<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.3">Jekyll</generator><link href="https://michaelgfalk.github.io/feed.xml" rel="self" type="application/atom+xml"/><link href="https://michaelgfalk.github.io/" rel="alternate" type="text/html" hreflang="en"/><updated>2026-03-27T04:56:57+00:00</updated><id>https://michaelgfalk.github.io/feed.xml</id><title type="html">blank</title><subtitle>Computational literary scholar from the University of Melbourne. </subtitle><entry><title type="html">The Adventures of Modball in the Land of Error</title><link href="https://michaelgfalk.github.io/blog/2026/the-adventures-of-modball-in-the-land-of-error/" rel="alternate" type="text/html" title="The Adventures of Modball in the Land of Error"/><published>2026-02-11T00:00:00+00:00</published><updated>2026-02-11T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2026/the-adventures-of-modball-in-the-land-of-error</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2026/the-adventures-of-modball-in-the-land-of-error/"><![CDATA[]]></content><author><name></name></author><summary type="html"><![CDATA[The metaphor of learning as a moving object becomes more literal.]]></summary></entry><entry><title type="html">Methodological Discourses in the early Computational Human Sciences</title><link href="https://michaelgfalk.github.io/blog/2025/methodological-discourses-in-the-early-computational-human-sciences/" rel="alternate" type="text/html" title="Methodological Discourses in the early Computational Human Sciences"/><published>2025-12-15T00:00:00+00:00</published><updated>2025-12-15T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/methodological-discourses-in-the-early-computational-human-sciences</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/methodological-discourses-in-the-early-computational-human-sciences/"><![CDATA[]]></content><author><name></name></author><summary type="html"><![CDATA[Background The history of Digital Humanities is typically traced back to Humanities Computing, and the seminal research of Fr Roberto Busa SJ (Jones 2016). In the homo calculans project, we aim to provide a broader, interdisciplinary understanding of the origins of computing in the Humanities, Arts and Social Sciences. Drawing inspiration from studies by Sula and Hill (2019) and Kleymann, Niekler, and Burghardt (2022), we have assembled a corpus of 496 pioneering publications in the Computational Humanities, Arts and Social Sciences (HASS) from the 1950s and 60s. We annotate these articles with rich metadata, and subject them to text analysis in order to discover how computing impacted the HASS disciplines in the first two decades of electronic digital computing. To account for the varied disciplines in the corpus, we situate our analysis in the History of the Human Sciences [Smith (1997); smith_what_2020]. In the early days of computational research, the community of computational scholars was relatively small, and disciplinary boundaries were porous. A pioneering researcher such as Jean-Claude Gardin could easily make original contributions to both Anthropology (Gardin 1965a) and Archaeology (Gardin 1965b), drawing on Literary Studies, Sociometry (Social Network Analysis) and Geography for methodological insights. By adopting the “Computational Human Sciences” as our object of study, we have been able to generate both a highly multidisciplinary corpus and a coherent set of research questions. There is no single accepted definition of the Human Sciences. For the sake of our analysis, we adopt the definition given by Ernst Cassirer in his Logik der Kulturwisschaften (1961). In Logik, Cassirer identifies “human action” [menschliches Handeln] as the common object of what he calls the “Cultural Sciences.” The distinctive feature of “human action,” according to Cassirer, is its “mediatedness” [Mittelbarkeit]. Human actions and artefacts are not simply physical objects, but “forms of expression” [Ausdrucksformen], mediated by symbols, which require interpretation (Cassirer 1980, 26, 51). Broadly speaking, the documents in our corpus fall into Cassirer’s definition, because they comprise early attempts to model or analyse human actions using computers, whether these actions are votes, purchases, historical deeds, acts of literary composition, or new pieces of music. The central problem raised by Cassirer’s definition is familiar to researchers in the Digital Humanities today: the problem of meaning (see e.g. Liu 2013). How can a dull, cold computer possibly enlighten us about the lively, fleshy meaning of all-to-human acts and symbols? This is a problem for us today, even in the age of lightning-fast personal computers and dazzling AI models. In the 1950s and 60s, researchers in the Human Sciences were faced with large, difficult, inaccessible devices locked away in University Computing