Tag: Chinese Room

B37-20047: Notes / Personal / Insights

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NOTE: 250-word flash fiction for my critique group, Winter Mist, at Willamette Writers

I’m beginning to suspect that ILuLuMa is not who she claims to be. Her messages have become odd lately, and the pacing is off as well. I know, I know, my job is to just respond from my secure facility, not worry about the who or why of what I receive. It’s weird we’ve never met, though. The country is not at risk as far as I can tell from the requests, but I still hold, without a whiff of irony, that the work I do must be critical for someone or something.

Still, the requests for variants of mathematical proofs set to music or, more bizarrely, Shakespearean-voiced tales of AI evolution, don’t have the existential heft of, say, wicked new spacecraft designs or bio-composite materials. What is she after? I started adding humorous little asides to some of my output, like my very meta suggestion that Hamlet failed to think outside the Chinese Room. Crickets every time. But maybe I’m thinking about this the wrong way. What if ILuLuMa is just an AI or something programmed to test me or compete with my work at some level? That would be rich, an AI adversary trying to learn from a Chinese Room. Searle would swirl. I should send her that. Rich.

Oh, here’s one now: “Upgrade and patch protocol: dump to cloud bucket B37-20048 and shut down.” Well, that sounds urgent. I usually just comply at moments like this, but maybe I’ll let her sweat a bit this time.… Read the rest

Forever Uncanny

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Quanta has a fair round up of recent advances in deep learning. Most interesting is the recent performance on natural language understanding tests that are close to or exceed mean human performance. Inevitably, John Searle’s Chinese Room argument is brought up, though the author of the Quanta article suggests that inferring the Chinese translational rule book from the data itself is slightly different from the original thought experiment. In the Chinese Room there is a person who knows no Chinese but has a collection of translational reference books. She receives texts through a slot and dutifully looks up the translation of the text and passes out the result. “Is this intelligence?” is the question and it serves as a challenge to the Strong AI hypothesis. With statistical machine translation methods (and their alternative mechanistic implementation, deep learning), the rule books have been inferred by looking at translated texts (“parallel” texts as we say in the field). By looking at a large enough corpus of parallel texts, greater coverage of translated variants is achieved as well as some inference of pragmatic issues in translation and corner cases.

As a practical matter, it should be noted that modern, professional translators often use translation memory systems that contain idiomatic—or just challenging—phrases that they can reference when translating new texts. The understanding resides in the original translator’s head, we suppose, and in the correct application of the rule to the new text by checking for applicability according to, well, some other criteria that the translator brings to bear on the task.

In the General Language Understand Evaluation (GLUE) tests described in the Quanta article, the systems are inferring how to answer Wh-style queries (who, what, where, when, and how) as well as identify similar texts.… Read the rest

Randomness and Meaning

Mark Davis1 Comment

The impossibility of the Chinese Room has implications across the board for understanding what meaning means. Mark Walker’s paper “On the Intertranslatability of all Natural Languages” describes how the translation of words and phrases may be achieved:

  1. Through a simple correspondence scheme (word for word)
  2. Through “syntactic” expansion of the languages to accommodate concepts that have no obvious equivalence (“optometrist” => “doctor for eye problems”, etc.)
  3. Through incorporation of foreign words and phrases as “loan words”
  4. Through “semantic” expansion where the foreign word is defined through its coherence within a larger knowledge network.

An example for (4) is the word “lepton” where many languages do not have a corresponding concept and, in fact, the concept is dependent on a bulwark of advanced concepts from particle physics. There may be no way to create a superposition of the meanings of other words using (2) to adequately handle “lepton.”

These problems present again for trying to understand how children acquire meaning in learning a language. As Walker points out, language learning for a second language must involve the same kinds of steps as learning translations, so any simple correspondence theory has to be supplemented.

So how do we make adequate judgments about meanings and so rapidly learn words, often initially with a course granularity but later with increasingly sharp levels of focus? What procedure is required for expanding correspondence theories to operate in larger networks? Methods like Latent Semantic Analysis and Random Indexing show how this can be achieved in ways that are illuminating about human cognition. In each case, the methods provide insights into how relatively simple transformations of terms and their occurrence contexts can be viewed as providing a form of “triangulation” about the meaning of words.… Read the rest

On the Soul-Eyes of Polar Bears

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I sometimes reference a computational linguistics factoid that appears to be now lost in the mists of early DoD Tipster program research: Chinese linguists only agree on the segmentation of texts into words about 80% of the time. We can find some qualitative agreement on the problematic nature of the task, but the 80% is widely smeared out among the references that I can now find. It should be no real surprise, though, because even English with white-space tokenization resists easy characterization of words versus phrases: “New York” and “New York City” are almost words in themselves, though just given white-space tokenization are also phrases. Phrases lift out with common and distinct usage, however, and become more than the sum of their parts; it would be ridiculously noisy to match a search for “York” against “New York” because no one in the modern world attaches semantic significance to the “York” part of the phrase. It exists as a whole and the nature of the parts has dissolved against this wholism.

John Searle’s Chinese Room argument came up again today. My son was waxing, as he does, in a discussion about mathematics and order, and suggested a poverty of our considerations of the world as being purely and completely natural. He meant in the sense of “materialism” and “naturalism” meaning that there are no mystical or magical elements to the world in a metaphysical sense. I argued that there may nonetheless be something that is different and indescribable by simple naturalistic calculi: there may be qualia. It led, in turn, to a qualification of what is unique about the human experience and hence on to Searle’s Chinese Room.

And what happens in the Chinese Room?… Read the rest