Off-topic, but can you give an example of irreducible uncertainty? I’ve been thinking that, technically, all uncertainty is epistemic uncertainty and that what people call aleatoric uncertainty is really just epistemic uncertainty that is quite expensive to reduce.
There are trivial examples, like when the decay of a given uranium atom will occur, but it seems likely there are macroscopic phenomena that are also irreducibly uncertain over time.
For instance, it’s probably the case that long-term weather prediction is fundamentally impossible past some point. Currently, we use 10-meter grids for simulating atmospheric dynamics, and have decent precision out to 2 weeks. But if we knew the positions / velocities / temperatures of every particle in the atmosphere as of today, let’s say, to 2 decimal places, (alongside future solar energy input fluctuations, temperature of the earth, etc.) we could in theory simulate it in full detail to know what things would be like in, say, a month—but we would lose precision over time, and because weather is a chaotic system, more than a couple months in the future, the loss of precision would be so severe that we would have essentially no information. And at some point, the degree of precision needed to extend how long we can predict hits hard limits due to quantum uncertainties, at which point we have fundamental reasons to think it’s impossible to know more.
Quantum randomness seems aleatory, so anything that depends on that to a large extent (everything depends on that to some extent) would probably also fit the term.
Off-topic, but can you give an example of irreducible uncertainty? I’ve been thinking that, technically, all uncertainty is epistemic uncertainty and that what people call aleatoric uncertainty is really just epistemic uncertainty that is quite expensive to reduce.
There are trivial examples, like when the decay of a given uranium atom will occur, but it seems likely there are macroscopic phenomena that are also irreducibly uncertain over time.
For instance, it’s probably the case that long-term weather prediction is fundamentally impossible past some point. Currently, we use 10-meter grids for simulating atmospheric dynamics, and have decent precision out to 2 weeks. But if we knew the positions / velocities / temperatures of every particle in the atmosphere as of today, let’s say, to 2 decimal places, (alongside future solar energy input fluctuations, temperature of the earth, etc.) we could in theory simulate it in full detail to know what things would be like in, say, a month—but we would lose precision over time, and because weather is a chaotic system, more than a couple months in the future, the loss of precision would be so severe that we would have essentially no information. And at some point, the degree of precision needed to extend how long we can predict hits hard limits due to quantum uncertainties, at which point we have fundamental reasons to think it’s impossible to know more.
Quantum randomness seems aleatory, so anything that depends on that to a large extent (everything depends on that to some extent) would probably also fit the term.