In this essay, I investigate the development of algorithms from a digital paradigm in Victorian England, specifically through the work of Ada Lovelace and the influences of the Jacquard loom. I consider Lovelace’s algorithms through the framework of poetics, that is, how meaning is made and materialized through symbolic inscription. Within the discursive contexts of industrial manufacturing and Romanticism, I find that an algorithmic mode of production emerges from the consideration and inscription of memory. Since the ramifications of inscription and memory echo throughout contemporary computing and the Digital Humanities, examining the logics and paradigms that computational inscriptions reproduce are increasingly vital today. Thus I ultimately argue for the poetic analyses of algorithms and computer code.

Dans cet article, j’enquête sur le développement d’algorithmes venant d’un paradigme numérique en Angleterre victorienne, spécifiquement à travers l’œuvre d’Ada Lovelace et les influences du métier à tisser Jacquard. Je considère les algorithmes de Lovelace par le biais du cadre poétique, c’est-à-dire, comment l’inscription symbolique crée et matérialise le sens. Dans les contextes discursifs de la fabrication industrielle et du Romantisme, je trouve qu’un mode de production algorithmique émerge de la considération et de l’inscription de mémoire. Puisque les ramifications d’inscriptions et de mémoire résonnent au sein de l’informatique contemporaine et des Humanités numériques, examiner les logiques et les paradigmes que les inscriptions computationnelles reproduisent devient actuellement de plus en plus primordial. Ainsi, je plaide en fin de compte en faveur des analyses poétiques d’algorithmes et de codes informatiques.

When we think about the digital, that is, in “digital technology” or “digital humanities,” what often come to mind are computers, speed and efficiency, and the electronic ethereality of such entities as the Internet and the Cloud. However, at its root, what “digital” refers to is how we handle information. To be digital is to handle information digitally, that is, in digits; specifically for us, those are ones and zeros. Calling our century the “Information Age” hints at this attention to information, though the label points more to our economic basis rather than our digital paradigm. After all, we have always handled information and attempted to make meaning from it; we have language and we have poetry. But what does the digital paradigm entail? What meaning do we make from ones and zeros? And how might it have developed?

In 1804, the textile industry was revolutionized by the Jacquard loom, a machine capable of interpreting holes punched on paper cards. These holes articulated patterns that were then visualized on woven textiles. Besides speeding up manufacturing processes, automation by the Jacquard loom also expressed a digital paradigm: the information of textile patterns was inscribed into a series of values based on whether or not a punched hole was present in a certain read order. An inscription based on “whether or not” is the foundation of the binary language. Paradigmatically speaking, information was encoded into a logical series of presences/absences and true/false. Our algorithms, and subsequently computer code, thus developed from this paradigm for handling information.

The Jacquard loom influenced the work of Charles Babbage and Ada Lovelace to design what is now recognized as the first computer and first computational algorithm, respectively. Lovelace’s Notes, which contain this algorithm, explicitly discusses the mechanism of the Jacquard loom and its punched cards (See Appendix A for an image of Lovelace’s algorithms, in which she writes specifiable steps for the Analytical Engine to calculate the Bernoulli numbers). But is the punched card, or its informational paradigm, the only thread linking the loom and the computer? Or does that historic tie evoke a more complex and culturally nuanced relationship that speaks through the punches on the card? In order to answer these questions, we would have to look at the discourses that place machines and their algorithms within the context of sociocultural forces, such as the industries involving looms and textiles. I propose that considering the contexts that surrounded Lovelace’s work, namely the mechanization of design and Romantic theories on the materiality of language, can give us insight into how computational algorithms developed from a digital paradigm. By looking at the material and sociocultural contexts surrounding algorithms, my essay also seeks to show the affinity between computer code and poetics.

After situating algorithms within the field of Digital Humanities, I consider the mechanization of weaving in early nineteenth-century England and the production of Kashmiri shawls with Jacquard looms. From there I consider the modes of shawl production in relation to Romantic theories of Logos, proposing this combination as a cultural context with which Lovelace’s work would have been conversant. Logos, or incarnational language, was a poetic project of the time, pursued particularly by Coleridge, thus providing a theoretical parallel to Lovelace’s poetical science. I argue that Babbage’s Analytical Engine gave Lovelace the impetus to apply mathematics in a way that shifted engagement with machines from a paradigm of calculation to that of computation.

