty distinction the sentence turns on -- measurable risk with a known outcome distribution versus true uncertainty without one; possibility theory and scenario planning are later and separate.
- A random variable can be sharply peaked, skewed, or nearly deterministic; the word marks that it has a distribution, not that its values are evenly or unpredictably spread. Not applicable wherever there is "uncertainty." The construct requires a genuine probability space — an Ω, an event sigma-algebra, and a measure P. Under Knightian uncertainty, scenario planning, or possibility theory there is no such measure, so the apparatus (expectation, variance, quantiles) does not engage at all
Verification¶
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