Profit over people : neoliberalism and global order / Noam Chomsky

 

In Profit Over People, Noam Chomsky takes on neoliberalism: the pro-corporate system of economic and political policies presently waging a form of class war worldwide. By examining the contradictions between the democratic and market principles proclaimed by those in power and those actually practiced, Chomsky critiques the tyranny of the few that restricts the public arena and enacts policies that vastly increase private wealth, often with complete disregard for social and ecological consequences. Combining detailed historical examples and uncompromising criticism, Chomsky offers a profound sense of hope that social activism can reclaim people's rights as citizens rather than as consumers, redefining democracy as a global movement, not a global market.

https://catalogue.nla.gov.au/catalog/2227556

 

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YOURDEMOCRACY.NET RECORDS HISTORY AS IT SHOULD BE — NOT AS THE WESTERN MEDIA WRONGLY REPORTS IT — SINCE 2005.

 

         Gus Leonisky

         POLITICAL CARTOONIST SINCE 1951.

CHOMSKY EXPLAINS THE VALUE OF LANGUAGE FOR HUMANS... AT THIS LEVEL ONE COULD ARGUE THAT ARTIFICIAL INTELLIGENCE IS VERY SAVVY ABOUT LANGUAGE AND "KNOWS" (COMPUTE) HOW TO USE LANGUAGE AND MANIPULATE IT....

 

HERE IS CHOMSKY AND LINGUSTICS:

 

Noam Chomsky is an American linguist who has had a profound impact on philosophy. Chomsky’s linguistic work has been motivated by the observation that nearly all adult human beings have the ability to effortlessly produce and understand a potentially infinite number of sentences. For instance, it is very likely that before now you have never encountered this very sentence you are reading, yet if you are a native English speaker, you easily understand it. While this ability often goes unnoticed, it is a remarkable fact that every developmentally normal person gains this kind of competence in their first few years, no matter their background or general intellectual ability. Chomsky’s explanation of these facts is that language is an innate and universal human property, a species-wide trait that develops as one matures in much the same manner as the organs of the body. A language is, according to Chomsky, a state obtained by a specific mental computational system that develops naturally and whose exact parameters are set by the linguistic environment that the individual is exposed to as a child. This definition, which is at odds with the common notion of a language as a public system of verbal signals shared by a group of speakers, has important implications for the nature of the mind.

Over decades of active research, Chomsky’s model of the human language faculty—the part of the mind responsible for the acquisition and use of language—has evolved from a complex system of rules for generating sentences to a more computationally elegant system that consists essentially of just constrained recursion (the ability of a function to apply itself repeatedly to its own output). What has remained constant is the view of language as a mental system that is based on a genetic endowment universal to all humans, an outlook that implies that all natural languages, from Latin to Kalaallisut, are variations on a Universal Grammar, differing only in relatively unimportant surface details. Chomsky’s research program has been revolutionary but contentious, and critics include prominent philosophers as well as linguists who argue that Chomsky discounts the diversity displayed by human languages.

Chomsky is also well known as a champion of liberal political causes and as a trenchant critic of United States foreign policy. However, this article focuses on the philosophical implications of his work on language. After a biographical sketch, it discusses Chomsky’s conception of linguistic science, which often departs sharply from other widespread ideas in this field. It then gives a thumbnail summary of the evolution of Chomsky’s research program, especially the points of interest to philosophers. This is followed by a discussion of some of Chomsky’s key ideas on the nature of language, language acquisition, and meaning. Finally, there is a section covering his influence on the philosophy of mind.

Table of Contents

1. Life
2. Philosophy of Linguistics
   1. Behaviorism and Linguistics 
   2. The Galilean Method 
   3. The Nature of the Evidence
   4. Linguistic Structures 
3. The Development of Chomsky’s Linguistic Theory
   1. Logical Constructivism
   2. The Standard Model
   3. The Extended Standard Model
   4. Principles and Parameters
   5. The Minimalist Program 
4. Language and Languages 
   1. Universal Grammar
   2. Plato’s Problem and Language Acquisition 
   3. I vs. E languages 
   4. Meaning and Analyticity
   5. Kripkenstein and Rule Following
5. Cognitive Science and Philosophy of Mind
6. References and Further Reading
   1. Primary Sources
   2. Secondary Sources 

1. Life

Avram Noam Chomsky was born in Philadelphia in 1928 to Jewish parents who had immigrated from Russia and Ukraine. He manifested an early interest in politics and, from his teenage years, frequented anarchist bookstores and political circles in New York City. Chomsky attended the University of Pennsylvania at the age of 16, but he initially found his studies unstimulating. After meeting the mathematical linguist Zellig Harris through political connections, Chomsky developed an interest in language, taking graduate courses with Harris and, on his advice, studying philosophy with Nelson Goodman. Chomsky’s 1951 undergraduate honors thesis, on Modern Hebrew, would form the basis of his MA thesis, also from the University of Pennsylvania. Although Chomsky would later have intellectual fallings out with both Harris and Goodman, they were major influences on him, particularly in their rigorous approach, informed by mathematics and logic, which would become a prominent feature of his own work.

After earning his MA, Chomsky spent the next four years with the Society of Fellows at Harvard, where he had applied largely because of his interest in the work of W.V.O. Quine, a Harvard professor and major figure in analytic philosophy. This would later prove to be somewhat ironic, as Chomsky’s work developed into the antithesis of Quine’s behaviorist approach to language and mind. In 1955, Chomsky was awarded his doctorate and became an assistant professor at the Massachusetts Institute of Technology, where he would continue to work as an emeritus professor even after his retirement in 2002. Throughout this long tenure at MIT, Chomsky produced an enormous volume of work in linguistics, beginning with the 1957 publication of Syntactic Structures. Although his work initially met with indifference or even hostility, including from his former mentors, it gradually altered the very nature of the field, and Chomsky grew to be widely recognized as one of the most important figures in the history of language science. Since 2017, he has been a laureate professor in the linguistics department at the University of Arizona.

