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Old 05-28-2009, 06:30 PM
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Default Discuss 73. Skeptoid’s Brian Dunning Finds Global Consciousness Project Lacking

I posted this yesterday... transcipt is there too:
73. Skeptoid’s Brian Dunning Finds Global Consciousness Project Lacking

Guest: Brain Dunning, host of the popular Skeptoid Podcast, joins Alex Tsakiris to discuss how skeptics view the Global Consciousness Project.

Last edited by alextsakiris; 05-28-2009 at 08:16 PM.
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Old 05-30-2009, 08:58 AM
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I said in my other thread that I was looking forward to this show, and it didnt disappoint

I have been listening to Brian Dunning for a long time (just about every show), and I have always enjoyed his content in spite of irritated by his "presentation style" - It always felt like he was overly dismissive in areas where there is clearly a debate (he has an episode about big oil for example). Safe to say I thought he would come into this show with guns blazing in the same way that he responds to "listener comments"

During the interview, he came across as a much "nicer" person, and it was really interesting to hear his motivation (giving people the opportunity to look at things in a different way, to paraphrase) - I can say he has done this many times (Marfa lights, one about nuclear power, another one about some hikers in russia)

When he first put out his random number generator podcast (or maybe a few weeks before) I joined his mailing list and we traded a few emails - I think he got really exasperated by the discussion on PSI/Ganzfeld, and eventually said (in his email discussion) that he was not willing to believe any of it - Nice to see the topic rise again -

I love Dean Radin's work - I can't wait to see what he says in the next episode (I havent read it yet) - But Brian came accross as a really decent guy - "props" to him

Last edited by fabkebab; 05-30-2009 at 09:01 AM.
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Old 05-30-2009, 09:44 AM
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Quote:
Originally Posted by fabkebab View Post
It always felt like he was overly dismissive in areas where there is clearly a debate (he has an episode about big oil for example).
What was he overly dismissive of in the big oil episode?

Quote:
When he first put out his random number generator podcast (or maybe a few weeks before) I joined his mailing list and we traded a few emails - I think he got really exasperated by the discussion on PSI/Ganzfeld, and eventually said (in his email discussion) that he was not willing to believe any of it
Did he say why he wasn't willing to believe any of it?
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Old 05-30-2009, 10:39 AM
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Default 73. Skeptoid?s Brian Dunning Finds Global Consciousness Project Lacking (Podcast)

Brain Dunning of Skeptoid Podcast discusses the Global Consciousness Project.

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Old 05-30-2009, 12:59 PM
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It is a while since I listened to the "big oil" podcast, so I am going to probably make a mistake here, but I will try my best.

I believe the premise of the show was about how interests in the oil of Iraq was not a factor in the iraq war- OK - but one of the things he says is that middle eastern oil is not important to us, because our oil comes from other sources (Venezuela, Canada, domestic production, etc) -

I dont disagree with what he says about the current situation- but the two major international agencies (EIA and IEA) both say that as time goes by, a lot of the smaller players will run out of oil, and that the middle east will become increasingly dominant as an oil provider (they have by far the biggest reserves) - So to talk about the current state of affairs is not relevant to how oil considerations play into a larger strategy - for that you have to look at projections.

Sorry if that sounds tedious and long winded, I tried to be concise - The thing is in this topic I didnt believe he did the casual listener great service (I have a background which touches on oil and gas) because he didnt look at things deeply enough before making his mind up and assuming himself to be correct

As for the email exchange - I dont have the exact quote because I dont have the message - It was something where he said he wasnt a skeptic : he was by his own admission dismissive (or something like that!! Sorry if I am putting words in someones mouth by not having the exact quotation!!) - I dont have the exact mail any more, but after I read that comment I gave up on the skeptoid mailing list because it ceased to be interesting as a debating place - but I still enjoy the podcasts. The mail exchange was sometime between 15 march 2007 and 30 april 2007, if you have access to the archives and are really interested
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Old 05-30-2009, 11:32 PM
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I must say I have only just listened to the Nelson interview podcast, that probably puts my comments into some perspective (the ones about Brian's comment in his email discussion newsletter thing)
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Old 07-04-2009, 08:41 AM
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What do people think of the results of the GCP?

Dunning's criticisms are essentially correct but don't come across well in this podcast. Partly because some are met with misleading replies that don't hold up under scrutiny.
I was considering writing a rebuttal to some points but I am not sure if there is a point in going through with it.
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Old 07-04-2009, 09:39 AM
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Quote:
Originally Posted by Miguel View Post
What do people think of the results of the GCP?

Dunning's criticisms are essentially correct but don't come across well in this podcast. Partly because some are met with misleading replies that don't hold up under scrutiny.
I was considering writing a rebuttal to some points but I am not sure if there is a point in going through with it.
yes, please do.
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Old 07-05-2009, 11:31 AM
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Alright. First some essential background:
1: You cannot measure randomness.
2: Random does not mean uniform

By tossing a coin and converting the heads/tails to 1s/0s you might get these sequences:
1010011010
1111100000
Which one is more likely? The answer is, of course, that they are exactly equally likely.
Now someone might point to the apparent pattern in the 2nd sequence. Don't be fooled by that. If we discarded those sequences with "patterns" then the data would no longer be random because we made a conscious selection.
Depending on how hard we look and how the data is presented a pattern may be more likely than a non-pattern. (See: Clustering illusion)

One last thing to bear in mind is the importance of how the data is interpreted. Let's say you treat those binary sequences as numbers and convert them to decimal:
666
992
Suddenly the innocent first sequence turns into the ominous number of the beast while the 2nd sequence becomes inconspicuous.
Obviously this would change yet again if we were to reverse the conversion of head/tails into 0s/1s and so on...

