Or: Surprisal value is the new value
Here is a lovely example of end-to-end information channel testing. Apparently, there are some naughty apps on your smartphone that will monitor your speech and use it for setting up your web search meta data (that’s so bad from a digital ethics perspective).
If you smartphone-talk about pet lizards and pink VWs with your friend Marge, and then suddenly start seeing both VW and reptile store ads in your news feeds: you’re not paranoid (Well — you could also be paranoid, but that is beside the point being made here). Your smartphone apps might well be parsing your speech (which is bad). Honestly: this is a serious digital ethics issue and shows just how far we have already fallen as a civilisation. However, the technique for detecting such misbehaviour is fascinating, and has many applications.
The idea here is simple, statistical, and straight from applied mathematician Claude E. Shannon’ s 1948 the Mathematical Theory of Communication (which statistical theory is still the basis of every communication channel that you use — including your smartphone). The more unlikely a message is overall (to occur), coupled with the more unlikely it is that it matches a previously produced message from a known, prior source: the less likely it is a random occurrence.
If you make up a nonsense phrase like “Unicorn phantabula scudders” in a private message, and it comes back to you several days later via the internet/Web: this is definitely not random. Why, because BOTH the syntax and the semantic content (meaning) are very unlikely given the set of known codes, alphabets, and ‘dictionaries’ of English (even ‘Phantabula scudders’ is extremely unlikely since it has never been recorded in any English text prior to my conjuring it up.)
This is makes for a very powerful and extremely useful tool for detecting hidden information channels and tracing the origin of concepts and terms. For example, you could use this — coupled with Google — to easily determine where the original (shorter) post of this article lives. Can you imagine two people purely accidentally coming up with the exact same neologism-packed line from Lewis Carroll’s ‘Jabberwocky’? (Not if you are not stupid, high, or being a nuisance.)
This is also heuristically and intuitively coherent. It is an outcome that you can guess at unaided by Shannon’s statistical theory because your brain is deploying its own approximate form of predictive, subjective Bayesian updating (roughly — setting your expectations based upon your prior information about how natural language works) to do it.
Shannon’s theory is not Bayesian, nor based upon subjective Bayesian probabilities. It uses frequentist statistics, or frequentism. Frequentism is about counting and ratios rather than updating prior probabilities based on new information as is the fashion with Bayesians. Yet both can kinds of probability can be applied to the situation of interest here.
(For the cognitive scientists out there: I don’t think that the brain literally has a Bayesian inference module that does literal Bayesian calculations. However, its operation when noticing how surprising a phrase or lexical string is can be fruitfully modelled with Bayesian theory.)
The more complex — and the more ‘nonsensy’ — your smartphone-thumbed or blog-inputted phrase, the surer you can be it is not a random occurrence for it (‘phantabula scudders’) to come back to you on the internet through an unrelated channel.
This works for unusual concepts that use familiar English words too. The same principles are applicable, although concepts are probably more difficult to analyse in frequentist terms the way Shannon’s theory does it. This is because there is no digital repository of concepts available for Google (and similar systems) to search to establish a set of frequency scores for each concept as can be done with English words (for which latter application a good online or digital dictionary and a digital library of English books will do.)
It particularly works for neologisms in science fiction texts that constitute what science fiction theorist Darko Suvin would have called a ‘novum’ (Suvin’s own neologism). A novum is a science-fictional ideation or invention that constitutes a plot device. A good example is Ursula K Le Guin’s ‘ansible’, which is a device (and a plot device) in her novel Rocannon’s World which is used for sending messages through spacetime at any distance instantaneously (which would require superluminal signal transmission speeds!)
In other words: it’s going to be easy for a science fiction writer to determine if you have stolen their script. Especially if they use a lot of novum neologisms. (You had better get cracking changing the names of — well — everything. That, in my experience, is what philosophers who steal other scholars’ ideas do!)
Importantly, however, Le Guin’s ansible is an overall less certain example of the kind of statistically surprising novum terms and messages that we are interested in. Why? Because it is less statistically — and subjectively — surprising as a concept in the context of the corpus of science fiction literature: the entire set of science fiction texts. Many science fiction authors (both dead and alive) are interested in the trope of sending messages (or objects) through time, and in time travel, astral projection, and other science fiction and fantasy themes like these.