Throughout his career, Chomsky has been at least as prolific in social, economic, and political criticism as in linguistics. Chomsky became publicly outspoken about his political views with the escalation of the Vietnam War, which he always referred to as an “invasion”. He was heavily involved in the anti-war movement, sometimes risking both his professional and personal security, and was arrested several times. He remained politically active and, among many other causes, was a vocal critic of US interventions in Latin America during the 1980s, the reaction to the September 2001 attacks, and the invasion of Iraq. Chomsky has opposed, since his early youth, the capitalist economic model and supported the Occupy movement of the early 2010s. He has also been an unwavering advocate of intellectual freedom and freedom of speech, a position that has at times pitted him against other left-leaning intellectuals and caused him to defend the rights of others who have very different views from his own. Despite the speculations of many biographers, Chomsky has always denied any connection between his work in language and politics, sometimes quipping that someone was allowed to have more than one interest.

In 1947, Chomsky married the linguist Carol Doris Chomsky (nee Schatz), a childhood friend from Philadelphia. They had three children and remained married until her death in 2008. Chomsky remarried Valeria Wasserman, a Brazilian professional translator, in 2014.

2. Philosophy of Linguistics

Chomsky’s approach to linguistic science, indeed his entire vision of what the subject matter of the discipline consists of, is a sharp departure from the attitudes prevalent in the mid-20th century. To simplify, prior to Chomsky, language was studied as a type of communicative behavior, an approach that is still widespread among those who do not accept Chomsky’s ideas. In contrast, his focus is on language as a type of (often unconscious) knowledge. The study of language has, as Chomsky states, three aspects: determining what the system of knowledge a language user has consists of, how that knowledge is acquired, and how that knowledge is used. A number of points in Chomsky’s approach are of interest to the philosophy of linguistics and to the philosophy of science more generally, and some of these points are discussed below.

a. Behaviorism and Linguistics

When Chomsky was first entering academics in the 1950s, the mainstream school of linguistics for several decades had been what is known as structuralism. The structuralist approach, endorsed by Chomsky’s mentor Zellig Harris, among others, concentrated on analyzing corpora, or records of the actual use of a language, either spoken or written. The goal of the analysis was to identify patterns in the data that might be studied to yield, among other things, the grammatical rules of the language in question. Reflecting this focus on language as it is used, structuralists viewed language as a social phenomenon, a communicative tool shared by groups of speakers. Structuralist linguistics might well be described as consisting of the study of what happens between a speaker’s mouth and a listener’s ear; as one well -known structuralist put it, “the linguist deals only with the speech signal” (Bloomfield, 1933: 32). This is in marked contrast to Chomsky and his followers, who concentrate on what is going on in the mind of a speaker and who look there to identify grammatical rules.

Structuralist linguistics was itself symptomatic of behaviorism, a paradigm prominently championed in psychology by B.F. Skinner and in philosophy by W.V.O. Quine and which was dominant in the midcentury. Behaviorism held that science should restrict itself to observable phenomena. In psychology, this meant seeking explanations entirely in terms of external behavior without discussing minds, which are, by their very nature, unobservable. Language was to be studied in terms of subjects’ responses to stimuli and their resulting verbal output. Behaviorist theories were often formed on the basis of laboratory experiments in which animals were conditioned by being given food rewards or tortured with electric shock in order to shape their behavior. It was thought that human behavior could be similarly explained in terms of conditioning that shapes reactions to specific stimuli. This approach perhaps reached its zenith with the publication of Skinner’s Verbal Behavior (1957), which sought to reduce human language to conditioned responses. According to Skinner, speakers are conditioned as children, through training by adults, to respond to stimuli with an appropriate verbal response. For example, a child might realize that if they see a piece of candy (the stimulus) and respond by saying “candy”, they might be rewarded by adults with the desired sweet, reinforcing that particular response. For an adult speaker, the pattern of stimuli and response could be very complex, and what specific aspect of a situation is being responded to might be difficult to ascertain, but the underlying principle was held to be the same.

Chomsky’s scathing 1959 review of Verbal Behavior has actually become far better known than the original book. Although Chomsky conceded to Skinner that the only data available for the study of language consisted of what people say, he denied that meaningful explanations were to be found at that level. He argued that in order to explain a complex behavior, such as language use, exhibited by a complex organism such as a human being, it is necessary to inquire into the internal organization of the organism and how it processes information. In other words, it was necessary to make inferences about the language user’s mind. Elsewhere, Chomsky likened the procedure of studying language to what engineers would do if confronted with a hypothetical “black box”, a mysterious machine whose input and output were available for inspection but whose internal functioning was hidden. Merely detecting patterns in the output would not be accepted as real understanding; instead, that would come from inferring what internal processes might be at work.

Chomsky particularly criticized Skinner’s theory that utterances could be classified as responses to subtle properties of an object or event. The observation that human languages seem to exhibit stimulus-freedom goes back at least to Descartes in the 17th century, and about the same time as Chomsky was reviewing Skinner, the linguist Charles Hockett (later one of Chomsky’s most determined critics) suggested that this is one of the features that distinguish human languages from most examples of animal communication. For instance, a vervet monkey will give a distinct alarm call any time she spots an eagle and at no other times. In contrast, a human being might say anything or nothing in response to any given stimulus. Viewing a paining one might say, “Dutch…clashes with the wallpaper…. Tilted, hanging too low, beautiful, hideous, remember our camping trip last summer? or whatever else might come to our minds when looking at a picture.” (Chomsky, 1959:2). What aspect of an object, event, or environment triggers a particular response rather than another can only be explained in mental terms. The most relevant fact is what the speaker is thinking about, so a true explanation must take internal psychology into account.