In our century, the inscription of memory has been veiled by layers of code (e.g. binary, machine code, compiled, etc.) unintelligible to the general public. Practically speaking, however, we can consider these inscriptions of memory in the kinds of activities algorithms currently produce, from simple email and word processing documents, to weather and dating apps, to the complex infrastructure of the World Wide Web. All these forces shape our experiences, and, in turn, are shaped by the algorithms we write. But how much do we understand about the operations of coding languages—when we swipe down to scroll on our Instagram, when we speak a command to Siri, when we follow our GPS systems—that these are all algorithmic operations expressed by computer code? Do we understand how our experiences have been shaped by a digital paradigm, by languages we never see or acknowledge?

In her book

My line of questioning attempts to integrate the claims of Vee and Schmidt to argue that algorithmic thinking not only produces coding languages, but is concurrently reified and further developed by coding languages. The relationship between the symbolic language of algorithms and its material effects and contexts is a poetic one: a way to make meaning of our technologies. I take Vee’s proposition of code as “a socially situated, symbolic system” (

To be sure, the most immediate context for the development of algorithms is the Industrial Revolution.

On one hand, this essay takes seriously Schmidt’s call for recognizing the role of algorithms in research, but on the other deviates from his recommendation for digital humanists to “understand the transformations that algorithms attempt to bring about” (

Ada Lovelace seems to be the most natural point to begin with, not just because she famously wrote the first computer program, but also due to her historical situation. The technological industrialization that Britain experienced in the first half of the nineteenth century shifted its cultures of production in a fashion much like the influence of digital technology and the Internet today. One example of this shift in Regency-era Britain manifests in productions of the Kashmiri shawl. Historian Chritralekha Zutshi considers the Kashmiri shawl at the intersection between industrialized manufacturing in Britain, interactions with imperial subjects, and domestic responses through fashion and literature. British colonists would travel to parts of south and central Asia to govern imperial subjects or extend economic relations, often returning with gifts, such as the Kashmiri shawl. These luxurious items were romanticized by travel narratives, which made them more valuable due to their exoticism.

The increasing demand for these so imagined exotic Kashmiri shawls, especially among members of Lovelace’s aristocratic circles, incentivized British factories to manufacture imitations. While the domestic textile industry attempted to compete with the authentic fabrics brought back through marketing rhetoric, the factory owners found ways to cut production costs so that their imitations could be sold at lower prices. As Zutshi (

Although the intended function of the Jacquard loom was to automate pattern-weaving for textiles, the form by which this was done (that is, through punched cards) shaped the way information was written and understood. Information was reduced to whether or not a hole was present on a given card: a value either true or false: binary. In the context of textiles, however, a pattern woven by the Jacquard loom did not just use binarized information, it also proposed that patterns were made up of binary codes. In other words, the symbolic inscriptions of the punched cards encoded material patterns such that the relationship between symbol and material produced a digital paradigm. As Essinger points out, “The portrait of Jacquard…was essentially a digitised image. Made using 24,000 punched cards, it wove an image of the inventor of the loom on which it was woven” (132). That is not to say this true/false logic was wholly novel; philosophers and logicians had been writing about it since Plato. It is the use of binary logic in such material endeavors that was new, a cultural blueprint for the Boolean algebra and computational methods that would follow (In fact, George Boole wrote

In one sense, the context of the Jacquard loom, that is, automated and machine-made weaving governed by human-made patterns, gave concrete boundaries for innovation. The inventor and its adopters refined it for simple and practical purposes. On the other hand, the context of weaving also provided boundaries against which to push. Innovators such as Babbage and Lovelace saw the potential of the mechanics of the Jacquard loom for handling other industrial processes, leading to the design of the Analytical Engine. For Lovelace, however, the context of weaving held a metaphorical sway as well. What kinds of information would the Engine be able to process and manipulate? What kinds of patterns would the Engine be able to weave? These “patterns” need not be relegated to aesthetics, that is, architectural designs or musical compositions (the latter of which Lovelace would also come to imagine). Rather, these “patterns” come from the process of weaving itself. The significance of the Jacquard loom on Lovelace’s work was not just in its potential for automated production, but the relationship between this automation (how it processed the holes in punched cards) and the context of weaving.

