Archive for the ‘new kind of science’ Category
Posted in algorithm, behavior, business strategy, computation, determinism, information theory, law, new kind of science, philosophy, politics, prediction, time on September 2, 2012| Leave a Comment »
As I watched some of the Republican National Convention, gear up for the DNC, get through my own daily work, read essays, strategize about business, talk to friends and family and synthesize all the data, I just come back to this question What Are We So Afraid Of?
I decided to write this post today specifically because I saw this ridiculous commercial yesterday for ADT Pulse. http://www.adtpulse.com/ This commercial made it clear that if you aren’t monitoring your home in real time with video all the time everything you know and love was in grave danger! So, I’ve decided to figure out just how afraid of everything I should be.
Here’s some of what we seem to be afraid about as a culture.
People different than us:
Technology and Media:
Medicine, Shots, Vaccines:
God, Heaven and Hell:
Our Children’s Safety:
Large Hadron Collider:
Nothing to Fear?
So is there anything to fear? are the fears valid? well, I guess they are valid fears if you don’t have information. So here’s some information.
Most fears drilled into us aren’t founded on evidence – at least not at the level we fear them:
Unemployment isn’t really that high in this country (or most western countries), especially if you get an education:
You’ll probably have 5-10 employers in your working lifetime so assume you’ll get laid off, fired or go out of business. There will be other businesses to hire you or you can just make something yourself:
Economy will have short term blips but ultimately continues to churn ahead:
You’re unlikely to be murdered
Children aren’t taken very often (at least in Colorado)
In fact, violence has long been on the decline:
It’s ok if you forget to pray, chances are it probably doesn’t change outcomes:
And humans have been getting tattoos for a long time and the world hasn’t ended:
Oh, and, humans aren’t that different from Bonobos or Chimps, much less other humans. So, maybe we should rethink that worrying about people that aren’t just like us:
Almost every one of common fears are unwound through perspective changes aka education aka realizing it’s not black and white. Again, see the S. Pinker History of Violence link above to get an idea of the real impact of just literacy and access to information and what it does to fear.
Is it a big deal that people fear the wrong things? Yes! Especially if it leads to suicide bombing, racial profiling, not getting an education and so on.
But, c’mon, aren’t there some things we should fear?
and maybe this too
well maybe this too
In the end, methinks fearing too much is a waste of time because in the end we just don’t know what’s going to happen, right?
Knowing you can’t predict it all (thus prevent it) what’s the point in worrying to the point of being truly scared?
So, no, ADT, I won’t be buying your Pulse product.
This post is my interpretation. Other thinkers, philosophers and researchers have other (more technical) approaches regarding this subject.
Statement: There are no models that completely explain the “how or why” sufficiently complex phenomenon.
Explain – Accurately represents the causes, context, behavior and consequences of a phenomenon and presents such representation in a usable form (we can apply this knowledge outside of just explaining)
Completely – 100% (or very nearly 100%) represent all cases of the phenomenon. In particular, there are no “exceptions” nor is there simply a “rule of thumb.”
“How and Why” – The actual behavior, make up, and structure of the phenomenon.
In other words:
All our scientific efforts produce models, not explanations. Models help us improve our methods and provide insight into phenomenon, but they are not the “thing” and they do not explain the “thing”. Our explanations based on models and/or the incomplete information they are always based on (computational irreducibility, uncertainty) are forever not complete and always capable of revision (inaccurate).
Math is the ultimate model language. It is a way to describe relationships when you strip away the gnarly details of the real world. It sometimes has beautiful results but never produces an explanation of the real world.
Computer science is inbetween the real world and math. A great way to simulate things and build new computational models, but because it’s not made of the stuff we’re often simulate it can’t possibly be completely accurate.
Biology and other specialized disciplines tend to rely more observations than abstract models. The result is a nearly infinite record of exception cases making conceptual models that span multiple phenomenon very difficult (well, that’s because you mostly can’t do it.)
Though I’m giving a very truncated account of everything hopefully the point is clear. Explanations are always our judgment, our subjective synthesis of the inaccurate data we have. This does not imply we don’t know anything. Nor does it imply we don’t have explanations. For simple, or relatively simple, phenomenon we have accurate explanations and good working knowledge.
Specifically, as related to this blog, economics, behaviorism, and social models are all useful models. None of the “laws” presented in these disciplines are fullproof. Rational Choice theory, supply and demand, matching laws…. these are good tools, but not full explanations of the how and way of behavior, media and social activity.
Proof: Is left as an exercise to the reader.
Proof Part Duex: This is an intractable problem. There’s no way to formally prove these statements. They are hunches. I do believe the proof is somehow along these lines: to determine if an explanation is complete and accurate I’d have to be able to reduce a phenomenon down somehow, which is impossible for sufficiently complex phenomenon. (think along the lines of the halting problem. i can’t determine if a program is going to halt any more quickly than running the program and seeing if it halts….)
There are many more resources and I’ll post them as I surface them.
Posted in analysis of behavior, data mining, information theory, intelligent agent, new kind of science, philosophy, software, tagged computation, computational neuroscience, nks, turing machines on August 7, 2008| 1 Comment »
The NKS summer school archive site is live. I figured it would be best for me to wait until that was done before I attempted to post my project or write too much about other’s projects.
Perturbing Turing Machines
Perturbations to elementary cellular automata have been investigated thoroughly. Under a certain level of perturbation, there are slight changes to local patterns but the automata tend to recover globally. The more complicated rules show greater disturbance but still can tolerate perturbations. This study considers similar perturbations to Turing machines.
Do Turing machines exhibit similar behavior?
“And the reason this is important is that in any real experiment, there are inevitably perturbations on the system one is looking at” (NKS p. 324). We must account for the effects of perturbations to draw any connections between these simple constructs and their natural counterparts.
Every project done there was interesting. I encourage readers to check them all out. Some projects are more abstract than others and all were a good launch pad for further research or immediate practical use.
I do have to call out Ben Rapoport’s project on neuronal computations. It was beautiful in many ways.
Posted in computation, mathematics, new kind of science, tagged alonzo church, church rosser theory, confluence, functional programming, mathematica, rewriting systems on July 16, 2008| Leave a Comment »
Basically… if symbolic systems terminate (program halts/gives output), the terminating expression is independent of how the rules were applied.
You probably are thinking, “and so what does this have to do with my life?”
a) maybe nothing if arithmetic never enters your life (unlikely)
b) it’s extremely good to know when you use functional programming that you can get to the same answer with many different ways of writing something. For good overview of functional programming, go here.