Chomsky’s observation concerning speech was part of his more general criticism of the behaviorist approach. Chomsky held that attempts to explain behavior in terms of stimuli and responses “will be in general a vain pursuit. In all but the most elementary cases, what a person does depends in large measure on what he knows, believes, and anticipates” (Chomsky, 2006: xv). This was also meant to apply to the behaviorist and empiricist philosophy exemplified by Quine. Although Quine has remained important in other aspects of analytic philosophy, such as logic and ontology, his behaviorism is largely forgotten. Chomsky is widely regarded as having inaugurated the era of cognitive science as it is practiced today, that is, as a study of the mental.

b. The Galilean Method

Chomsky’s fundamental approach to doing science was and remains different from that of many other linguists, not only in his concentration on mentalistic explanation. One approach to studying any phenomenon, including language, is to amass a large amount of data, look for patterns, and then formulate theories to explain those patterns. This method, which might seem like the obvious approach to doing any type of science, was favored by structuralist linguists, who valued the study of extensive catalogs of actual speech in the world’s languages. The goal of the structuralists was to provide descriptions of a language at various levels, starting with the analysis of pronunciation and eventually building up to a grammar for the language that would be an adequate description of the regularities identifiable in the data.

In contrast, Chomsky’s method is to concentrate not on a comprehensive analysis but rather on certain crucial data, or data that is better explained by his theory than by its rivals. This sort of methodology is often called “Galilean”, since it takes as its model the work of Galileo and Newton. These physicists, judiciously, did not attempt to identify the laws of motion by recording and studying the trajectory of as many moving objects as possible. In the normal course of events, the exact paths traced by objects in motion are the results of the complex interactions of numerous phenomena such as air resistance, surface friction, human interference, and so on. As a result, it is difficult to clearly isolate the phenomena of interest. Instead, the early physicists concentrated on certain key cases, such as the behavior of masses in free fall or even idealized fictions such as objects gliding over frictionless planes, in order to identify the principles that, in turn, could explain the wider data. For similar reasons, Chomsky doubts that the study of actual speech—what he calls performance—will yield theoretically important insights. In a widely cited passage (Chomsky, 1962, 531), he noted that:

Actual discourse consists of interrupted fragments, false starts, lapses, slurring, and other phenomena that can only be understood as distortions of an underlying idealized pattern.

Like the ordinary movements of objects observable in nature, which Galileo largely ignored, actual speech performance is likely to be the product of a mass of interacting factors, such as the social conventions governing the speech exchange, the urgency of the message and the time available, the psychological states of the speakers (excited, panicked, drunk), and so on, of which purely linguistic phenomena will form only a small part. It is the idealized patterns concealed by these effects and the mental system that generates those patterns —the underlying competence possessed by language users —that Chomsky regards as the proper subject of linguistic study. (Although the terms competence and performance have been superseded by the I-Language/E-Language distinction, discussed in 4.c. below, these labels are fairly entrenched and still widely used.)

c. The Nature of the Evidence

Early in his career (1965), Chomsky specified three levels of adequacy that a theory of language should satisfy, and this has remained a feature of his work. The first level is observational, to determine what sentences are grammatically acceptable in a language. The second is descriptive, to provide an account of what the speaker of the language knows, and the third is explanatory, to give an explanation of how such knowledge is acquired. Only the observational level can be attained by studying what speakers actually say, which cannot provide much insight into what they know about language, much less how they came to have that knowledge. A source of information about the second and third levels, perhaps surprisingly, is what speakers do not say, and this has been a focus of Chomsky’s program. This negative data is drawn from the judgments of native speakers about what they feel they can’t say in their language. This is not, of course, in the sense of being unable to produce these strings of words or of being unable, with a little effort, to understand the intended message, but simply a gut feeling that “you can’t say that”. Chomsky himself calls these interpretable but unsayable sentences “perfectly fine thoughts”, while the philosopher Georges Rey gave them the pithier name “WhyNots”. Consider the following examples from Rey 2022 (the “*” symbol is used by linguists to mark a string that is ill-formed in that it violates some principle of grammar):

(1) * Who did John and kiss Mary? (Compared to John, and who kissed Mary?and who-initial questions like Who did John kiss?)

(2) * Who did stories about terrify Mary? (Compared to stories about who terrified Mary?)

Or the following question/answer pairs:

(3) Which cheese did you recommend without tasting it? * I recommended the brie without tasting it. (Compared to… without tasting it.)

(4) Have you any wool? * Yes, I have any wool.

An introductory linguistics textbook provides two further examples (O’Grady et al. 2005):

(5) * I went to movie. (Compared to I went to school.)

(6) *May ate a cookie, and then Johnnie ate some cake, too. (Compared to Mary ate  a cookie, and then Johnnie ate a cookie too/ate a snack too.)

The vast majority of English speakers would balk at these sentences, although they would generally find it difficult to say precisely what the issue is (the textbook challenges the reader to try to explain). Analogous “whynot” sentences exist in every language yet studied.

What Chomsky holds to be significant about this fact is that almost no one, aside from those who are well read in linguistics or philosophy of language, has ever been exposed to (1) –(6) or any sentences like them. Analysis of corpora shows that sentences constructed along these lines virtually never occur, even in the speech of young children. This makes it very difficult to accept the explanation, favored by behaviorists, that we recognize them to be unacceptable as the result of training and conditioning. Since children do not produce utterances like (1) –(6), parents never have a chance to explain what is wrong, to correct them, and to tell them that such sentences are not part of English. Further, since they are almost never spoken by anyone, it is vanishingly unlikely that a parent and child would overhear them so that the parent could point them out as ill-formed. Neither is this knowledge learned through formal instruction in school. Instruction in not saying sentences like (1)–(6) is not a part of any curriculum, and an English speaker who has never attended a day of school is as capable of recognizing the unacceptability of (1)–(6) as any college graduate.