My point here is that the loom was not just significant in the history of computing due to its mechanics, but also due to the connotations that surround weaving. The significance of the Jacquard loom differs from machines before it, such as the printing press or the steam engine, because the craft of weaving bears a metaphorical affinity to the process of

From Victorian England, Zutshi gives us more concrete examples of these kinds of interpretations through the discourses surrounding the Kashmiri shawl. The marketing strategy of the textile industry capitalized on the distinction between hand-woven Kashmiri fabrics and machine-woven British imitations. One kind of weaving was pitted against the other.

We have seen that this control was deployed through symbolic inscription, specifically through punched cards.

If we follow Coleridge’s theory that poetry attempts to use language to render reality (not just represent it), then poetry can also be said to inscribe memory. Thus, the activity of inscription denotes a double duty: something is carved into existence (that is, created or made), and because of its symbolic form, it is also representational and readable. In contemporary academic terms, Susan Stewart (

For a more concrete example, let us take a serendipitous look at an excerpt from the work of Lovelace’s father, the poet Lord Byron. In the third canto of

The stanza starts by highlighting the textual distance between Byron’s mentions of Lovelace in the first stanza and that in the current one. To be exact, they are 113 stanzas apart. Perhaps he does this to imply that she has been in the back of his mind through the whole text, through Rousseau and Napoleon and the Alps, and so underlies the themes of Childe Harold’s philosophical wanderings. The reminder of Byron’s relationship with and separation from Lovelace recalls the memory for the reader. That is, the phrase “with thy name this song begun” reminds readers of the first stanza, and by doing so, collapses the distance of 113 stanzas. This collapse is further amplified by the repetition of “My daughter!” in the next line, the first iteration being connected to “begun,” the second to “end.” In a sense, Lovelace serves as an

With that particular phrase, Byron challenges our conception of space and time and leads us to a new way of thinking about their relationship. We might conventionally talk about the length of years in terms of duration, but describing it with “far” is a move that questions the distinction between space and time. Just as Byron collapses 113 stanzas of his text with iterations of “My daughter!”, “far years” collapses the spatial into the temporal through the grammatical relationship between noun and adjective. The temporal noun is described with a spatial term, making time seem concrete and reachable. That is, the denotation of “far years” indexes our conventional conceptions of time and space, while its form inscribes their convolution. If we might eventually reach a far land having sailed enough distance, we might also be able to reach “far years.” But how does this apply to Byron and Lovelace? For one, they were separated by physical distance, Lovelace growing up in England while Byron wandered the Continent. They were also separated by time, for it had been months since Byron last saw her. In another sense, however, the use of the temporal period “years” indicates that Byron also considers the separation between his present time and Lovelace’s, which suggests his speculation that she will eventually read this line in the future, in Lovelace’s own present. Byron creates an imaginative distance between father and daughter for the reader: he roams the Continent and writes to his daughter while she, perhaps years later, reads her father’s poetry.

The quick connection we can make to computer code, in terms of

Before we examine specific instances of how Lovelace’s mathematical notation employs this poetics of writing memory, it is important to understand the machine for which these notations were written. The Analytical Engine, known as the first designed digital computer, was designed by Charles Babbage in 1837. Its main body was a “mill” which contained complex arrangements of gears and a number of mechanical columns, or arms, on which the numerical values to be calculated would be inscribed (See Appendix B for an image of Babbage’s trial model of the Analytical Engine). The operator would provide instructions to the Engine by means of hole-punched cards, inspired by the Jacquard loom, which contained the binary information of the elements of mathematical expressions. The difference between the format of these expressions and that found in conventional mathematics is that the former had to directly affect the material movements of the Engine; equations had to be performed by the machine, rather than remaining in the abstract. The first attempts at computational expressions that considered the materiality of the Engine are found in L. F. Menabrea’s “Sketch of the Analytical Engine Invented,” written in French and translated by Lovelace in 1843.