Thus, although the name ‘ansible’ is very statistically unlikely even in the science fiction genre and corpus: ansible-like devices and meaning are quite common in science fiction (although kudos — and deserved popularity — goes to Le Guin for the ansible because it was unique when she invented it, and it also ‘anticipated’ debates about superluminal information transmission in quantum physics more than two decades later!) The syntax is very unlikely, but the semantic content of such a novum term in the context of the science fiction genre and its texts is somewhat likely in terms of frequency of occurrence: in frequentist statistical terms.
Nonetheless, a novum neologism is a good marker of the novum concept because words and concepts go together an awful lot in natural language. So much so that the basis of all psychometric instruments for measuring personality in psychology are based entirely upon lexical analysis of terms corresponding to concepts of personality traits in English dictionaries! (The results of which analyses are then fed into a more mathematically sophisticated correlational factor-analysis.)
So, a novum neologism’s conceptual content and semantic content is less unlikely for science fiction fans and writers (and literary theorists) as an audience — and individually — when analysed and appraised in subjective Bayesian-updating terms (based upon prior probabilities for certain types of concepts and conceptualisation.) Science fiction readers already have elevated subjective prior probabilities — or expectations — for such concepts. Nevertheless, the more surprising it is conceptually the better it is in aesthetic and literary terms.
Still, a novum neologism — the string of letters — and its accompanying concept(s) are statistically unlikely in frequentist statistical terms when the entire corpus of English literary works and non-fiction writing is used to do the string-frequency counting (the ratio of the number of occurrences of ‘ansible’ to other words when one adds all the English texts ever written together.) It has what philosopher of information Fred Dretske called high ‘surprisal’ value.
In a frequentist sense you are statistically surprised to encounter the improbable lexical string and its meaning. This translates coherently into a Bayesian subjective probability interpretation too, although Dretske did not pursue that approach much. You’re subjectively surprised to see the novum based upon your existing subjective probabilities for such outcomes. Novum neologisms and concepts have high surprisal value.
Suvinian novums are a big part of the basis of the intertextual-aesthetic, scientistic-aesthetic, and cultural-textual appeal of science fiction literature in subgenres like cyberpunk, hard science fiction, and informationist science fiction. In literary terms — both on the frequentist basis and applying a more Bayesian assessment — there is an aesthetic effect associated with high surprisal novums. The more surprising the term and concept are (although it’s clearly mostly about the concepts) the more aesthetically appealing the literary work.
Luddites don’t want to be surprised by nasty technology and science. Science fiction fans, on the other hand, are after that technovum-surprisal-rush. (Hey look. I did another neologism. This one — ‘technovum’ — seems to belong to my weird and arcane science fiction literary theory oeuvre. Apologies to Suvin are in order, probably. I tell you what though: if I see ‘technovum’ anywhere else then I am sending the killer robots around to remonstrate with the offending party. Unless there’s a citation to this phantabulogorical post, that is, in which case: ansible-transmitted virtual love and hugs in advance.)
Science fiction readers enjoy being surprised by scientistic technical, conceptual, and lexical invention — especially when it helps deliver up a highly inventive plot. When a novum with high surprisal value is also a good plot device that increases the inventiveness of the overall plot, character construction, and mise-en-scène then the science fiction text has a good chance of becoming famous literature. Such novums constitute a unique aesthetic that fits with the scientistic trope of the ‘eureka moment’ and the spirit of scientific discovery, which are element of the paradigm, scientistic cultural aesthetic of science fiction.
However, if you’re writing some amazing Michael-Verhoeven-grade informationist science fiction and you novum-up a barabulous neurampusplat or a zardoogifier (personally I don’t really recommend those, specifically) and these nifty neologisms and their accompanying concepts (the mind boggles) come back at you in someone’s blog post or movie script: you’ve very likely been hacked by a hack!
In lieu of a reference list, here is a copy of the Bibliography from my 2009–10 Master of Philosophy thesis Informationist Science Fiction Theory and Informationist Science Fiction.
B i b l i o g r a p h y
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