Let's turn to the GCP now:
Their Random Number Generators (RNGs) produce 1s and 0s. Like tossing a lot of coins very fast and converting to 1s and 0s.
Then they count how many 1s they got.
Each of their RNGs does 200 "tosses"per second. Mathematically one expects 100 1s. Mind: "Expects" is mathematical jargon!
It means that if you generate a few million (or more, the more the better) seconds of data then you will find that the average number of 1s per second approaches 100.
However: In less than 6% of all seconds will the number be actually exactly 100.
IE in any ordinary sense we don't expect exactly 100.

It's still the case that any specific combination of 1s and 0s is equally likely. There simply are more combinations with 100 1s than, for example, 200 (for which there is only 1 combination). Basically when we analyse the data like that we lump together a lot of combinations simply based on how many 1s they have and that is why some outcomes end up more likely than others.
In the above examples we have an equal number of 1s which means that this way of analyzing would not distinguish between the two.

The more 1s there are in a set period of time, the fewer combinations there are that have still more 1s. IE the less often you will get more 1s and this then is taken (by the GCP) to indicate that something is going on.

Before we go on I must explain why multiple analysis is a problem:
To do this I am going to talk about throwing dice instead of coins. We can easily translate the results of any sufficiently large number of coin throws into a dice throw. We just make a table which maps 1/6th of all combination to each side of a dice. This will only be an approximation but it will be arbitrarily close.

Throw the dice. Let's say you get a 3. What are the chances? 1/6th obviously. How amazing that we should have gotten this number instead of any other... But wait we could have said the same with any other number so this is obviously fallacious.
It's surely not noteworthy that a dice should land at all. Only if the number is somehow called in advance is there any reason to take note.
And what if we call 1 number but throw more than 1 dice? Certainly puts a hit in perspective. And more importantly: If we were using coins instead and translating the results with a table we could get 2 throws in 1 simply by changing the table.

When you're only looking at how many 1s you get you can also use the same data for multiple "throws" for example by looking at different time periods.

I hope that's enough basics to understand the basic problems with the GCP.


Let's get to some concrete instances now:

911
What Brian Dunning said:
Basically, when something happens, like 911 happened, they then went back to their data, they looked at the data from that period, and they tried very hard to find a pattern. By using the right statistical controls, carefully chosen statistical controls, it is easy to find just about any kind of pattern you want. That’s basically what they’re doing.
I hope that my introduction gives enough background so that one may realize why this is bad.
On his show's site Dunning gives this quote:
We show that the choice was fortuitous in that had the analysis window been a few minutes shorter or 30 minutes longer, the formal test would not have achieved significance... We differ markedly with regard to the posted conclusions. Using Radin’s analysis, we do not find significant evidence that the GCP network’s EGG’s responded to the New York City attacks in real time. Radin’s computation of 6000:1 odds against chance during the events are accounted for by a not-unexpected local deviation that occurred approximately 3 hours before the attacks. We conclude that the network random number generators produced data consistent with mean chance.
From: http://www.lfr.org/LFR/csl/library/Sep1101.pdf

Here's a quote from Radin that Tsakiris gives:
In any case, several of us have independently re-analyzed certain events like 911 and we get the exact same result.
I think Americans call that being economical with the truth.

How much trust should we have in their analyses of other events that did not receive the same degree of attention?

Furthermore: It simply is not enough that an event was known in advance to happen. The precise "recipe" for the analysis has to be pre-specified.
You can find a pattern in virtually any random data, you just (probably) won't find the same pattern if you look at more of that data (a so-called out-of-sample test).

New year
New year's eve is in some ways ideal to look at. It is a recurring predictable event. There's no question of maybe simply not reporting the analysis if it turns out to be unfavorable.
However, the question is obviously if they always used the same recipe.
The answer is no. They did it right in the last 3 years ('07-'09) but without any remarkable results.
In 2006 they use a different recipe that they developed by 'data mining'. In 2005 they had looked through previous New Year's data for a pattern and then tried to find the same pattern in 06. As one would expect from random data it was not there.
There's more to be said but I don't want to bore people with irrelevant detail. Suffice to say: It’s almost silly to have to go over this stuff repeatedly, because it’s all so spelled-out so darn clearly on the Web site.

IMHO the GCP is fatally flawed as a scientific experiment. An experiment is like asking Mother Nature a Yes/No question.
Practically, there is no way in which the GCP could find a no answer given the way it is set up.
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Old 07-05-2009, 11:34 PM
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I'm still unclear what they think a "statistically significant" variance from random numbers would even mean. Why would our attention have that affect?
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