An AI is an AI is an AI…or not.

Every morning, of late, when I read the news, there is a slew of headlines of what AI has done for us lately.

Just this morning, I read:

Robert Wickham of Salesforce is the source of the last statement, that AI will be the new electricity, once we are done oohing and ahhing. Or being afraid that we will all lose our jobs.

AI, however, is not like electricity. It is not so straight forward. While it may, eventually, be ubiquitous and unconsidered, so far we cannot provide a single and clear definition for what it is, and thus these reductive metaphors create greater confusion than clarity.

In each article ‘AI’ describes something different. Deep learning, neural networks, robotics, hardware, a combination, etc. Even within deep learning or neural networks, the meanings can be different, as can the nuts and bolts. Most media and humans use ‘AI’ as shorthand for whatever suits their context. AI, without an agreed upon definition, but the lack of clarity, differentiation, and understanding does make it very difficult to discuss in a nuanced manner.

There is code, there is data, there is an interface–for inputs and outputs, and all of these are (likely) different in each instantiation.  Most of the guts are proprietary, in the combination of code and data and training. So we don’t necessarily know what makes up the artificial intelligence.

Even code, as shorthand to a layperson, as the stuff that makes computers do what they do, is a broad and differentiated category. In this case, like language, it is used for a particular purpose, so this reduction is perhaps not as dangerous. We’ve never argued that code is going to take over the world, or that rogue code is creating disasters.  As compared to algorithms, a few years ago, and AI, now.

So much of this lumping is a problem? We lump things, such as humans or cats, into categories based on like attributes, but we do have some ways to differentiate them. These may not be useful categories, nationality, breed, color, behavior, gender.  (Even these are pretty fraught of late, so perhaps our categorization schemes for mammals needs some readdressing.)  On the other side, we could consider cancer, an incredibly reductive title for very a broad range of…well of what? Tumor types? Mechanisms? Genetic predispositions? There are discussions, given recent research, as to whether cancer should be a noun, perhaps it is better served as a verb. Our bodies cancer, I am cancering, to show the current activity of internal cellular misbehavior.

What if we consider of this  on the intelligence side, how do we speak of intelligence, artificial or otherwise? For intelligence, like consciousness, in humans, we do not have clear explanations for what it is or how it works. So not perhaps the simplest domain to borrow language from, and apply it to machines.  Neural networks is one aspect, modeled on human brains, but it is limited to the structural pathways, a descriptor of how information travels and is stored.

The choice to use AI to represent such a broad range of concepts, behaviors, and functions concerns me. Even in the set of headlines above, it is difficult to know what is being talked about, from a continuum of visible outputs to robots who speak.  If we cannot be more clear about what we are discussing it is incredibly complicated to make clear decisions, about functions, about inputs, about outputs, data, biases, ethics, and all the things which have broad impacts on society.

I haven’t seen clear work on how we should use this language, and though I worked with IBM Watson for a while on exactly this concern, I can’t say I have a strong recommendation for how we categorize not just what we have now, but, as importantly, what is being built and what will exist in the future. The near future.

I’ll work on this later, as in soon, ways in which to talk about these parts in a public context that are clearer, and allow for growth of creations into a systems model.  Check back!


Grammar checking software, language change, and precursors to the future

Almost 20 years ago I wrote my master’s thesis on ‘Grammar Checking Software as a Tool of Language Change’ or some such title. I’ve since lost track of the paper, it was, in that day, on paper.

I was studing at Georgetown University, and my work focused on language and power, from a sociolinguistic and cultural perspective. I had been using assorted early 90s log files I had collected, from IRC and a forum used at UCSC when I was an undergrad, and assessing markers of power in language in the online environment, watching the evolution of language change, and seeing the ways in which one positioned oneself, via language. One of the areas that particularly interested me, which I delved further into, is how non-native speakers of English marked authority online in an anonymous environment and using a language that was rapidly evolving, often different, in each community.

This work led to me to the early grammar and spelling checkers, and my often curiousity as to why they were so not grammatical. I decided to analyse the grammaticality of the current crop of tools against Fowler’s Modern English Usage. For those non-grammar nerds, Fowler’s is an early 20th century grammar text which is/was the go-to for proper English. As a comparator it had its issues, but those I worked around and wrote about. As I worked through analyzing different software programs, I eventually opted to use on Microsoft Word, due to the enormity of my task.

The outcome of this was that even at its most stringent, the grammar checker was no where near Fowler’s. And at its more casual levels — at the time it had three — the English it was recommending was so odd and so lax that the usage of the tool, in my estimation, would ‘teach’ a user a very different English than one would learn at school.

