estimator

Karma: 203

estimator 3 Apr 2015 18:57 UTC
15 points
on: Against the internal locus of control
I was kinda surprised to see IQ as an external factor; my impression is that internal vs. external locus of control is actually personality traits vs. circumstances and environment, and IQ obviously falls into the first category.

If you consider IQ and mental health external factors, what are the internal factors, then? Willpower? But willpower is determined by the brain structure just as IQ and mental health and other personality traits.

Basically, if you assign everything to the “external” category, so that the “internal” is an empty set (or almost empty), then one’s success is determined by “external” factors. No surprise here.

Why IQ shouldn’t be considered an external factor

estimator4 Apr 2015 17:58 UTC

2 points

10 comments2 min readLW link

estimator 4 Apr 2015 19:24 UTC
0 points
in reply to: janos’s comment on: Why IQ shouldn’t be considered an external factor
Well, you’re right that in the mental illness case my definition works badly, but I can’t think about a better precise definition right now (can you?); probably something like selecting a specific “sub-process” in brain which is related to the conscious experience, but it’s fuzzy and I’m not even sure that such separation is possible.

I think the correct intuitive definition of “locus of control” is “those things you can do if you want to”.

I have a feeling that it is a rephrasing of “things under your control”.

Causality is entirely about hypothetical interventions; to say “your way of thinking affects your IQ” is just to say that if I was to change your way of thinking, I could change your IQ.

Actually, I’m arguing that causal arrows are pointing in the opposite direction: if I was to change your IQ, I could change your way of thinking. The rest of article is about what happens if we assume IQ fixed (that somehow resembles Bayesian inference).

estimator 4 Apr 2015 19:36 UTC
0 points
in reply to: [deleted]’s comment on: Why IQ shouldn’t be considered an external factor

Involuntary responses are not under your control and are not “determined by physical processes in your brain”, but are considered actions. Voluntary responses are also influenced by factors occurring outside your brain. If you’re tired, you are not likely to do any heavy exercise although you are able to choose to do so. If you see an explosion in front of you, you are likely to drop to the ground or run away.

I see now (after reading yours and janos’ comments), that my definition isn’t perfect; but I think if you exclude some brain parts and include some other systems, my argument against seeing IQ as external will still hold (at least if your definition still includes brain parts which affect IQ).

Yes, internal locus of control factors such as clothing, diet, or hair style are a major influence on attractiveness, but height; I have never heard anyone make that argument before. How is height under my control or what sort of arguments could be made in favor of such a belief? I recognize you are not actually arguing this is the case, but I’m not sure how you could even consider this to be a plausible argument.

I’m not arguing that height is under your control; that would be strange indeed. But the physical factors are sometimes considered properties of a person, so I included things as height as an example of what considered “internal factor”. I tried to analyse the locus control question in the most general case, that is, define two categories, “internal” and “external” (whatever that actually means), and then find out which is the most important. Basically, I argued that you can’t have IQ in one category and brain in the other.

estimator 5 Apr 2015 10:08 UTC
14 points
on: Cognitive Bias Mnemonics

I know that I’ve read about a number of biases by now, but they don’t come to mind very easily. If I wish to become wary enough to spot cognitive biases in my own thought, then I might appreciate being able to quickly summon many examples of cognitive biases to mind.

You probably don’t need to be able to make a full list of cognitive biases off the top of your head; rather, you need to have relevant memory about biases triggered whenever you encounter a situation where you are prone to them. As for training this, you can, say, open a list of biases at the end of the day, and figure out which biases you were affected by during the day, and try to remember those.

Of course, if you often want to tell others about cognitive biases, memorize a few of them with some good examples.

estimator 5 Apr 2015 10:46 UTC
0 points
in reply to: Thrasymachus’s comment on: Against the internal locus of control
Now, I think that the source of our disagreement are diverging intuitions about free will and IQ.

I think that I can boost my IQ to some extent by exerting willpower; the amount of “thought power” in relaxed, normal and extreme-effort states seem to differ quite substantially.

You may see IQ score as the measure of maximal “thought power” (like when one passes IQ test when fully rested with no distractions and making his best effort); it makes IQ more or less constant, but a worse predictor of success, since success is more determined by average cleverness rather than peak cleverness.

estimator 5 Apr 2015 18:59 UTC
3 points
on: A question on DAG interpretation
Firstly, you can’t have a two-side arrow in DAG (Direct Acyclic Graph), since it creates a cycle of length 2. Also, I’m not sure if “Error” nodes U1 and U2 are necessary: possible errors can be expressed as noise in CPD (in node “W” and “Y” CPD, to be specific). I will assume next, that U1 and U2 nodes were removed, so we don’t have the two-side arrow now.