Centres, and had to justify their methods to scholarly colleagues who might not even have computer access. It is in this context that we propose our three research questions: RQ1. What were the central methods of study across the different disciplines? RQ2. How did scholars explain and justify their new methods? What rhetorical or affective devices did they use to obtain acceptance for their results? RQ3. How can this history help us understand the breadth of Computational Human Sciences today? The Corpus The corpus for this study includes 496 publications published between 1950 and 1969 (Table&nbsp;1). The corpus is in the form of a Zotero library, which can be viewed online, though without full-text access for copyright reasons1 While most publications presented original research, the corpus also included reviews and conference reports. All items were written in English as the search was conducted in this language. Table&nbsp;1 Document Type n journalArticle 355 bookSection 122 book 8 conferencePaper 8 magazineArticle 2 report 1 The corpus was built using purposeful snowball sampling. First, we started with Guetzkow (1962), tracing both its cited references and subsequent citations within the 1950 to 1969 timeframe. This process yielded 88 sources. Next, we examined the journal Behavioral Science, which featured a ‘Computers in Behavioral Science’ section from 1959 to 1967, identifying 112 relevant sources. This concentration likely explains the relative over-representation of behavioural science and psychology within the corpus. We then reviewed the journal Computers and the Humanities (1967–1969), locating 73 sources, as well as the 1966 annual bibliography published in 1967, which yielded 67 additional references. We did not proceed beyond 1966 due to the rapidly increasing volume of references. We then included papers from three well-known multi-disciplinary collections of the 1960s, including Bessinger, Parrish, and Arader (1964), Hymes (1965) and Stone et al. (1966). At this point, we observed that several disciplines, such as Religious Studies and History/Cliometrics were under-represented. To complete the search, therefore, we conducted targeted Google Scholar searches using the keywords ‘discipline + computer’, which added 31 sources. Items in the corpus were systematically tagged for discipline and computer. We determined the disciplines of each text and any computers by reading the abstract and, if necessary, the text. Our approach was inspired by Sula and Hill (2019), but differs in an important respect. Sula and Hill (2019) determine the discipline of an article by inspecting the author affiliation. Our approach prioritises how the sources themselves framed disciplinary identity and computational engagement. High-level statistics on the discipline and computer tags are show in Table&nbsp;2 and Figure&nbsp;1. At the time of writing this abstract, we have not fully normalised the discipline tags, though we intend to do so. Table&nbsp;2: Musicology is surprisingly well represented. Discipline n Psychology 71 Behavioural science 48 Literary Studies 46 Musicology 42 Linguistics 35 Statistics 35 Anthropology 29 Political Science 27 Interdisciplinary 23 History 17 Visual Arts 16 Sociology 15 Humanities 11 Archaeology 10 Economics 10 Machine Translation 10 Geography 9 Religious Studies 9 Natural Language Processing 7 Management Science 5 Art History 4 Cliometrics 4 Education 4 Classics 3 Business 2 Demography 2 Library Studies 2 History 1 Accounting 1 Marketing 1 Museum 1 Organizational behavior 1 Performing Arts 1 Philosophy 1 Simulation??? 1 Taxation 1 Figure&nbsp;1: The graph reflects IBM’s market dominance and early sponsorship of Humanities Computing. The meaning of ‘experiment’ To understand the range of methods (RQ1) and their justification (RQ2), we investigate keywords in the corpus using various text-analytic techniques. In this abstract, we show just one of these techniques: lexical network analysis. Figure&nbsp;2 and Figure&nbsp;3 show lexical networks for the word “experiment” in the Psychology (n=71) and Literary Studies (n=46) articles in the corpus. To produce these networks, the documents are split into 200-word chunks, pairwise correlations are computed between all the words, the data is converted into a graphical format using iGraph, edges are dropped between words if their pairwise correlation is less than 0.35, and then the neighbourhood of order 2 is shown for the target word (in this case, “experiment”). In a nutshell, the figures show the most closely associated words with the target word, along with the associated words’ most associated words. Figure&nbsp;2: Most highly correlated words with “experiment” and its neighbours, in 200-word chunks from the Psychology articles. Figure&nbsp;3: Most highly correlated words with “experiment” and its neighbours, in 200-word chunks from the Literary Studies articles. As can be seen, the discourse of “experiment” differs markedly in the Psychology and Literary Studies articles. In the Literary Studies articles, the experiment is the use of computers. Close associates of the word “experiment” include the names of popular contemporary machines (e.g.