There was no way this was not purposeful, which led me to many questions, most of which remained unanswered, as MS did not wish to speak to me about them.  At the most basic, I was curious who wrote the program because I felt that no linguist would have built a grammatically incorrect system.  This led me to the hypothesis that the linguists built the systems and the marketers freaked out at all the wavy green and red lines and insisted it have fewer. I would love to have heard more of the inside of this, and if you happened to work on this, I’d love to hear from you.

This has really interesting ramifications for both Americans and non-native English speakers. In general, and in different ways, each can use a boost in grammar, and if you have an authoritative tool telling you that no, you cannot use ‘which’ refering to a cat, it must be ‘that’ then this is a possible shift.  It refuses the use of the passive voice, and other constructs it deemed overly complex. One cannot use a run on sentence nor a fragment.  It flattened, significantly, the ability to be creative in language.

We could say that one could turn this off, or that it could be ignored, but in the course of doing the research, I did eventually become bothered by all the wavy lines and want to change words to adhere to what I called Microsoft English.  Because it was, in fact, a significantly different and evolved English.  One that was being rapidly disseminated by what was becoming the most widely used word processor.

Whether or not Microsoft was attempting to create a new English, or was aware of the possible cultural ramifications, and power structures, that they were creating and/or re-inforcing, changes were happening.

And this was in one language. Years later I went back and re-ran some of my assessments in French, out of curiousity for the formality/informality and what it would recommend, and even in a language which has an Academie to control the language, there were shifts away from the rulings. So perhaps in most languages we see changes due to the judgments of software, and then these likely flow into society, because we do learn from software.

I doubt most people have considered this, that the language promoted by their grammar checking software is ‘wrong’ or at the very least, not a standard, until they created a standard.  I am not writing this, nor did I at the time, to be a stickler for Fowler’s or old grammar rules, but to surface the awareness that changes in the systems’ use of language flow outward into spoken language, and that they often have significant ramifications in how we can think about things. If your software systematically attempts to remove the use of animate pronouns for animals, plants and objects, it becomes of judgment of the humanity of any thing other than a human.   These are the things invisible to most people, yet significant in the ways in which we exist in our worlds.

In the same vein, I still look at the ways in which software is an output into our language, not just how language changes within power and control structures, but also the adoption of words, and the modification of our grammar, to make it easier to interact with the machines. More on this last bit later.



Temporal translation

I collect old dictionaries, in many languages, translations and otherwise. They are full of rich cultural information, new words, pathways, changed meanings, and I enjoy reading them for the glimpses of other worlds.

Often they contain words that I have to look up in other dictionaries, such as my copy of the first Hebrew-English translation dictionary released in Israel. It has so many words about the desert, about the plants, water, formations, growing, that I had to look a signficant number of them up in English, as I had never heard them.  A more modern Hebrew-French translation dictionary I have does not include nearly as many words of this sort.

I can build these models in my mind, in bits and pieces. But what would it be like to build them in the machine, to provide a rich view into different time periods by pouring in time-specific language data?

What if the machine can translate me to 1700s English? What if the machine translated from time periods, different Englishes, or Frenches? What about dialects?

I don’t know where phonology data would come from. What if I want to translate to Beowulf? How does the machine learn to pronounce the language properly?

I can imagine an amazing visualization, a time line, that I can drag into the past, to hear the sounds. Except it would need regional variation as well.

In the tradtion of vac, in which sound matters, the sound and the meaning intricately entwined, what histories can we learn by having the ability to translate to other places in time, not just other languages?

Luc Steels and language evolution models in robots

Luc Steels’ work from more than a decade ago on the evolution of language, is one of the few examples of someone thinking about how robots could evolve langauge. He looks at the evolution of language using agents/AIs as the means of exploring how languages are learned and evolved.

What I am interested in is different than this. I am interested in how machines evolve language to communicate with each other, what this means for how humans understand machines, and what the communication will be between the two in the future. So ai/ai conversations as well as ai/ai/human.  I prefer the triad because it is important to my hypotheses that the machines interrelate with each other as well as humans.

To go back for a moment, to the evolution of language, think of it this way. You have the origins of language, the means in which children learn a language, and the ways in which a language evolves. For the latter, for example, take a teenager, whose language may well be incomprehensible to adults.  You can see linguistic variation both in the meanings of words, as well as the grammatical structures.  We don’t question this in teens, though we do usually expect them to speak our languages as well, to control, as a linguist would say, across the continuum of variations.  Now imagine two AIs as teenagers, I want to understand the way in which they evolve language in order to communicate, and what drives both the evolution of parts (words, grammar) as well as what underlies the communication needs that leads to changes in language.

So thus, how do we create models of language evolution that machines may adopt if they are allowed to change language as they see fit, for whatever reason. Mostly, now, we discuss this in terms of efficiency, but that is a very human deterministic view that I prefer to avoid at this time.  Some of the current, and unfortunately very small, data sets I have seen on the AI language evolutions have similar markers to early creole language models, and I’d like to see more data to understand if this is what is happening.