As for d-separability: you have a direct edge from S to Y; there is no way they can be d-separated.

In general case, the separation set Z is not unique: consider graph A → B → C → D, first set is {A}, second is {D}, and there are multiple sets by which they can be separated: {B}, {C}, {B, C} If you want to find one of them, you can enumerate all the undirected paths from first set of nodes X to the second set of nodes Y, and then separate them, until no non-separated paths are left.

To find out whether two sets of nodes X and Y are d-separated by a set of nodes Z, you can either use the definition of d-separability (i.e. check all paths from X to Y), or the Bayes Ball algorithm.

Note on terminology: this object is called a Directed Graphical Model (DGM) or a Bayesian network, or a belief network, or a causal network. Sure, DGMs are DAGs, but not all DAGs are DGMs; DAG is a far more general term.

P. S. Why Lesswrong, and not, say, StackExchange?

estimator 5 Apr 2015 20:25 UTC
0 points
in reply to: Gunnar_Zarncke’s comment on: A question on DAG interpretation
Well, every instrument has its purpose. Why post a question here and have to include apologizing disclaimer and be downvoted and wait a few hours for a single answer if you can go to a specialized questions/answers site where you’ll be welcome and will have your answer in minutes?

P. S. I have neither downvoted nor upvoted this post.

estimator 5 Apr 2015 22:45 UTC
2 points
on: In what language should we define the utility function of a friendly AI?
Yes, FAI problem is an overfitting problem; you have a vast space of parameters (all the algorithms, if you consider the general case).

No matter how well you specify your values, your description can be hacked if it is expressed in a language which has enough room for different interpretations of the same expression. Even programming languages probably aren’t strict enough, since they sometimes have “implementation-specific” or “undefined behavior” expressions. So when you say “high-level”, you should mean “high-level as Haskell”, not “high-level as natural languages”.

And then good luck defining your values, e.g. love, in a programming language.

estimator 5 Apr 2015 23:16 UTC
0 points
in reply to: Val’s comment on: In what language should we define the utility function of a friendly AI?
Declarative languages, maybe? like Prolog.

People certainly have motivation to create programming languages as high-level as possible, as using such languages reduces development costs. So there are languages which are more or less directly optimized for high-levelness, like Python.

On the other hand, programming languages design is limited by the fact that programs on it must actually work on real computers. Also, most effort in creating programming languages is directed to imperative ones, as they are usually more convenient for programming purposes.

But still, programming languages seem to be the humanity’s best effort at creating rigorous enough languages. There are other approaches, like logical artificial languages (e.g. Loglan), but I think they are still too imprecise for FAI purposes.

estimator 7 Apr 2015 16:34 UTC
0 points
on: Is Belief in Belief a Useful Concept?
Translating to your terminology, belief in belief concept states that:
- All beliefs are what you call quasi-bayesian beliefs
- When a person “chooses” to believe something, he/she often ends up believing that he/she has that belief.
And it is way more Occam-Razor-compilant, while explaining the same evidence. “Binary Beliefs” is a clearly redundant category; all of its content can be seen as high-confidence quasi-bayesian beliefs.

As for choosing beliefs: I never chose to believe that the Sun is going to rise tomorrow; in fact, I can’t remember a single “choosing to belief” act of mine. You either think that something is true, or not, and it isn’t a matter of choice, but of plausibility estimation. One can try to override his belief system, but it’s hard, and people usually fail that, ending up with belief in belief, since convincing yourself that you believe in something is easier than convincing yourself that something is actually true—it requires less overriding.

estimator 7 Apr 2015 18:09 UTC
0 points
in reply to: Unknowns’s comment on: Is Belief in Belief a Useful Concept?
Then I can’t see any significant difference between your model and belief-in-belief model, which you claim to oppose.

It seems to me that what we usually call belief in belief basically means that someone holds a binary belief together with a quasi-Bayesian belief which conflicts with it.