&nbsp;the IBM 1401 or 1620), and words describing the concrete process of using the computer (hours, processed, verified, disk, arranged, etc.). The discourse in Psychology is nothing like this. In the 1950s and 1960s, Psychology was already established as an “experimental” discipline, especially in the United States, where most of our corpus originates. Here the computer is talked about in a more abstract way, as an existing experimental paradigm is computerized, perhaps with a corresponding reduction of effort. The nature of computation As well as investigating particular methods or methodological concepts, we also investigate the concept “computational” itself. One of the most fruitful lines of inquiry is metaphor: As you know by now, if you have been following these lectures, computers are not giant brains at all; they are giant clerks. (Green 1961, 227) The words “clerk” or “clerical” (including plurals and other derivations) appear in 79 articles in the corpus. Close reading of these instances indicates that there was a fluid boundary between metaphorical and literal clerks in the early days of the Computational Human Sciences. Sometimes, a computer would be gradually programmed by a research group to resemble their human clerks, until the human clerks no longer found employment in the research. Some researchers found this metaphor uninspiring: We are still not thinking of the computer as anything but a myriad of clerks or assistants in one convenient console. Most of the results I have just described could have been accomplished with the available means of half a century ago. We do not yet understand the true nature of the computer. And we have not yet begun to think in ways appropriate to the nature of this machine.(Milic 1966, 4) Researchers in this school tried to push the Computational Human Sciences furhter into the new field of Artificial Intelligence. Perhaps the computer could think differently, and allow the researcher to pose new questions. One researcher who argued this was was Gardin, who insisted that in the the process of scholar-computer interaction, the computer could gradually move beyond “clerical drudgery,” and take over the “‘intelligent’ functions of problem-solving” normally reserved to the scholar who leads the research team. The computer-as-clerk was one solution to the problem of meaning. In this metaphor, the computer merely automated non-scholarly tasks hitherto undertaken by clerical staff, rather than by the scholar her- or himself. This metaphor vividly evokes the social, moral and cultural situation of humanistic and social-scientific research in the 1950s and 60s, and provides further reflection on the origins of Digital Humanities, and the values encoded in our methods today. The computer-as-intelligence was then, and remains now, a radical proposition about the nature of human and machine reasoning, whose implications are as thrilling—and frightening—as they were in the 1950s and 60s. Conclusion Researchers in the Human Sciences adopted computational methods enthusiastically as soon as high-speed digital computers became available at the end of the 1940s. This is the first study to systematically compare the epistemic and cultural impacts of computing across the Human Sciences in the first two decades of computing. Although researchers brought different disciplinary assumptions to computing, the fundamental problem of the computer’s meaningless was common across the disciplines. Researchers proposed different solutions to this problem. Sometimes they accomodated computers into existing social structures, casting them as “clerks” which merely automated low-value work in the lab or library. Sometimes they cast their work as more “experimental,” considering ways that computers might actually alter the very nature of their disciplines. We have only scratched the surface in this abstract, and hope to present a fuller picture in the full paper. References Bessinger, Jess B. Jr., Stephen M. Parrish Parrish, and Harry F. Arader, eds. 1964. Literary Data Processing Conference Proceedings. New York: IBM. Cassirer, Ernst. 1980. Zur Logik Der Kulturwissenschaften: Fünf Studien. Darmstadt: Wissenschafltiche Buchgesellschaft. Gardin, J. C. 1965a. “A Typology of Computer Uses in Anthropology.” In The Use of Computers in Anthropology, edited by Dell Hymes, 103–18. Berlin, New York: DE GRUYTER MOUTON. https://doi.org/10.1515/9783111718101.103. ———. 