But back to Steels’ and one of his talks I quite enjoy, given at Aldebaran in 2005.  He explains what matters to his work, and the ways in which he is modeling the past.

One of his most interesting points is that embodiment is required for the evolution that he is interested in. He is attempting to model the evolution of human language, and without embodiment, it doesn’t work.

This is also very interesting to consider in the current AI/agents that are being created, and how gestures may change the ways AI and humans will and can communicate.  I haven’t yet seen much written about this, but I also haven’t explicitly looked for papers and research on language evolution and embodiment in the current collections of intelligences being designed and built.

Origins are difficult in linguistics. We don’t really know where and how languages originated in humans or why. We don’t have a clear understanding of how languages work in our minds, or how languages are learned. We can argue different positions and there is an enormous body of work and theory on this, but I wouldn’t say there is agreement. However, and while people do study this, it isn’t on par with the explorations for the origin of the universe, for example. We lack a clear and precise model of behavior, language, and intelligence, so when we are building machines that engage in these domains I might argue that we can’t be sure of the outcome. In effect, unlike the game Go, there are no first principles we can give a machine.

But, as Steel’s points out, asking these questions on origins can provide us with profound insights. And this loops back to his work, on looking at the evolution of language, and how he is going about trying to address these questions.

Here is the link to the video, Can Robots Invent Their Own Language. it’s worth a watch if you are interested in these fields.



Stronger attention to language, please.

AI Now Institute is an independent research institution looking at the ‘social implications of artificial intelligence,’ something very needed as we continue to have such rapid and significant change in AI, driven by a very limited set of creators.

The Institute itself has four domains which it uses to bucket to the work they do on “the social implications of artificial intelligence”.

  • Rights & Liberties
  • Labor & Automation
  • Bias & Inclusion
  • Safety & Critical Infrastructure

Reading their 2017 Report, I believe it should have more emphasis on language in its recommendations, about which I would like to say more. Linguists, specifically those outside the computational linguistics field, need to be more integrated in the creation of AI as technology and interface.

Language is an underlying consideration in Bias & Inclusion, with this description:

However, training data, algorithms, and other design choices that shape AI systems may reflect and amplify existing cultural prejudices and inequalities.

Which does not have a strong enough inclusion or consideration of the language(s) used to train these systems. While bias work is written about language in AIs, it is more likely to fall on the corpus, that is to say, which words are used in descriptions, and the like. When you feed a corpus into a machine, it brings all its biases with it, and since these data sets are extant, they come with all the societal issues that seem to be more visible now than at earlier times.

Language and power, language and bias, minority languages, all of these have long been topics in the field of linguistics. They are also touched on in behavioral economics, with priming and other ways in which we set into the minds of humans particular considerations. You can also see this in the racial bias work from Harvard that was very prevalent on the web a few years back.

Language is a core human communication tool that entails so much history and meaning that without a greater attention to the social and cultural implications of the language we choose, from how we discuss these topics, to how language is embedded in the interaces of our AI systems we are glossing over something of great meaning with far too little attention.

I don’t think that language belongs only in the realm of bias & inclusion, in the long run. It may create outsiders at this time, but language is such a core consideration, it seems larger than any of these four domains.  Though to note, as well, none of these domains explicitly attend to the interfaces and the ways in which we interact with these systems, so language would belong there as well, as an input and an output, with differing needs and attentions on each side.





Linguistic anthropology and AI, part 2

I posted the original set of questions so I could shoot them over to a few people, to get their thoughts on my thoughts. Delivered even more than expected.  In the emails and conversations I’ve had since then, there are ever more questions, that I am going to keep documenting here.

  • If it were possible to allow the AIs to interrupt each other, to cut in before one finished what it was saying, what would happen?
  • What happens if you have three AIs in conversation or negotiation?
  • Are the AIs identical in the beginning? If, so, who modifies language first, and do they do it differently? In concert? In reaction?
  • Does an AI who changes language get considered a new incarnation of the AI? Does it modify itself, as it modifies its language?
  • If you have two AIs with different programming, two different incarnations, of a sort, what modifications do they make, vs two instantiations of the same thing?
  • Does language come about as a means of addressing desires and needs? [Misha wrote this and I find I don’t agree, which is really a deeply fascinating place to go with this.]
  • Can machines have desires and needs? How would we know the answer to this?
  • Is the assumption that machines modify language for reasons of efficiency overly deterministic?
  • What is the role of embodiment in the creation of language? Is it required for something to be meaningful? Does it change the way language works? Would it ‘count’ for cyborgs?

One thing I have discovered is that I go at this from a different perspective than many of my conversation partners, which is that I accept that it is possible that everything we think we know is wrong, both about humans, and about machines.  As I wrote, we assume humans are rational in order to make models of human behavior, which are faulty, because we are not. We assume machines are rational, because we programmed them to be, but what if they, too, are not? There seems to be a sense that binary does not allow for irrationality, or anomaly, but..what if it does?

