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AI, Academic Journals, and Obfuscation

21 Apr

A common complaint about the structure for publishing and distributing academic journals is that it is designed in such a way that it obfuscates and obscures the true bleeding edge of science and even the humanities.  Many an undergrad has complained about how they found a dozen sources for their paper, but that all but two of them were behind absurd paywalls.  Even after accounting for the subscriptions available to them through their school library.  One of the best arguments for the fallacy that information wants to be free is the way in which academic journals prevent the spread of potentially valuable information and make it very difficult for the indirect collaboration between multiple researchers that likely would lead to the fastest advances of our frontier of knowledge.

In the corporate world, there is the concept of the trade secret.  It’s basically a form of information that creates the value in the product or the lower cost of production a specific corporation which provides that corporation with a competitive edge over other companies in its field.  Although patents and trade secret laws provide incentive for companies to innovate and create new products, the way academic journals are operated hinders innovation and advancement without granting direct benefits to the people creating the actual new research. Rather, it benefits instead the publishing company whose profit is dependent on the exclusivity of the research, rather than the value of the research itself to spur scientific advancement and create innovation.

Besides the general science connection, this issue is relevant to a blog like the Chimney because of the way it relates to science fiction and the plausibility and/or obsolescence of the scientific  or world-building premise behind the story.

Many folks who work  in the hard sciences (or even the social sciences) have an advantage in the premise department, because they have knowledge and the ability to apply it at a level an amateur or  a generalist is unlikely to be able to replicate.  Thus, many generalists or plain-old writers who work in science fiction make use of a certain amount of handwavium in their scientific and technological world-building.  Two of the most common examples of this are in the areas of faster-than-light(FTL) travel (and space travel in general) and artificial intelligence.

I’d like to argue that there are three possible ways to deal with theoretical or futuristic technology in the premise of  an SF novel:

  1. To as much as possible research and include in your world-building and plotting the actual way in which a technology works and is used, or  the best possible guess based on current knowledge of how such a technology could likely work and be used.  This would include the possibility of having actual plot elements based on quirks inherent in a given implementation.  So if your FTL engine has some side-effect, then the world-building and the plot would both heavily incorporate that side-effect.  Perhaps some form of radiation with dangerous effects both dictates the design of your ships and the results of the radiation affecting humans dictates some aspect of the society that uses these engines (maybe in comparison to a society using another method?)  Here you are  firmly in “hard” SF territory and are trying to “predict the future” in some sense.
  2. To say fuck it and leave the mechanics of your ftl mysterious, but have it there to make possible some plot element, such as fast travel and interstellar empires.  You’ve got a worm-hole engine say, that allows your story, but you don’t delve into or completely ignore how such a device might cause your society to differ from the present  world.  The technology is a narrative vehicle rather than itself the reason for the story.  In (cinematic) Star Wars, for example, neither the Force nor hyper-drive are explained in any meaningful way, but they serve to make the story possible.
  3. A sort of mix between the two involves  obviously handwavium technology, but with a set of rules which serve to drive the story. While the second type is arguably not true speculative fiction, but just utilizes the trappings for drama’s sake, this type is speculative, but within a self-awarely unrealistic premise.

 

The first type of SF often suffers from becoming dated, as the theory is disproven, or a better alternative is found.  This also leads to a possible forth type, so-called retro-futurism, wherein an abandoned form of technology is taken beyond it’s historical application, such as with steampunk.

And therein lies a prime connection between our two topics:  A\a technology used in a story may already be dated without the author even knowing about it.  This could be because they came late to the trend  and haven’t caught on to it’s real-world successor; it could also be because an academic paywall or a company on the brink of releasing a new product has kept the advancement private from the layperson, which many authors are.

Readers may be surprised to find that there’s a very recent real-world example of this phenomenon: Artificial Intelligence.  Currently, someone outside the field but who may have read up on the “latest advances” for various reasons might be lead to believe that deep-learning, neural networks, and  statistical natural language processing are the precursors or even the prototype technologies that will bring about real general/human-like artificial intelligence, either  in the near or far future.