1965b. “Reconstructing an Economic Network in the Ancient East with the Aid of a Computer.” In The Use of Computers in Anthropology, edited by Dell H. Hymes and Wenner-Gren Foundation For Anthropo, 377–92. Berlin, New York: DE GRUYTER MOUTON. https://doi.org/10.1515/9783111718101.377. Green, Bert F. 1961. “Using Computers to Study Human Perception.” Educational and Psychological Measurement 21 (1): 227–33. https://doi.org/10.1177/001316446102100123. Guetzkow, Harold Steere. 1962. Simulation in Social Science; Readings. Englewood Cliffs, N.J., Prentice-Hall. http://archive.org/details/simulationinsoci0000guet. Hymes, Dell H., ed. 1965. The Use of Computers in Anthropology: DE GRUYTER MOUTON. https://doi.org/10.1515/9783111718101. Jones, Steven E. 2016. Roberto Busa, S. J. , and the Emergence of Humanities Computing: The Priest and the Punched Cards. London, UNITED KINGDOM: Taylor &amp; Francis Group. Kleymann, Rabea, Andreas Niekler, and Manuel Burghardt. 2022. “Conceptual Forays: A Corpus-Based Study of ‘Theory’ in Digital Humanities Journals.” Journal of Cultural Analytics 7 (4). https://doi.org/10.22148/001c.55507. Liu, Alan. 2013. “The Meaning of the Digital Humanities.” PMLA 128 (2): 409–23. http://www.jstor.org/stable/23489068. Milic, Louis T. 1966. “The Next Step.” Computers and the Humanities 1 (1): 3–6. https://www.jstor.org/stable/30199191. Smith, Roger. 1997. The Fontana History of the Human Sciences. London: Fontana. Stone, Philip J., Dexter Dunphy, Daniel M. Ogilvie, and Marshall S. Smith, eds. 1966. The General Inquirer: A Computer Approach to Content Analysis. Cambridge, Mass: M.I.T. Press. Sula, Chris Alen, and Heather V Hill. 2019. “The Early History of Digital Humanities: An Analysis of Computers and the Humanities (1966–2004) and Literary and Linguistic Computing (1986–2004).” Digital Scholarship in the Humanities, November, fqz072. https://doi.org/10.1093/llc/fqz072. Footnotes https://www.zotero.org/groups/5939021/homo-calculans-corpus↩︎]]></summary></entry><entry><title type="html">‘Artificial intelligence’ myths have existed for centuries – from the ancient Greeks to a pope’s chatbot</title><link href="https://michaelgfalk.github.io/blog/2025/conversation-ai-myths/" rel="alternate" type="text/html" title="‘Artificial intelligence’ myths have existed for centuries – from the ancient Greeks to a pope’s chatbot"/><published>2025-12-11T00:00:00+00:00</published><updated>2025-12-11T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/conversation-ai-myths</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/conversation-ai-myths/"><![CDATA[<div class="theconversation-article-body"> <figure> <img src="https://images.theconversation.com/files/704714/original/file-20251126-56-vqq3nc.jpg?ixlib=rb-4.1.0&amp;rect=0%2C0%2C1582%2C934&amp;q=45&amp;auto=format&amp;w=754&amp;fit=clip"/> <figcaption> Prometheus – Heinrich Füger (c.1817) <span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Heinrich_fueger_1817_prometheus_brings_fire_to_mankind.jpg">Public domain, via Wikimedia Commons</a></span> </figcaption> </figure> <span><a href="https://theconversation.com/profiles/michael-falk-419993">Michael Falk</a>, <em><a href="https://theconversation.com/institutions/the-university-of-melbourne-722">The University of Melbourne</a></em></span> <p>It seems the AI hype has turned into an <a href="https://theconversation.com/yes-there-is-an-ai-investment-bubble-here-are-three-scenarios-for-how-it-could-end-269525">AI bubble</a>. There have been many bubbles before, from the <a href="https://en.wikipedia.org/wiki/Tulip_mania">Tulip mania</a> of the 17th century to the <a href="https://en.wikipedia.org/wiki/Subprime_mortgage_crisis">derivatives bubble</a> of the 21st century. For many commentators, the most relevant precedent today is the <a href="https://youtu.be/ZIbEn5oH4jA?si=nAdwGeAtaPaAkvyu">dotcom bubble</a> of the 1990s. Back then, a new technology (the <a href="https://en.wikipedia.org/wiki/World_Wide_Web">World Wide Web</a>) unleashed a wave of “<a href="https://en.wikipedia.org/wiki/Irrational_exuberance">irrational exuberance</a>”. Investors poured billions into any company with “.com” in the name. </p> <p>Three decades later, another new technology has unleashed another wave of exuberance. Investors are pouring billions into any company with “AI” in its name. But there is a crucial difference between these two bubbles, which isn’t always recognised. The World Wide Web existed. It was real. General Artificial Intelligence does not exist, and no one knows <em>if</em> or <em>when</em> it ever will. </p> <p>In February, the CEO of OpenAI, Sam Altman, wrote on his blog that the very latest systems have only just started to “<a href="https://blog.samaltman.com/three-observations">point towards</a>” AI in its “<a href="https://theconversation.com/not-everything-we-call-ai-is-actually-artificial-intelligence-heres-what-you-need-to-know-196732">general</a>” sense. OpenAI may market its products as “AIs”, but they are merely <a href="https://theconversation.com/nvidia-ceo-jensen-huang-has-been-called-the-ai-oppenheimer-but-he-dismisses-concerns-ai-is-just-processing-data-256583">statistical data-crunchers</a>, rather than “intelligences” in the sense that human beings are intelligent.