Hi Marc,

*/Eliezer/*'s hubris about a Bayesian approach to intelligence is 
nothing more than the usual 'metabelief' about a mathematics... or about 
computation... meant in the sense that "cognition is computation", where 
computation is done BY the universe (with the material of the universe 
used to manipulate abstract symbols) 

*You don't have to work so hard to walk away from that approach...*

Computationalism is FALSE in the sense that it cannot be used to 
construct a scientist.
A scientist deals with the UNKNOWN.
If you could compute a scientist you would already know everything! 
Science would be impossible.
So you *can* 'compute/simulate' a scientist, but if you could the 
science must already have been done... hence you wouldn't want to. 
Computationalism is FALSE in the sense of 'not useful', not false in the 
sense of 'wrong'.

You cannot model a modeller of the intrinsically unknown. As a 
computationalist  manipluator of abstract symbols you are required to 
deliver a model of how to learn - in which you must specify how all 
novelty shall be handled! In other words you can;t deal with the REAL 
unknown - where you have no such model!....

 ie. a computationalist scientist is an oxymoron: a logical 
contradiction. If you say you can then you are question begging 
computationalism whilst failing to predict an a-priori unsupervised 
observer (a scientist).

The Bayesian 'given' (the conditional) assumes knowledge of a given 
which is a-priori not available. It assumes observation of the kind we 
have.. otherwise how would you know any options to choose as 
givens?..... furthermore it assumes that if somehow we were to 
experiment to resolve a choice of 'givens' (Bayesian conditionals) as 
being the 'truth' - then there are potentially an enormous collection of 
'givens', all of which can be inserted in the same bayesian predictor... 
resulting  in degenerate knowledge.... you know NOTHING because you fail 
to resolve anything useful about the world outside. You don't even know 
there's an 'outside'.

The bayesian (all computationalist) approach fails to predict 
observation (in the sense of ANY observation/an observer, not a 
particular observation) and fails to predict the science that might 
result from an observer.

This is the achilles heel of the computationalist argument.

The computationalist delusion (dressed up in Bayesian or any other 
abstract symbol-manipulator's clothes) has to stop right here, right now 
and for good.

BTW This does not mean that 'cognition is not computation'.... I hold 
that cognition is NATURAL symbol manipulation, not ABSTRACT symbol 
manipulation. But that's a whole other story... The natural symbols are 
the key.

Please feel free to deliver the above to Eliezer. He'll remember me! 
Tell him the AGI he is so fearful of are a DOORSTOP and will be 
pathetically vulnerable to human intervention. The whole AGI 
fear-mongering realm needs to get over themselves and start being 
scientific about what they do. It's all based on assumptions which are 


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