Examples can be multiplied far beyond (1)–(6); there are indefinite numbers of strings of English words (or words of any language) that are comprehensible but unacceptable. If speakers are not trained to recognize them as ill-formed, how do they acquire this knowledge? Chomsky argues that this demonstrates that human beings possess an underlying competence capable of forming and identifying grammatical structures—words, phrases, clauses, and sentences —in a way that operates almost entirely outside of conscious awareness, computing over structural features of language that are not actually pronounced or written down but which are critical to the production and understanding of sentences. This competence and its acquisition are the proper subject matter for linguistic science, as Chomsky defines the field.

d. Linguistic Structures

An important part of Chomsky’s linguistic theory (although it is an idea that predates him by several decades and is also endorsed by some rival theories) is that it postulates structures that lie below the surface of language. The presence of such structures is supported by, among other evidence, considering cases of non-linear dependency between the words in a sentence, that is, cases where a word modifies another word that is some distance away in the linear order of the sentence as it is pronounced. For instance, in the sentence (from Berwick and Chomsky, 2017: 117):

(7) Instinctively, birds who fly swim.

we know that instinctively applies to swim rather than fly, indicating an unspoken connection that bypasses the three intervening words and which the language faculty of our mind somehow detects when parsing the sentence. Chomsky’s hypothesis of a dedicated language faculty —a part of the mind existing for the sole purpose of forming and interpreting linguistic structures, operating in isolation from other mental systems —is supported by the fact that nonlinguistic knowledge does not seem to be relied on to arrive at the correct interpretation of sentences such as (7). Try replacing swim with play chess. Although you know that birds instinctively fly and do not play chess, your language faculty provides the intended meaning without any difficulty. Chomsky’s theory would suggest that this is because that faculty parses the underlying structure of the sentence rather than relying on your knowledge about birds.

According to Chomsky, the dependence of human languages on these structures can also be observed in the way that certain types of sentences are produced from more basic ones. He frequently discusses the formation of questions from declarative sentences. For instance, any English speaker understands that the question form of (8) is (9), and not (10) (Chomsky, 1986: 45):

(8) The man who is here is tall.

(9) Is the man who is here tall?

(10) * Is the man who here is tall?

What rule does a child learning English have to grasp to know this? To a Martian linguist unfamiliar with the way that human languages work, a reasonable initial guess might be to move the fourth word of the sentence to the front, which is obviously incorrect. To see this, change (8) to:

(11) The man who was here yesterday was tall.

A more sophisticated hypothesis might be to move the second auxiliary verb in the sentence, is in the case of (8), to the front. But this is also not correct, as more complicated cases show:

(12) The woman who is in charge of deciding who is hired is ready to see him now.           

(13) * Is the woman who is in charge of deciding who hired is ready to see him now?

In fact, in no human language do transformations from one type of sentence to another require taking the linear order of words into account, although there is no obvious reason why they shouldn’t. A language that works on a principle such as switch the first and second words of a sentence to indicate a question is certainly imaginable and would seem simple to learn, but no language yet cataloged operates in such a way.

The correct rule in the cases of (8) through (13) is that the question is formed by moving the auxiliary verb (is) occurring in the verb phrase of the main clause of the sentence, not the one in the relative clause (a clause modifying a noun, such as who is here). Thus, knowing that (9) is the correct question form of (8) or that (13) is wrong requires sensitivity to the way that the elements of a sentence are grouped together into phrases and clauses. This is something that is not apparent on the surface of either the spoken or written forms of (8) or (12), yet a speaker with no formal instruction grasps it without difficulty. It is the study of these underlying structures and the way that the mind processes them that is the core concern of Chomskyan linguistics, rather than the analysis of the strings of words actually articulated by speakers.

3. The Development of Chomsky’s Linguistic Theory

 Chomsky’s research program, which has grown to involve the work of many other linguists, is closely associated with generative linguistics. This name refers to the project of identifying sets of rules—grammars—that will generate all and only the sentences of a language. Although explicit rules eventually drop out of the picture, replaced by more abstract “principles”, the goal remains to identify a system that can produce the potentially infinite number of sentences of a human language using the resources contained in the minds of a speaker, which are necessarily finite.

Chomsky’s work has implications for the study of language as a whole, but his concentration has been on syntax. This branch of linguistic science is concerned with the grammars that govern the production of sentences that are acceptable in a language and divide them from nonacceptable strings of words, as opposed to semantics, the part of linguistics concerned with the meaning of words and sentences, and pragmatics, which studies the use of language in context.

Although the methodological principles have remained constant from the start, Chomsky’s theory has undergone major changes over the years, and various iterations may seem, at least on a first look, to have little obvious common ground. Critics present this as evidence that the program has been stumbling down one dead end after another, while Chomsky asserts in response that rapid evolution is characteristic of new fields of study and that changes in a program’s guiding theory are evidence of healthy intellectual progress. Five major stages of development might be identified, corresponding to the subsections below. Each stage builds on previous ones, it has been alleged; superseded iterations should not be considered to be false but rather replaced by a more complete explanation.

a. Logical Constructivism

Chomsky’s theory of language began to be codified in the 1950s, first set down in a massive manuscript that was later published as Logical Structure of Linguistic Theory (1975) and then partially in the much shorter and more widely read Syntactic Structures (1957). These books differed significantly from later iterations of Chomsky’s work in that they were more of an attempt to show what an adequate theory of natural language would need to look like than to fully work out such a theory. The focus was on demonstrating how a small set of rules could operate over a finite vocabulary to generate an infinite number of sentences, as opposed to identifying a psychologically realistic account of the processes actually occurring in the mind of a speaker.