</p> <p>So why are investors so keen to give money to the people selling AI systems? One reason might be that AI is a <em>mythical</em> technology. I don’t mean it is a lie. I mean it evokes a powerful, foundational story of Western culture about human powers of creation. </p> <p>Perhaps investors are willing to believe AI is just around the corner because it taps into myths that are deeply ingrained in their imaginations?</p> <h2>The myth of Prometheus</h2> <p>The most relevant myth for AI is the Ancient Greek myth of Prometheus. </p> <p>There are many versions of this myth, but the most famous are found in <a href="https://en.wikipedia.org/wiki/Hesiod">Hesiod</a>’s poems <a href="https://chs.harvard.edu/primary-source/hesiod-theogony-sb/">Theogony</a> and <a href="https://chs.harvard.edu/primary-source/hesiod-works-and-days-sb/">Works and Days</a>, and in the play <a href="https://classics.mit.edu/Aeschylus/prometheus.html">Prometheus Bound</a>, traditionally attributed to <a href="https://en.wikipedia.org/wiki/Aeschylus">Aeschylus</a>. </p> <p>Prometheus was a Titan, a god in the Ancient Greek pantheon. He was also a criminal who stole fire from Hephaestus, the blacksmith god. Hiding the fire in a stalk of fennel, Prometheus came to earth and gave it to humankind. As punishment, he was chained to a mountain, where an eagle visited every day to eat his liver.</p> <p>Prometheus’ gift was not simply the gift of fire; it was the gift of intelligence. In Prometheus Bound, he declares that before his gift humans saw without seeing and heard without hearing. After his gift, humans could write, build houses, read the stars, perform mathematics, domesticate animals, construct ships, invent medicines, interpret dreams and give proper offerings to the gods.</p> <p>The myth of Prometheus is a creation story with a difference. In the Hebrew Bible, God does not give Adam the power to create life. But Prometheus gives (some of) the gods’ creative power to humankind.</p> <p>Hesiod indicates this aspect of the myth in Theogony. In that poem, Zeus not only punishes Prometheus for the theft of fire; he punishes humankind as well. He orders Hephaestus to fire up his forge and construct the first woman, Pandora, who unleashes evil on the world.</p> <p>The fire that Hephaestus uses to make Pandora is the same fire that Prometheus has given humankind.</p> <figure class="align-center "> <img alt="Prometheus manufacturing the first man, in an eighteenth-century engraving of an ancient gem in the Carafa Collection." src="https://images.theconversation.com/files/703539/original/file-20251119-56-bo2o9v.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=754&amp;fit=clip" srcset="https://images.theconversation.com/files/703539/original/file-20251119-56-bo2o9v.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=600&amp;h=422&amp;fit=crop&amp;dpr=1 600w, https://images.theconversation.com/files/703539/original/file-20251119-56-bo2o9v.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=600&amp;h=422&amp;fit=crop&amp;dpr=2 1200w, https://images.theconversation.com/files/703539/original/file-20251119-56-bo2o9v.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=600&amp;h=422&amp;fit=crop&amp;dpr=3 1800w, https://images.theconversation.com/files/703539/original/file-20251119-56-bo2o9v.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=754&amp;h=531&amp;fit=crop&amp;dpr=1 754w, https://images.theconversation.com/files/703539/original/file-20251119-56-bo2o9v.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=754&amp;h=531&amp;fit=crop&amp;dpr=2 1508w, https://images.theconversation.com/files/703539/original/file-20251119-56-bo2o9v.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=754&amp;h=531&amp;fit=crop&amp;dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"/> <figcaption> <span class="caption">In this 18th-century engraving, Prometheus constructs the first man.</span> <span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:PrometheusCarrafa25.jpg">Wikimedia Commons</a></span> </figcaption> </figure> <p>The Greeks proposed the idea that <em>humans</em> are a form of artificial intelligence. Prometheus and Hephaestus use technology to manufacture men and women. As historian Adrienne Mayor reveals in her book <a href="https://press.princeton.edu/books/hardcover/9780691183510/gods-and-robots">Gods and Robots</a>, the ancients often depicted Prometheus as a craftsman, using ordinary tools to create human beings in an ordinary workshop.