I think I need to wrap into these discussions four things:

  1.  a primer on computational linguistics for those who don’t have it
  2.  a bit of an overview on general linguistics, and where we stand on that
  3.  an overview of creole linguistics, because I think it is a very interesting model to use for the evolution of AI languages, particularly and perhaps except, for the bit where it requires a power dynamic, historically.
  4. some discussion of the genetic evolution of algorithms, deep learning, adversarial networks etc.

Misha’s last really interesting question to me: “Can you evolve language without pain?” is a bit acontextual as I toss it here, but what an interesting question about feedback loops.


Nigerian Pidgin on the BBC

French24 posted an interesting (by which I mean riddled with mis-statements) article about the BBC starting up a service for Nigerian Pidgin, which has 75MM speakers, according to the France24 article, and according to other sources, approximately 30MM first AND second languages speakers.  The article is strangely dismissive of the language and of the speakers, as I read it.

Nigerian Pidgin is the name of the creole language spoken by a significant percentage of the population.  When I studied it, now 20 years ago, it was considered English-based with an influx of words from major trading populations, so it had Portuguese and Swahili origin words. It was not “Portuguese-based” or “Jamaican Patois inspired” as the article claims. The history of the slave populations and the trade routes are the history of the creation of the language.

Creoles, like most languages, have a continuum of formality, but in the case of creoles, rather than going from slang to formal language, because the creole emerged with a base language, in this case English, the ‘higher’ form (because old school linguists were just that way) is closer to English, and the ‘lower’ form, farther away. This can be grammar, it can be vocabulary, it can be cadence, it varies by language. Comparable to, say Verlan and French. Which doesn’t even begin to touch regional dialects.

Back to the article!

The first line of the article is flat out impossible, a language has a grammar. Languages change. Unwritten languages have no standard orthography, until they do.

 Imagine a language without an alphabet, held together without grammar or spelling, which changes every day but is nonetheless spoken and understood by more than 75 million Nigerians.

Many languages have no alphabet specific to their language, we use Roman or Greek or Cyrillic characters to write. Alphabets specific to a language are a newer incarnation, often tied to national interests or identity. Think Georgian, Cherokee, and Korean. These alphabets were created long after the languages.

Writing (Nigerian) Pidgin may be new, delivering the news over the airwaves and on a website, as well, however the language evolved just so that people could communicate and this is really no different.   If it had a prior association with the ‘lower classes’ it is because it began with the oppression of the locals by the British colonial empire, and the trade routes that grew around their outposts.

Says the French linguist quoted in the article, “It’s a language that belongs to bonody at the same time as belonging to everybody.”  And can’t we say the exact same thing about every language we speak?

The BBC anouncement is much better, but refers to the language as a pidgin and defines it as such, even though, at least when I was in grad school for Linguistics, it was considered a creole. There are so many sociocultural and historical complexities of pidgins and creoles, and I haven’t studied this one since grad school, so I will leave it at that. I am looking forward to the service though, reminder of times past. It will be interesting to see if I can still understand the language or if it has evolved too much.


Whale Syntax

I continue to be obsessed with these sounds, from Charles Lindsay’s CODE Humpback. I am always astonished that humans think other species on earth do not have language, complex or otherwise. Once upon a time I was an avid scuba diver and time spent under water in the vicinity of whales and other cetaceans quickly removes such a thought. Of course, I also trained as a linguist, so that may have something to do with it.

The RCA Morse Code transmitting and receiving stations at Bolinas and Pt. Reyes California are the last of their kind in the U.S. to maintain this once vital maritime language.

I had no idea those still existed, and would like to see them.

Are whales older than Sanskrit? [YES]





Elegant and incisive

I am working backwards through my year plus worth of notebooks on The Adelphi Project, and I came to this series of questions which I had written, in the very early days:

Who are the world’s eloquent and living intellectuals of today? What are they writing about? In what languages? Who writes the fiction? Do we have any? Are they revolutionary? Counter revolutionary? What are the architects writing?

One of the complicating factors is that those who fit historically into such spaces, we know their histories, their times, their trajectories, their deaths, and this makes it easier, I think, to evaluate them as intellectuals. But that cannot be the best of ways, we must recognize the intellectuals of our time, what I can see in the past, is those whose thoughts stuck, at least for now.

This project involves some interesting early 20th century novelists, novelists I think we don’t currently have, in the English speaking world. Notably, these are not English speakers, that I am thinking of, but rather notably, those from within the Austro-Hungarian Empire.

I am not looking only for novelists, but I was struck by the weight of this short novels, of their ideas, and this doesn’t feel of the present era, so I had started with that question. I am just seeking those who are notable and on par with the past, not the best of the present.