Now it seems to be the definition of belief-in-belief, written in obscure terminology. Replace “quasi-Bayesian belief” to “actual belief”, and “holds a binary belief” to “acts as if he had a belief” and that’s it.

estimator 10 Apr 2015 17:13 UTC
4 points
in reply to: polymathwannabe’s comment on: What level of compassion do you consider normal, expected, mandatory etc. ?
What if your estimate of other person’s defection is 90%? 95%? 99%? What if he explicitly stated that he won’t cooperate? What if you are Omega, and can make the prediction with 100% accuracy?

estimator 10 Apr 2015 19:20 UTC
3 points
in reply to: [deleted]’s comment on: If you could push a button to eliminate one cognitive bias, which would you choose?
I think of science fiction as of sampling from futures-space; so it doesn’t have to be the most probable scenario, just somewhat plausible.

estimator 4 May 2015 10:20 UTC
4 points
in reply to: Houshalter’s comment on: Is Determinism A Special Case Of Randomness?
Any “fundamentally” random process can be seen as a deterministic process. Since it will have a single outcome, we can set it as the only outcome possible, and yield a fully deterministic process which is indistinguishable from the original, random, process. In other words, we can say that a fundamentally random process is a deterministic process which relies on hidden variables which are unreachable for us.

estimator 4 May 2015 21:04 UTC
3 points
in reply to: [deleted]’s comment on: Is Determinism A Special Case Of Randomness?
Note that fundamentally random processes viewpoint and hidden variables viewpoint are equivalent—they produce the same predictions—so choosing one is the matter of convenience.

And hidden variables viewpoint is convenient exactly because it allows to think that probabilities is in the mind, that is, probabilities are nothing but a measure of uncertainty. It eliminates the only special case—fundamentally random processes, thus allowing us to apply our uncertainty-measure concept everywhere. Fundamentally random processes are processes which rely on parameters for which we (fundamentally) can’t reduce our uncertainty, and that’s it.

So yes, I would agree.

estimator 4 May 2015 21:30 UTC
0 points
in reply to: Houshalter’s comment on: Is Determinism A Special Case Of Randomness?
We can’t say. They are hidden; all our hypotheses about them would be unfalsifiable. Moreover, the fundamentally random and hidden variables viewpoints are indistinguishable by experiment, so choosing one is a matter of convenience, not absolute truth.

estimator 5 May 2015 8:52 UTC
1 point
in reply to: [deleted]’s comment on: Is Determinism A Special Case Of Randomness?
As others already mentioned, introducing fundamental randomness doesn’t help in resolving free will problem—whether or not physical processes are truly random, you have no control over them.

You may want to read LW free will sequence.

estimator 5 May 2015 9:58 UTC
0 points
in reply to: Houshalter’s comment on: Is Determinism A Special Case Of Randomness?
Hidden variables aren’t random; they are fixed, but unknown. Maybe we are using different definitions of randomness here. Yet I can’t see why you are comfortable with a hidden deterministic algorithm setting hidden variables; wouldn’t such an algorithm itself be random by your definition?

There is no point in arguing, which of the hypotheses producing the same results is “really true”. We should just pick the simplest one according to the Occam razor. But the simplest hypothesis isn’t just the one which involves less objects (like hidden variables), but rather, the one for which our theories fit with minimal stretch. If you agree with the interpretation of probabilities as a measure of uncertainty, then it’s simpler to use the fundamentally random processes interpretation which fits into this framework—the one with hidden variables.

estimator 6 May 2015 11:33 UTC
8 points
on: Is there a list of cognitive illusions?
These aren’t illusions, even free will; let alone time, money and probability.

Free will concept (as used by anyone but philosophers) makes sense; there are things that are controlled by your conscious processes. For example, now I’m deliberately controlling my arms to type this comment, isn’t it a free will? Of course, I’m entity within physics, my thoughts and actions are fully determined by physics laws (whether random or not), etc, etc. Yet, I can deliberately move my arm.

Probability isn’t an illusion; probability is a measure of uncertainty, and probability theory is a large and very useful field mathematics which supplies us with knowledge about how to use such a nice tool. It’s not an illusion; it’s a mathematical concept.

Time isn’t an illusion; no matter how timeless your physics theory, it must contain explanation for phenomena that you now call time. If you develop a shiny new gravitation theory, apples won’t fall differently. You can a new shiny timeless physics, butwhatever you now call time isn’t going to disappear. It would be explained as a dimension, or as a function of position of all particles in the universe.

As for money, I don’t quite understand why they are considered an illusion at all. I have checked banknotes in my wallet; they are real, as far as I can tell. Did you mean some economical misconceptions?

It all adds up to normality.

estimator

Why IQ shouldn’t be con­sid­ered an ex­ter­nal factor

Why IQ shouldn’t be considered an external factor