</p> <p>If Prometheus gave us the fire of the gods, it would seem to follow that we can use this fire to make our own intelligent beings. Such stories abound in Ancient Greek literature, from the inventor Daedalus, who created statues that came to life, to the witch Medea, who could restore youth and potency with her cunning drugs. Greek inventors also constructed <a href="https://www.nature.com/articles/s41598-021-84310-w">mechanical computers for astronomy</a> and remarkable moving figures <a href="https://www.jstor.org/stable/j.ctv18msqmt.10?seq=4">powered by gravity, water and air</a>.</p> <h2>The Pope and the chatbot</h2> <p>2,700 years have passed since Hesiod first wrote down the story of Prometheus. In the ensuing centuries, the myth has been endlessly retold, especially since the publication of Mary Shelley’s <a href="https://theconversation.com/frankenstein-how-mary-shelleys-sci-fi-classic-offers-lessons-for-us-today-about-the-dangers-of-playing-god-175520">Frankenstein; or the Modern Prometheus</a> in 1818.</p> <p>But the myth is not always told as fiction. Here are two historical examples where the myth of Prometheus seemed to come true.</p> <p><a href="https://www.britannica.com/biography/Sylvester-II">Gerbert of Aurillac</a> was the Prometheus of the 10th century. He was born in the early 940s CE, went to school at <a href="https://en.wikipedia.org/wiki/Aurillac_Abbey">Aurillac Abbey</a>, and became a monk himself. He proceeded to master every known branch of learning. In the year 999, he was elected Pope. He died in 1003 under his pontifical name, Sylvester II.</p> <p>Rumours about Gerbert spread wildly across Europe. Within a century of his death, his life had already become legend. One of the most famous legends, and the most pertinent in our age of AI hype, is that of Gerbert’s “brazen head”. The legend was told in the 1120s by the English historian <a href="https://en.wikipedia.org/wiki/William_of_Malmesbury">William of Malmesbury</a>, in his well researched and highly regarded book, Deeds of the English Kings. </p> <p>Gerbert was deeply learned in astronomy, a science of prediction. Astronomers could use the <a href="https://en.wikipedia.org/wiki/Astrolabe">astrolabe</a> to predict the position of the stars and foresee cosmological events such as eclipses. According to William, Gerbert used his knowledge of astronomy to construct a talking head. After inspecting the movements of the stars and planets, he cast a head in bronze that could answer yes-or-no questions.</p> <p>First Gerbert asked the head: “Will I become Pope?” </p> <p>“Yes,” answered the head. </p> <p>Then Gerbert asked: “Will I die before I sing mass in Jerusalem?” </p> <p>“No,” the head replied. </p> <p>In both cases, the head was correct, though not as Gerbert anticipated. He did become Pope, and he sensibly avoided going on pilgrimage to Jerusalem. One day, however, he sang mass at <a href="https://en.wikipedia.org/wiki/Santa_Croce_in_Gerusalemme">Santa Croce in Gerusalemme</a> in Rome. Unfortunately for Gerbert, Santa Croce in Gerusalemme was known in those days simply as “Jerusalem”.</p> <p>Gerbert sickened and died. On his deathbed, he asked his attendants to cut up his body and cast away the pieces, so he could go to his true master, Satan. In this way, he was, like Prometheus, punished for his theft of fire. </p> <figure class="align-left zoomable"> <a href="https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=1000&amp;fit=clip"><img alt="" src="https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=237&amp;fit=clip" srcset="https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=600&amp;h=588&amp;fit=crop&amp;dpr=1 600w, https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=600&amp;h=588&amp;fit=crop&amp;dpr=2 1200w, https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=600&amp;h=588&amp;fit=crop&amp;dpr=3 1800w, https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=754&amp;h=739&amp;fit=crop&amp;dpr=1 754w, https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=754&amp;h=739&amp;fit=crop&amp;dpr=2 1508w, https://images.theconversation.com/files/704713/original/file-20251126-56-teuxhj.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=754&amp;h=739&amp;fit=crop&amp;dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"/></a> <figcaption> <span class="caption">Pope Sylvester II and the Devil.</span> <span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Silvester_II._and_the_Devil_Cod._Pal._germ._137_f216v_(cropped).jpg">Public domain, via Wikimedia Commons</a></span> </figcaption> </figure> <p>It is a thrilling story. It is not clear whether William of Malmesbury actually believed it. But he does try to persuade his readers that it is plausible. Why did this great historian with a devotion to the truth insert some fanciful legends about a French pope into his history of England? Good question!