U.S. Plan For "Thinking Machines" Repository

An anonymous reader writes "Information scientists organized by the US's NIST say they will create a "concept bank" that programmers can use to build thinking machines that reason about complex problems at the frontiers of knowledge — from advanced manufacturing to biomedicine. The agreement by ontologists — experts in word meanings and in using appropriate words to build actionable machine commands — outlines the critical functions of the Open Ontology Repository (OOR). More on the summit that produced the agreement here."

Ok, humanity is screwed

[Crayboff]

Wow, this can be scary. I hope the US is investing in a primitive non-computerized emergency plan to destroy this project, in case of the uprising. There has to be strict limitations placed on this sort of system, not just 3 rules. This is one time when the lessons learned from fictional books/movies would come in handy. I'm serious too.

Not about thinking machines

[clang_jangle]

The summary isn't terribly clear, but according to TFA:

The ontology wordsmiths envision an electronic OOR in which diverse collections of concepts (ontologies) such as dictionaries, compendiums of medical terminology, and classifications of products, could be stored, retrieved, and connected to various bodies of information. OOR users, tasked with creating a computer program for manufacturing machines, for example, would be able to search multiple computer languages and formats for the unambiguous words and action commands. Plans call for OOR's inventory to support the most advanced logic systems such as Resource Description Framework, Web Ontology Language and Common Logic, as well as standard Internet languages such as Extensible Markup Language (XML).

It's merely intended as a convenient resource for programmers.

Re:Ok, humanity is screwed

[geekoid]

You don't need to understand to think.
Thinking doesn't mean cognition either.

Re:Every few years the same thing.

[somersault]

What reason do you have to believe that all efforts will fail? A computer powerful enough to simulate all the cells in a brain would presumably be able to do everything a brain can do? Brains are like blank slates then take 25 years of training before they are regarded as fit for specialised jobs - a computer that was capable of forming semantic links and organising them properly would be able to give the illusion of understanding, and in fact can do a passable job in limited domains (thinking about for example medical 'knowledge base' type systems which take symptoms and work out possible causes). It is beyond our current understanding to build a proper thinking computer, but that doesn't mean we shouldn't work towards it. If we did it properly then we really would be able to build computers that could work out logical and more objective conclusions for problems (given enough factual input data to allow it to make unbiased 'decisions').

Unless you want to say that there is some mystical element to brains, there is nothing precluding the eventual design and building of 'sentient' computers, surely? Beyond our own fear of what would happen if we did such a thing, as evidenced by plenty of 20th century fiction. Building sentient computers could even be regarded as a type of evolution, as they would then be able to improve upon themselves at an exponential rate..

Re:Every few years the same thing.

[FleaPlus]

Actually the researchers themselves aren't saying anything at all about "thinking machines" -- that was just added by the blog summary. In fact, if you had read the document describing their plans [cim3.net], you would have seen that it doesn't even include the words "thinking," "AI," or "intelligence." All they want to do is create an Internet-accessible database of ontologies and ways for ontology-related services to interoperate. Your smears of them as "unethical" and "parasites" are completely uncalled for.

You forgot to mention something...

[Estanislao Martínez]

You forgot to mention that it will fail for the exact same reasons that Good Old-Fashioned AI has always failed. All the classifications in the ontology, when actually applied to any real-world problem, will turn out to be unexpectedly and hopelessly fragile.