Even before Chomsky, since at least the 1930s, the structure of a sentence was thought to consist of a series of phrases, such as noun phrases or verb phrases. In Chomsky’s early theory, two sorts of rules governed the generation of such structures. Basic structures were given by rewrite rules, procedures that indicate the more basic constituents of structural components. For example,

S → NP VP

indicates that a noun phrase, NP, followed directly by a verb phrase, VP, constitute a sentence, S. “NP → N” indicates that a noun may constitute a noun phrase. Eventually, the application of these rewrite rules stops when every constituent of a structure has been replaced by a syntactic element, a lexical word such as Albert or meows. Transformation rules alter those basic structures in various ways to produce structures corresponding to complex sentences. Importantly, certain transformation rules allowed recursion. This is a concept central to computer science and mathematical logic, by which a rule could be applied to its own output an unlimited number of times (for instance, in mathematics, one can start with 0 and apply the recursive function add 1 repeatedly to yield the natural numbers 0,1,2,3, and so forth.). The presence of recursive rules allows the embedding of structures within other structures, such as placing Albert meows under Leisa thinks to get Leisa thinks Albert meows. This could then be placed under Casey says that to produce Casey says that Leisa thinks Albert meows, and so on. Embedding could be done as many times as desired, so that recursive rules could produce sentences of any length and complexity, an important requirement for a theory of natural language. Recursion has not only remained central to subsequent iterations of Chomsky’s work but, more recently, has come to be seen as the defining characteristic of human languages.

Chomsky’s interest in rules that could be represented as operations over symbols reflected influence from philosophers inclined towards formal methods, such as Goodman and Quine. This is a central feature of Chomsky’s work to the present day, even though subsequent developments have also taken psychological realism into account. Some of Chomsky’s most impactful research from his early career (late 50s and early 60s) was the invention of formal language theory, a branch of mathematics dealing with languages consisting of an alphabet of symbols from which strings could be formed in accordance with a formal grammar, a set of specific rules. The Chomsky Hierarchy provides a method of classifying formal languages according to the complexity of the strings that could be generated by the language’s grammar (Chomsky 1956). Chomsky was able to demonstrate that natural human languages could not be produced by the lowest level of grammar on the hierarchy, contrary to many linguistic theories popular at the time. Formal language theory and the Chomsky Hierarchy have continued to have applications both in linguistics and elsewhere, particularly in computer science.

b. The Standard Model

Chomsky’s 1965 landmark work, Aspects of the Theory of Syntax, which devoted much space to philosophical foundations, introduced what later became known as the “Standard Model”. While the theory itself was in many respects an extension of the ideas contained in Syntactic Structures, there was a shift in explanatory goals as Chomsky addressed what he calls “Plato’s Problem”, the mystery of how children can learn something as complex as the grammar of a natural language from the sparse evidence they are presented with. The sentences of a human language are infinite in number, and no child ever hears more than a tiny subset of them, yet they master the grammar that allows them to produce every sentence in their language. (“Plato’s Problem” is an allusion to Plato’s Meno, a discussion of similar puzzles surrounding geometry. Section 4.b provides a fuller discussion of the issue as well as more recent developments in Chomsky’s model of language acquisition.) This led Chomsky, inspired by early modern rationalist philosophers such as Descartes and Leibniz, to postulate innate mechanisms that would guide a child in this process. Every human child was held to be born with a mental system for language acquisition, operating largely subconsciously, preprogrammed to recognize the underlying structure of incoming linguistic signals, identify possible grammars that could generate those structures, and then to select the simplest such grammar. It was never fully worked out how, on this model, possible grammars were to be compared, and this early picture has subsequently been modified, but the idea of language acquisition as relying on innate knowledge remains at the heart of Chomsky’s work.

An important idea introduced in Aspects was the existence of two levels of linguistic structure: deep structure and surface structure. A deep structure contains structural information necessary for interpreting sentence meaning. Transformations on a deep structure —moving, deleting, and adding elements in accordance with the grammar of a language —yield a surface structure that determines the way that the sentence is pronounced. Chomsky explained (in a 1968 lecture) that,

If this approach is correct in general, then a person who knows a specific language has control of a grammar that generates the infinite set of potential deep structures, maps them onto associated surface structures, and determines the semantic and phonetic interpretations of these abstract objects (Chomsky, 2006: 46).

Note that, for Chomsky, the deep structure was a grammatical object that contains structural information related to meaning. This is very different from conceiving of a deep structure as a meaning itself, although a theory to that effect, generative semantics, was developed by some of Chomsky’s colleagues (initiating a debate acrimonious enough to sometimes be referred to as “the linguistic wars”). The names and exact roles of the two levels would evolve over time, and they were finally dropped altogether in the 1990s (although this is not always noticed, a matter that sometimes confuses the discussion of Chomsky’s theories).

Aspects was also notable for the introduction of the competence/performance distinction, or the distinction between the underlying mental systems that give a speaker mastery of her language (competence) and her actual use of the language (performance), which will seldom fully reflect that mastery. Although these terms have technically been superseded by E-language and I-language (see 4.c), they remain useful concepts in understanding Chomsky’s ideas, and the vocabulary is still frequently used.

c. The Extended Standard Model

Throughout the 1970s, a number of technical changes, aimed at simplification and consolidation, were made to the Standard Model set out in Aspects. These gradually led to what became known as the “Extended Standard Model”. The grammars of the Standard Model contained dozens of highly specific transformation rules that successively rearranged elements of a deep structure to produce a surface structure. Eventually, a much simpler and more empirically adequate theory was arrived at by postulating only a single operation that moved any element of a structure to any place in that structure. This operation, move α, was subject to many “constraints” that limited its applications and therefore restrained what could be generated. For instance, under certain conditions, parts of a structure form “islands” that block movement (as when who is blocked from moving from the conjunction in John and who had lunch? to give *Who did John and have lunch?). Importantly, the constraints seemed to be highly consistent across human languages.

