So, Eric [Charles], 

 

What exactly were the practicial consequences of declaring that Hillary was 
“probably” going to win the election or that a full house was probably going to 
win the pot given she lost and the dealer held a strait flush?  

 

Nick

 

Nicholas Thompson

Emeritus Professor of Ethology and Psychology

Clark University

 <mailto:thompnicks...@gmail.com> thompnicks...@gmail.com

 <https://wordpress.clarku.edu/nthompson/> 
https://wordpress.clarku.edu/nthompson/

 

 

From: Friam <friam-boun...@redfish.com> On Behalf Of Eric Charles
Sent: Saturday, April 18, 2020 12:06 PM
To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Subject: Re: [FRIAM] anthropological observations

 

-------- Nick says --------- Nate constantly says that making such predictions 
is, strictly speaking, not his job.  As long as what happens falls within the 
error of his prediction, he feels justified in having made it.   He will say 
things like, "actually we were right."  I would prefer him to say, "Actually we 
were wrong, but I would make the same prediction under the same circumstances 
the next time.”  In other words, the right procedure produced, on this 
occasion, a wrong result. -----------------

 

Well... so this connects a lot with poker, which I am in the process of 
teaching the 10 year old... If I recall, Nate was giving Trump a 1/3 chance of 
victory, which was much higher than most of the other models at the time. You 
can hardly fault someone because something happened that they said would happen 
2/3 of the time. 

 

If a poker player has a model that predicts a given play to be the best option, 
because it will work 2/3 of the time, and this one time it doesn't work, that 
isn't grounds to say the model failed. 

 

 YOU want the modelers to have models that rarely give anything close to even 
odds. So do I, so I'm sympathetic. But the modeler might prefer a more honest 
model, that includes more uncertainty, for a wide variety of reasons. 


-----------

Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist

American University - Adjunct Instructor

 

 

On Sat, Apr 18, 2020 at 12:17 PM uǝlƃ ☣ <geprope...@gmail.com 
<mailto:geprope...@gmail.com> > wrote:

I think it's interesting that you seemed to have *flipped* your thinking within 
the same post. You restate my point about conceptual metaphors by saying 
models/computation merely *justifies* decisions/rhetoric. Then a few paragraphs 
later, you suggest that's conflating language with thought.

My diatribe to Nick was that he *uses* metaphors/models simply to impute his 
conceptual structure onto Nate. Nick's decision is already made and he wants 
Nate's work to justify it. And the way he *imputes* his conceptual structure 
into Nate's work is through the sloppy use of metaphor. Then when Nate tells 
Nick (indirectly) that Nick's wrong about what Nate's done, Nick rejects Nate's 
objection.

I'm picking on Nick, of course. We all do it. I wish we all did it much less.

On 4/18/20 6:14 AM, Steven A Smith wrote:
> But frankly as often as not, I saw
> them use our work to *justify* the decision they had already made or
> were leaning heavily toward, *apparently* based on larger strategic
> biases. 
> 
> [...]
> 
> As for your gut-level (and often well articulated) mistrust of
> "metaphorical thinking",  you may conflate a belief (such as mine) that
> language is metaphorical at it's base with being a "metaphorical
> thinker".    Metaphor gets a bad rap/rep perhaps because of the
> "metaphorical license" often taken in creative arts (albeit for a
> different and possibly higher purpose).  

-- 
☣ uǝlƃ

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