In science, these three terms are generally interchangeable. Their common usage is that they all describe activities, or "events", that are "subject to chance". Such activities, events or processes that are described by these terms are governed by the laws of probability. They all describe activities, events, or "happenings" whose repetitions do not always produce the same outcomes even when given the same inputs every time (initial conditions). In other words, uncertainty is involved.

However, like most words, these enjoy other usage, meanings, as well. For example "random" is sometimes used to mean "disorganized" or "lacking in specific pattern". This is a very different meaning than "activities that don't always produce the same outcome given the same inputs". Consider what a math formula for each of these tow meanings wold consist of. One of them would be based on probabilities; but the other would involve stationary relationships.

On 8/8/17 5:31 PM, Nick Thompson wrote:


I think I know the answer to this question, but want to make sure:

What is the difference beween calling a process “stochastic”, “indeterminate”, or “random”?


Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University <>

*From:*Friam [] *On Behalf Of *Grant Holland
*Sent:* Tuesday, August 08, 2017 6:51 PM
*To:* The Friday Morning Applied Complexity Coffee Group <>; glen ☣<>
*Subject:* Re: [FRIAM] Future of humans and artificial intelligence

Thanks for throwing in on this one, Glen. Your thoughts are ever-insightful. And ever-entertaining!

For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution /is/ stochastic. (You actually did not disagree with me on that. You only said that the reason I was right was another one.) A good book on the stochasticity of evolution is "Chance and Necessity" by Jacques Monod. (I just finished rereading it for the second time. And that proved quite fruitful.)


On 8/8/17 12:44 PM, glen ☣ wrote:

    I'm not sure how Asimov intended them.  But the three laws is a trope that clearly 
shows the inadequacy of deontological ethics.  Rules are fine as far as they go.  But 
they don't go very far.  We can see this even in the foundations of mathematics, the 
unification of physics, and polyphenism/robustness in biology.  Von Neumann (Burks) said 
it best when he said: "But in the complicated parts of formal logic it is always one 
order of magnitude harder to tell what an object can do than to produce the object." 
 Or, if you don't like that, you can see the same perspective in his iterative 
construction of sets as an alternative to the classical conception.

    The point being that reality, traditionally, has shown more expressiveness 
than any of our rule sets.

    There are ways to handle the mismatch in expressivity between reality 
versus our rule sets.  Stochasticity is the measure of the extent to which a 
rule set matches a set of patterns.  But Grant's right to qualify that with 
evolution, not because of the way evolution is stochastic, but because 
evolution requires a unit to regularly (or sporadically) sync with its 

    An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head 
will *always* fail.  It's guaranteed to fail because syncing with the 
environment isn't *built in*.  The sync isn't part of the AI's onto- or 

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