Grammars were also simplified by cutting out information that seemed to be specified in the vocabulary of a language. For example, some verbs must be followed by nouns, while others must not. Compare I like coffee and She slept to * I like and * She slept a book. Knowing which of these strings are correct is part of knowing the words like and slept, and it seems that a speaker’s mind contains a sort of lexicon, or dictionary, that encodes this type of information for each word she knows. There is no need for a rule in the grammar to state that some verbs need an object and others do not, which would just be repeating information already in the lexicon. The properties of the lexical items are therefore said to “project” onto the grammar, constraining and shaping the structures available in a language. Projection remains a key aspect of the theory, so that lexicon and grammar are thought to be tightly integrated.

Chomsky has frequently described a language as a mapping from meaning to sound. Around the time of the Extended Standard Model, he introduced a schema whereby grammar forms a bridge between the Phonetic Form, or PF, the form of a sentence that would actually be pronounced, and the Logical Form, or LF, which contained the structural specification of a sentence necessary to determine meaning. To consider an example beloved by introductory logic teachers, Everyone loves someone might mean that each person loves some person (possibly a different person in each case), or it might mean that there is some one person that everyone loves. Although these two sentences have identical PFs, they have different LFs.

Linking the idea of LF and PF to that of deep structure and surface structure (now called D-structure and S-structure, and with somewhat altered roles) gives the “T-model” of language:

D-structure

|

transformations

|

PF –    S-Structure    – LF

As the diagram indicates, the grammar generates the D-structure, which contains the basic structural relations of the sentence. The D-structure undergoes transformations to arrive at the S-structure, which differs from the PF in that it still contains unpronounced “traces” in places previously occupied by an element that was then moved elsewhere. The S-structure is then interpreted two ways: phonetically as the PF and semantically as the LF. The PF is passed from the language system to the cognitive system responsible for producing actual speech. The LF, which is not a meaning itself but contains structural information needed for semantic interpretation, is passed to the cognitive system responsible for semantics. This idea of syntactic structures and transformations over those structures as mediating between meaning and physical expression has been further developed and simplified, but the basic concept remains an important part of Chomsky’s theories

d. Principles and Parameters

In the 1980s, the Extended Standard Model would develop into what is perhaps the best known iteration of Chomskyan linguistics, what was first referred to as “Government and Binding”, after Chomsky’s book Lectures on Government and Binding (1981). Chomsky developed these ideas further in Barriers (1986), and the theory took on the more intuitive name “Principles and Parameters”. The fundamental idea was quite simple. As with previous versions, human beings have in their minds a computational system that generates the syntactic structures linking meanings to sounds. According to Principles and Parameters Theory, all of these systems share certain fixed settings (principles) for their core components, explaining the deep commonalities that Chomsky and his followers see between human languages. Other elements (parameters) are flexible and have values that are set during the language learning process, reflecting the variations observable across different languages. An analogy can be made with an early computer of the sort that was programmed by setting the position of switches on a control panel: the core, unchanging, circuitry of the computer is analogous to principles, the switches to parameters, and the program created by one of the possible arrangements of the switches to a language such as English, Japanese, or St’at’imcets (although this simple picture captures the essence of early Principles and Parameters, the details are a great deal more complicated, especially considering subsequent developments).

Principles are the core aspects of language, including the dependence on underlying structure and lexical projection, features that the theory predicts will be shared by all natural human languages. Parameters are aspects with binary settings that vary from language to language. Among the most widely discussed parameters, which might serve as convenient illustrations, are the Head and Pro-Drop parameters.

A head is the key element that gives a phrase its name, such as the noun in a noun phrase. The rest of the phrase is the complement. It can be observed that in English, the head comes before the complement, as in the noun phrase medicine for cats, where the noun medicine is before the complement for cats; in the verb phrase passed her the tea, the verb passed is first, and in the prepositional phrase in his pocket, the preposition inis first. .......

READ MORE: https://iep.utm.edu/chomsky-philosophy/

 

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YOURDEMOCRACY.NET RECORDS HISTORY AS IT SHOULD BE — NOT AS THE WESTERN MEDIA WRONGLY REPORTS IT — SINCE 2005.

 

         Gus Leonisky

         POLITICAL CARTOONIST SINCE 1951.

 

Both of these influencers are successful - but only one is human

BY Sakshi Venkatraman

 

In some ways, Gigi is like any other young social media influencer.

With perfect hair and makeup, she logs on and talks to her fans. She shares clips: eating, doing skin care, putting on lipstick. She even has a cute baby who appears in some videos.

But after a few seconds, something may seem a little off.

She can munch on pizza made out of molten lava, or apply snowflakes and cotton candy as lip gloss. Her hands sometimes pass through what she's holding.

That's because Gigi isn't real. She's the AI creation of University of Illinois student Simone Mckenzie - who needed to make some money over the summer.

Ms Mckenzie, 21, is part of a fast-growing cohort of digital creators who churn out a stream of videos by entering simple prompts into AI chatbots, like Google Veo 3. Experts say this genre, dubbed "AI slop" by some critics and begrudging viewers, is taking over social media feeds.

And its creators are finding considerable success.

"One video made me $1,600 [£1,185] in just four days," Ms Mckenzie said. "I was like, okay, let me keep doing this."

After two months, Gigi had millions of views, making Ms Mckenzie thousands through TikTok's creator fund, a programme that pays creators based on how many views they get. But she's far from the only person using AI to reach easy virality, experts said.