That can be forgiven pretty  easily, since the real precursor to AI is sitting behind a massive build-up of paywalls and corporate trade secrets.  While very keen individuals may have heard of the “memristor”, a sort of circuit capable of behavior  similar to a neuron, this is a hardware innovation.  There is  speculation that modified memristors might be able to closely model the activity of the brain.

But there is already a software solution: the content-agnostic relationship  mapping, analysis, formatting, and translation engine.  I doubt anyone reading this blog has ever heard of it.  I would indeed be surprised if anyone at Google or Microsoft had, either.  In fact, I only know it it by chance, myself. A friend I’ve been doing game design with on and off for the past few years told me about it while we were discussing the AI  model used in the HTML5 tactical-RPG Dark Medallion.

Content-agnostic relationship mapping is a sort of neuron simulation technology that permits a computer program to learn and categorize concept-models in a way that is similar to how humans do, and is basically the data-structure underlying  the software “stack”.  The “analysis” part refers to the system and algorithms used to review and perform calculations based on input from the outside world.  “Formatting” is the process of  turning the output of the system into intelligible communication–you might think of this as analogous to language production.  Just like human thoughts, the way this system “thinks” is not  necessarily all-verbal.  It can think in sensory input models just like a person: images, sounds, smells, tastes, and also combine these forms of data into complete “memories”.  “Translation” refers to the process of converting the stored information from the underlying relationship map into output mediums: pictures, text, spoken language, sounds.

“Content agnostic” means that the same data structures can store any type of content.  A sound, an image, a concept like “animal”: all of these can be stored in the same type of data structure, rather than say storing visual information as actual image files or sounds as audio files.  Text input is understood and stored in these same structures, so that the system does not merely analyze and regurgitate text-files like the current statistical language processing systems or use plug and play response templates like a chat-bot.  Further, the system is capable of output in any language it has learned, because the internal representations of knowledge are not stored in any one language such as English.  It’s not translation, but rather spontaneous generation of speech.

It’s debatable whether this system is truly intelligent/conscious, however.  It’s not going to act like a real human.  As far as I understand it, it possesses no driving spirit like a human, which might cause it to act on its own.  It merely responds to commands from a human.  But I suspect that such an advancement is not far away.

Nor is there an AI out there that can speak a thousand human languages and program new AIs, or write novels.  Not yet, anyway.  (Although apparently they’ve developed it to the point where it can read a short story and answer questions about it, like the names of the main characters or the setting. ) My friend categorized this technology as somewhere between an alpha release and a beta release, probably closer to alpha.

Personally, I’ll be impressed if they can just get it reliably answering questions/chatting in English and observably learning and integrating new things into its model of the world.  I saw some screenshots and a quick video of what I’ll call an fMRI equivalent, showing activation of the individual simulated “neurons”* and  of the entire “brain” during some low-level tests.  Wikipedia seems to be saying the technical term is “gray-box testing”, but since I have no formal software-design training, I can’t say if I’m mis-uderstanding that term or not.   Basically, they have zoomable view of the relationship map, and when the program is activating the various nodes, they light on the screen.   So, if you ask the system how many legs a cat has, the node for cat will light up, followed by the node for “legs”, and maybe the node for “possession”.  Possibly other nodes for related concepts, as well.  None of the images I saw actually labelled the nodes at the level of zoom shown, nor do I have a full understanding of how the technology works.  I couldn’t tell anyone enough for them to reproduce it, which I suppose is the point, given that if this really is a useable technique for creating AIs, it’s probably worth more than the blog-platform I’m writing this on or maybe even all of  Google.

 

Getting back to our original topic, while this technology certainly seemed impressive to me, it’s quite possible it’s just another garden path technology like I believe statistical natural language processing to be.  Science fiction books with clear ideas of how AI works will work are actually quite few and far between.  Asimov’s Three Laws, for example, are not about how robot brains work, but rather about  higher-level things like will AI want to harm us.  In light of what I’ve argued above, perhaps that’s the wisest course.  But then again, plenty of other fields  and technologies are elaborately described in SF stories, and these descriptions used to restrict and/or drive the plot and the actions of the characters.

If anyone does have any books recommendations that do get into the details of how AI works in the story’s world,I would love to read some.

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