As Lovelace (_{x}, where “V” symbolized any numerical value and the subscripted index “x” indicated the specific mechanical arm in the Engine on which “V” was inscribed. Lovelace’s revision of Menabrea’s expression was to add a superscript, an upper index, “to indicate any ^{y}V_{x} (See Fig. 2 in Appendix A for concrete examples of this notation used by Lovelace’s algorithm to calculate the Bernoulli numbers through the Analytical Engine). The inclusion of this upper index, the superscripted “y” as the indication of “

The mathematical expression “2^{2},” for example, shows two different uses of the number 2. The first “2” holds a numerical value of 2, which is a conventional arithmetic conception of number. The superscripted “2,” however, while also bearing a numerical value, is an operational function. That is, the symbol “2” is both an object receiving an action and a subject that acts on another number. The expression “2^{2}” could be rewritten as “the numerical value of two multiplied by itself

For instance, Lovelace writes:

^{1}V_{21} + ^{1}V_{31} = ^{2}V_{21}

(Lovelace 714)

Recall that “V” is the arbitrary symbol for any variable number that the engine calculates, the lower indices refer to the physical location of each variable (i.e. the column of the engine), and the upper indices refer to the iteration of each alteration. That is, the upper index labels the current state, hence memory of the specified mechanical arm. As Lovelace writes, the upper indices “furnish a powerful means of tracing back the derivation of any result; and of registering various circumstances concerning that ^{1}V_{21} is the first of the substitution series, differing from ^{2}V_{21} only in terms of the upper index. Thus, we understand that ^{2}V_{21} is the second iteration of a value placed on the twenty-first column of the engine, “merely the final consequence” of this calculation.

The above equation expresses that the number in the twenty-first column of the engine is added to the number in the thirty-first column, and the result is registered onto the twenty-first column. The final result of this calculation replaces the initial numerical value of the twenty-first column, and this replacement is indicated by the upper index of ^{2}V_{21}. In a sense, the engine

Additionally, this process of inscription, or the rewriting of memory, only works when there is a medium on which memory is inscribed. That is, memory is considered in computation because computation is finite and material. On the other hand, algebra, in its abstraction, is infinite and immaterial; therefore space, hence memory, need not be considered. As Lovelace writes, “[t]he bounds of

To see how Lovelace continues to inscribe memory for the Engine, let us consider the next iteration of its twenty-first column:

^{1}V_{33} ÷ 2 + ^{2}V_{21} = ^{3}V_{21}

(Lovelace 715)

Lovelace again alters the memory of this column. She halves the value of the thirty-third column and then adds it to the twenty-first column. The difference in superscripts between ^{2}V_{21} and ^{3}V_{21} indicates that the value on the twenty-first column has changed. Again, the column

(t)he following would be the successive sets of operations for computing the

coefficients of

(×, ×, ÷, ×), (×, ×, ×, ÷, +, +),

Or we might represent them as follows, according to the numerical order of the operations:–

(1, 2 … 4), (5, 6 … 10),

(

In this case, Lovelace uses numbers to denote “numerical order”. But the objects that the numbers order are not numerical values or even alteration of values, as done by the upper indices we have just examined. The novel move Lovelace makes here is taking

As Lovelace (

In the material context of weaving, we might consider

Contemporary conversations surrounding computational methods such as

In the Digital Humanities, debates regarding the efficacy of computational methods in humanities research show the limits of this conflation. The dispute between

In terms of this essay: having inscribed the memory of a Fourier transform into the basis of the computer program, the computer cannot but “remember” its experiences as Fourier transforms. A poetics analysis would show, as Schmidt effectively considers, that the material contexts of the Fourier transform relate to its symbolic inscriptions in ways that might not be conducive for literary analysis. Even the basis of sentiment analysis itself is suspect. The computational method attributes “sentiment” to certain terms based on a predefined dictionary. Andrew Piper and Richard Jean So, for example, used this method to conclude that novels written during the Victorian era are the most sentimental of literatures. They examined about 2,000 novels and “searched for indications of differing levels of sentimentality using dictionaries developed by

For the Victorian who has woven her way through this essay, the connection between mathematics and poetry in the development of algorithms is certainly not a sentimental one. Binary operations, it seems, finds its logic in the cultural pressures of commercial production, and in our century, we continue to reproduce this logic through our computer code. My contention here is that computers still do not have the power to anticipate analytical relations or truths because the intelligence on which their computational powers are based were shaped for economic outcomes. That is, “what we are acquainted with,” in Lovelace’s terms, are data structures that developed from commercialization. That is not to say these structures we have currently developed from computer science are useless; in fact, they have been quite useful. It is certainly useful for self-driving cars to recognize stop signs to promote traffic order and prevent accidents. For those in power, it matters less