"It's surging right now and it's probably going to continue," said Jessa Lingel, associate professor and digital culture expert at the University of Pennsylvania.

Its progenitors - who now can generate videos of literally anything in just a few minutes - have the potential to disrupt the lucrative influencer economy.

But while some say AI is ruining social media, others see its potential to democratise who gains fame online, Lingel said. Those who don't have the money or time for a fancy background, camera setup or video editing tools can now go viral, too.

Traditional influencers being pushed out?

Social media influencing only recently became a legitimate career path. But in just a few years, the industry has grown to be worth over $250bn, according to investment firm Goldman Sachs. Online creators often use their own lives - their vacations, their pets, their makeup routines - to make content and attract a following.

AI creators who can make the same thing - only faster, cheaper and without the constraints of reality.

"It certainly has the potential to upset the creator space," said Brooke Duffy, a digital and social media scholar at Cornell University.

Ms Mckenzie, creator of Gigi, said videos take her only a few minutes to generate and she sometimes posts three per day.

That's not feasible for human influencers like Kaaviya Sambasivam, 26, who has around 1.3 million followers across multiple platforms.

Depending on the kind of video she's making - whether it's a recipe, a day-in-my life vlog, or a makeup tutorial - it may take anywhere from a few hours to a few days to fully produce. She has to shop, plan, set up her background and lighting, shoot and then edit.

AI creators can skip nearly all of those steps.

"It bears the question: is this going to be something that we can out compete? Because I am a human. My output is limited," Ms Sambasivam, based in North Carolina, said. "There are months where I will be down in the dumps, and I'll post just the bare minimum. I can't compete with robots."

She started building her channel while living with her parents during the Covid pandemic. Without a set-up, she said she duct-taped her phone to the wall to film. Eventually, she spent money she made as an influencer buying tripods, lighting, makeup and food for her videos. It took years to build her following.

Ms Mckenzie said she considered being a more traditional influencer, but didn't have the money, time or setup. That's why she created Gigi.

"My desk at home has a lot of books and stuff," she said. "It's not the most visually appealing. It definitely makes it easier that you can just pick whatever background you want with AI."

"Real" life on AI videos

When Ms Mckenzie started, she turned to Google's Veo 3 chatbot, asking it to generate a woman - someone to stand in as her.

Gigi is her age, 21, with tanned skin, green eyes, freckles, winged eyeliner and long black hair. She then asked the chatbot to make Gigi talk. Gigi now starts each video chiding commentators who accuse her of being AI. Then, mockingly proving them right, she eats a bedazzled avocado or a cookie made of slime. 

Ms Duffy said digital alterations aren't new. First, there were programs like Photoshop, used for image editing. Next, apps like FaceTune made it easier for users to change their faces for social media. But she said the main precursor to today's hyper-realistic AI videos were celebrity deepfakes, emerging in the late 2010s. 

But they now look much, much more real, Ms Duffy said, and they can spread faster.

AI videos run the gamut from the absurd - a cartoon of a cat working at McDonald's - to the hyper-realistic, like fake doorbell camera footage. They represent every genre - horror, comedy, culinary. But none of it is real.

"It's become, in some ways, a form of meme culture," Ms Duffy said.

One 31-year-old American woman living in South Korea has a TikTok page dedicated to an AI-generated puppy, Gamja, who wears headphones, cooks and curls his hair. She's received millions of views as well as partnerships from companies who want to be featured in her videos.

"I wanted to blend things that people love, which include food and puppies, in a way that hadn't been done before," she said.

One of the biggest AI content creators on TikTok is 27-year-old Daniel Riley. He has an audience of millions, but they have never seen his face. Rather, his "time travel" videos have earned him nearly 600,000 subscribers and tens of millions of views.

"POV: you wake up in Pompeii on eruption day" and "POV: you wake up as Queen Cleopatra" are some of his most popular titles, taking viewers through a 30-second-long fictionalised day in ancient history.

"I realised I could tell stories that would normally cost millions to produce and give people a look into different eras through their phone," he said.

And he's developed another stream of income - a bootcamp to teach others how to make similar AI videos for a monthly fee.

Will anyone know the difference?

"Stop calling me AI," Gigi says at the beginning of each TikTok. She's arguing with sceptics' - but some audience members unquestioningly believe she's real.

On one hand, AI videos that are almost indistinguishable from reality pose a real problem, Ms Lingel said, especially for young kids who don't yet have media literacy.

"I think it'll be almost impossible for an ordinary human to tell the difference soon," she said. "You're going to see a rise in misinformation, you're going to see a rise in scams, you're going to see a rise in content that's just…crappy."

On the other, AI videos can be mesmerising, experts said, offering cartoonish, exaggerated material.

"It's those images and posts that seem to toe the line between reality and duplicity that capture our attention and encourage us to share," Ms Duffy said.

A Harvard University study indicated that among AI users between the ages of 14-22, many say they use it to generate things like images and music.

Still, she said, the question is if human discernment can keep up with rapidly improving technology.

Almost every day, the creator of Gamja said she hears from people online, worried about her AI-generated puppy: they think he's eating foods that are unhealthy, they say - because they think they're watching a real dog.

https://www.bbc.com/news/articles/ce3wyplnev1o

 

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YOURDEMOCRACY.NET RECORDS HISTORY AS IT SHOULD BE — NOT AS THE WESTERN MEDIA WRONGLY REPORTS IT — SINCE 2005.

 

         Gus Leonisky

         POLITICAL CARTOONIST SINCE 1951.

 

 

AI powered 2025's economy to record highs. So why are only robots smiling?

By business reporter Daniel Ziffer

 

 

I don't know what I expected. Not this. I blame the robots. I blame the penguins.

The economy of 2025 has challenged people's certainty.