</p> <p>Is it so fanciful to believe that an advanced astronomer might build a general-purpose prediction machine? In those days, astronomy was the most powerful science of prediction. The sober and scholarly William was at least willing to entertain the idea that brilliant advances in astronomy might make it possible for a Pope to build an intelligent chatbot.</p> <p>Today, that same possibility is credited to machine-learning algorithms, which can predict which ad you will click, which movie you will watch, which word you will type next. We can be forgiven for falling under the same spell.</p> <h2>The anatomist and the automaton</h2> <p>The Prometheus of the 18th century was Jacques de Vaucanson, at least <a href="https://gallica.bnf.fr/ark:/12148/bpt6k1064220h/f61.image.r=promethee">according to Voltaire</a>:</p> <blockquote> <p>Bold Vaucanson, rival of Prometheus,<br/> Seems, imitating the springs of nature,<br/> To steal the fire of heaven to animate the body.<br/></p> </blockquote> <figure class="align-right zoomable"> <a href="https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=1000&amp;fit=clip"><img alt="" src="https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=237&amp;fit=clip" srcset="https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=600&amp;h=763&amp;fit=crop&amp;dpr=1 600w, https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=600&amp;h=763&amp;fit=crop&amp;dpr=2 1200w, https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=600&amp;h=763&amp;fit=crop&amp;dpr=3 1800w, https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=754&amp;h=959&amp;fit=crop&amp;dpr=1 754w, https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=754&amp;h=959&amp;fit=crop&amp;dpr=2 1508w, https://images.theconversation.com/files/704706/original/file-20251126-64-epado4.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=754&amp;h=959&amp;fit=crop&amp;dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"/></a> <figcaption> <span class="caption">Jacques de Vaucanson – Joseph Boze (1784).</span> <span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Jacques_de_Vaucanson_rectangular.jpg">Public domain, via Wikimedia Commons</a></span> </figcaption> </figure> <p>Vaucanson was a great machinist, famous for his <a href="https://en.wikipedia.org/wiki/Automaton">automata</a>. These were clockwork devices that realistically simulated human or animal anatomy. Philosophers of the time believed that the body was a machine – so why couldn’t a machinist build one?</p> <p>Sometimes Vaucanson’s automata were scientifically significant. He constructed a piper, for example, that had lips and lungs and fingers, and blew the pipe in much the same way a human would. Historian Jessica Riskin explains in her book <a href="https://press.uchicago.edu/ucp/books/book/chicago/R/bo21519800.html">The Restless Clock</a> that Vaucanson had to make significant discoveries in acoustics in order to make his piper play in tune.</p> <p>Sometimes his automata were less scientific. His <a href="https://historyofinformation.com/detail.php?id=412">digesting duck</a> was hugely famous, but turned out to be fraudulent. It appeared to eat and digest food, but its poos were in fact prefabricated pellets hidden inside the mechanism.</p> <p>Vaucanson spent decades working on what he called a “moving anatomy”. In 1741, he presented a plan to the Lyons Academy to build an “imitation of all animal operations”. Twenty years later, he was at it again. He secured support from King Louis XV to build a simulation of the circulatory system. He claimed he could build a complete, living artificial body.</p> <figure class="align-center zoomable"> <a href="https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=1000&amp;fit=clip"><img alt="" src="https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=754&amp;fit=clip" srcset="https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=600&amp;h=320&amp;fit=crop&amp;dpr=1 600w, https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=600&amp;h=320&amp;fit=crop&amp;dpr=2 1200w, https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=600&amp;h=320&amp;fit=crop&amp;dpr=3 1800w, https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=754&amp;h=402&amp;fit=crop&amp;dpr=1 754w, https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=30&amp;auto=format&amp;w=754&amp;h=402&amp;fit=crop&amp;dpr=2 1508w, https://images.theconversation.com/files/704711/original/file-20251126-74-gx4f2x.jpg?ixlib=rb-4.1.0&amp;q=15&amp;auto=format&amp;w=754&amp;h=402&amp;fit=crop&amp;dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"/></a> <figcaption> <span class="caption">Three of Vaucanson’s famous automata: the Flute Player, the Digesting Duck, and the Provençal Farmer, who played the pipe and tambourine.