I am not suggesting that we impose conventional poetic forms on computer code, though there might be generative possibilities in comparing, say, the structure of a sonnet with that of defining a computational function. Rather, I propose that computer code is already structured in poetic forms. Computational processes, such as iteration, recursion, or while-loops, for example, are symbolic inscriptions that produce material effects; they stage a construction of meaning and memory based on their material contexts. Coding languages underlie the entirety of our digital technologies; and since most of our everyday lives intertwine with the digital, the forms its languages take produce immediate ramifications. Besides using these technologies for computational research, it would be productive for the humanities to be literate in the paradigms that underlie their encodings. Ones and zeros and specifiable algorithmic steps do not just produce new forms of information but, perhaps more importantly to the humanities, transform the ways we handle information and make meaning from it. After all, computer codes are human languages: they are woven with wefts we warp, themselves weaving and unweaving clouds of thought into the electric shawls of our screens.

The additional files for this article can be found as follows:

Diagram of an algorithm for the Analytical Engine for the computation of Bernoulli numbers and close-up of portion of diagram showing the first two rows of algorithmic equations, from “Sketch of The Analytical Engine Invented by Charles Babbage” by Luigi Menabrea. DOI:

Trial model of the Analytical Engine constructed by Charles Babbage. DOI:

That is, Lovelace’s mathematics present a “set of specifiable steps that produce an output” (

For example, a common method in distant reading practices is “term frequency and inverse document frequency,” or tf-idf. This method receives a text and returns the frequency certain words appear in the text, as well as the relationship this frequency has to other words in the text. If a word, say, “computer” is frequent in a certain part of a text but not in another, the researcher might find this significant. Schmidt’s point is that digital humanists need to understand that tf-idf transforms the information of a given text in this way, but that they do not necessarily need to understand the calculations and code that underlie this transformation.

Much scholarship on Lovelace’s work has focused on the biographical circumstances that surround her work (Dorothy Stein, Doron Swade, Betty Alexandra Toole, James Essinger, Benjamin Woolley, Joan Baum, Christopher Hollings). While my essay takes Lovelace’s biography into account, it also attempts to give credence to the sociocultural contexts in England at the time. Lovelace’s Notes, in this essay, is as much a work of intention as it is a symptom of her milieu--it is a “case”: a set of choices made with and against its contexts.

As R.C. Allen (

Tenen’s (

R.C. Allen (

Regarding historical usages of algorithms, Caroline A. Jones writes: “For Victorian engineer Charles Babbage…difference was to be automated for minimum error and maximum utility in the struggle to produce invariant numeric tables for the use of scientists, navigators, and surveyors, but of most burning necessity for actuaries in the burgeoning new commercial insurance trade” (

Essinger (

For example, William Moorcroft, a consultant and agent for the East India Company, concluded that “the techniques involved in the production of shawls could not be allowed to remain in the hands of Kashmiri weavers--whom he described as ingenious but oppressed and fraudulent--they had to be systematized into scientific knowledge through an imperial mediator so as to be more effectively utilized by British industry” (

Zutshi (

Within an imperial context the argument could be extended to legal and bureaucratic discourses as well. Control over matter manifested in imperial rule and the bureaucratic governance of British colonies, reinforced by the industrial innovations that were produced by such a “rational” culture (as opposed to their colonial counterparts, who were stuck in old traditional ways). If we transferred this conversation onto the issue of coding literacy, as was mentioned through the work of Vee previously, we might see a similar power dynamic between the technologically literate and those who are not. In these cases, the distinctions are not made on national lines so much as corporate and material ones. In other words, Apple is now an “Empire on which the sun never sets.” The time told on an iPhone is superior to a wristwatch precisely because of its digital nature.

Imogen Forbes-Macphail (

Betty Alexandra Toole (

In Lev Grossman’s (

I use the term

Jerome Christensen (

In algebra, the notation “x” is used to designate a variable that can encompass any numerical value. Let’s take the equation “x = y + 5” as an example. In this case, the value of “x” would be dependent on “y,” so if we assigned “y = 5,” and substituted this value into the equation, then “x = (5) + 5,” in which case the value of “x” would be 10. Here we clearly see the arbitrariness of the symbols “x” and “y,” though “=,” “+,” and “5” are definite.

It is important to reemphasize that numbers in mathematics are conventionally taken in the arithmetic sense, as numerical values. Abstraction of these values progressed in algebraic notation, where

The author has no competing interests to declare.