A permacrisis. A flurry. Contradictions and causation, chaos and change.

Markets are at record highs, but it doesn't feel like a party because so many people aren't invited.

Wait, hold on — the World Trade Uncertainty Index is higher than it was during the COVID-19 pandemic or the global financial crisis. And gold is at record highs as well, up 67 per cent in a year!

That's what people buy when they fear the world will fall apart.

Meanwhile, our corporate regulator is investigating our (essentially) monopoly stock market provider — the ASX — after "repeated and serious failures", a phrase you could have said about it any time for the past decade.

(I reckon the time last year when ASIC sued the stock market operator for misleadingly saying a project to replace its systems was "progressing well" probably flagged that things weren't "progressing well").

Our global collective worry rocketed after US President Donald Trump — who in words, advertisements and deeds had promised substantial tariffs on friends, neighbours and enemies — did something truly shocking to global traders: announcing tariffs on friends, neighbours and enemies.

Markets slumped, chaos reigned, penguins on remote uninhabited islands shivered as tariffs were slapped on their non-existent exports to the United States.

The only certainty from then onwards: uncertainty.

Party time — right?

The Nasdaq index of mega-tech stocks is up 17 per cent from the already elevated level where it started in January.

The so-called Magnificent Seven artificial intelligence-exposed companies are pumping cash and optimism through markets. (Let's ignore the fact one of the most talked-about books this year is If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI).

Our ASX 200 group of the 200 largest listed companies is up 4.5 per cent — and it would have been more but for a wobble since October.

It's what George Tharenou of global investment fund UBS told me was an "up crash", with assets like share markets and property just heading skywards.

'It's almost a detachment from fundamentals'

Tharenou called it FOMO: the fear of missing out.

And he's not the only one suspicious of what seems like an empty boom in a dangerous time.

Analysts and experts talk about "2008 vibes" — what things felt like in the time just before the global financial crisis crushed the world economy. (It took 12 years for the ASX 200 to again reach the level it was at before the crisis).

The government's sovereign wealth store, the Future Fund, has $250 billion under management. Chief executive Raphael Arndt told The Australian Financial Review the year felt like a "perpetual inflection point — a permacrisis if you like".

"The weaponisation of trade, the persistence of inflation, climate shocks and a rising cost of capital — these all have tested the very assumptions that underpin investment theory."

We keep shredding economic norms.

That crushing inflation requires unemployment to rise.

That increasing cost of trade, tariffs, will crimp gross domestic product (GDP) growth (although that still might happen).

That gold booms when the market is falling.

And here's the biggest thing. We're talking about the "business" economy, the indices, the returns. They do affect people's lives. However, there's a lot more to it.

There are far bigger forces at play.

You aren't meant to know these incredibly obvious things people are talking about

Every time there's an election, the public service writes a manual for the incoming minister.

There's a "Red Book" in case of a Labor win and a "Blue Book" if the Coalition wins.

In May, Labor didn't just win; the Coalition was banished. In our two most populous cities, Sydney and Melbourne, there are collectively just three Liberal-held seats that don't include farmland in them. Three.

These so-called incoming government briefs are an honest look at issues facing the minister in their portfolio and are created for an audience of one: that person.

So I still kind of feel for the Treasury body that accidentally emailed me the one that only Jim Chalmers was meant to read.

Blunt doesn't cover what it told Jim, and we told you:

• You need to lift taxes
• You need to cut spending
• Your key election promise, building 1.2 million homes? Not going to happen (unless you massively change things immediately)

Chalmers said he was "relaxed" about the release of the advice, which described actions most government economists, journalists and the data were all across.

(Without labouring the point, the lawyers were less relaxed about it).

But it wasn't even the most impactful brief.

Buried in the manual for Social Services Minister Tanya Plibersek was this missile: There's a boomer boom as poor and middle-income people subsidise the incomes of older rich people.

Literally:

"Low and middle-income earners are subsidising the retirement incomes of seniors with significant wealth in addition to their homes."

Think about that. Poor people are subsidising the income of older non-working people who are significantly wealthy beyond owning their house.

People who don't need help are getting support from people who do.

Beyond being unfair, it is poisoning the well.

"The majority of Australians believe current income distribution is unfair," the brief reads, having been obtained using the Freedom of Information (FOI) process.

"This appears to be affecting views on democracy, as fewer people believe hard work leads to a better life."

We've tilted the playing field.

Job mobility is at decades-low levels as people stay put, imperilled by a tax system that makes buying and selling houses extremely expensive, tying people to mortgages so massive they dissuade people from taking risks.

Meanwhile, people with home loans are still getting smashed by high repayments.

For all of 2024, the Reserve Bank's key interest rate stayed the same. Early this year it stuttered marginally lower — just as public anger was becoming white hot — going lower two more times, before flatlining again.

The RBA is now flagging its economy-throttling interest rates probably haven't beaten inflation.

No real shock. Lots of that cost-of-living pressure is driven by longer-term issues like the messy but necessary energy transition and climate-change-fuelled insurance cost surges.

Beyond that, we're seeing the hard-to-squash price rises of an economy where productivity is increasingly reliant on services provided by humans rather than machines that can squeeze widgets out faster.

Workers get slapped with accusations of slackness as our productivity rate stutters, despite the obvious and contentious nature of even agreeing on the measurement of the concept in rapidly expanding fields like health care, the NDIS and teaching.

https://www.abc.net.au/news/2025-12-29/end-of-year-economics-analysis-wrap/106176480

 

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YOURDEMOCRACY.NET RECORDS HISTORY AS IT SHOULD BE — NOT AS THE WESTERN MEDIA WRONGLY REPORTS IT — SINCE 2005.

 

         Gus Leonisky

         POLITICAL CARTOONIST SINCE 1951.