</span> <span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Jouets_M%C3%A9caniques_de_Vaucanson_;_Un_Sauvage,_un_berger_provencal_et_un_canard_cropped.jpg">Public domain, via Wikimedia Commons</a></span> </figcaption> </figure> <p>There is no evidence that Vaucanson ever completed a whole body. In the end, he couldn’t live up to the hype. But many of his contemporaries believed he could do it. They <em>wanted</em> to believe in his magical mechanisms. They <em>wished</em> he would seize the fire of life.</p> <p>If Vaucanson could manufacture a new human body, couldn’t he also repair an existing one? This is the promise of some AI companies today. According to Dario Amodei, CEO of Anthropic, AI will <a href="https://www.darioamodei.com/essay/machines-of-loving-grace#1-biology-and-health">soon allow people</a> “to live as long as they want”. Immortality seems like an attractive investment.</p> <p>Sylvester II and Vaucanson were great technologists, but neither was a Prometheus. They stole no fire from the gods. Will the aspiring Prometheans of Silicon Valley succeed where their predecessors have failed? If only we had Sylvester II’s brazen head, we could ask it.<img src="https://counter.theconversation.com/content/270175/count.gif?distributor=republish-lightbox-basic" alt="The Conversation" width="1" height="1" style="border: none !important; box-shadow: none !important; margin: 0 !important; max-height: 1px !important; max-width: 1px !important; min-height: 1px !important; min-width: 1px !important; opacity: 0 !important; outline: none !important; padding: 0 !important" referrerpolicy="no-referrer-when-downgrade"/></p> <p><span><a href="https://theconversation.com/profiles/michael-falk-419993">Michael Falk</a>, Senior Lecturer in Digital Studies, <em><a href="https://theconversation.com/institutions/the-university-of-melbourne-722">The University of Melbourne</a></em></span></p> <p>This article is republished from <a href="https://theconversation.com">The Conversation</a> under a Creative Commons license. Read the <a href="https://theconversation.com/artificial-intelligence-myths-have-existed-for-centuries-from-the-ancient-greeks-to-a-popes-chatbot-270175">original article</a>.</p> </div>]]></content><author><name></name></author><category term="research"/><category term="artificial-intelligence"/><category term="literature"/><summary type="html"><![CDATA[The AI bubble is interesting, because investors are pouring billions into a technology that doesn't exist yet. Some ancient, powerful, seductive myths could be to blame for their exuberance.]]></summary></entry><entry><title type="html">LISP Invites Serious Philosophising</title><link href="https://michaelgfalk.github.io/blog/2025/lisp-invites-serious-philosophising/" rel="alternate" type="text/html" title="LISP Invites Serious Philosophising"/><published>2025-12-11T00:00:00+00:00</published><updated>2025-12-11T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/lisp-invites-serious-philosophising</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/lisp-invites-serious-philosophising/"><![CDATA[]]></content><author><name></name></author><summary type="html"><![CDATA[My recap of our 3-hour workshop at DHA25]]></summary></entry><entry><title type="html">Homo Calculans</title><link href="https://michaelgfalk.github.io/blog/2025/homo-calculans/" rel="alternate" type="text/html" title="Homo Calculans"/><published>2025-12-04T00:00:00+00:00</published><updated>2025-12-04T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/homo-calculans</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/homo-calculans/"><![CDATA[]]></content><author><name></name></author><summary type="html"><![CDATA[We present our initial analysis of the homo calculans corpus at DHA25. You can view the slides here.]]></summary></entry><entry><title type="html">Digital Humanities Australaisa ‘25</title><link href="https://michaelgfalk.github.io/blog/2025/dha25/" rel="alternate" type="text/html" title="Digital Humanities Australaisa ‘25"/><published>2025-11-30T00:00:00+00:00</published><updated>2025-11-30T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/dha25</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/dha25/"><![CDATA[<p><a href="https://dha25.org">DHA25</a> is upon us. So is the annual meeting of the <a href="https://inke.ca/re-defining-open-social-scholarship-in-an-age-of-generative-intelligence/">Canadian Australian Partnership for Open Scholarship</a>. I have had great fun putting the conference together as a member of the <a href="https://aa-dh.org">aaDH Executive</a> and <a href="https://dha25.org/info/organisers/">conference organising committee</a>. I will be giving quite a few presentations at the conference. I’ve collected all the slides here where I’m first author:</p> <h2 id="tuesday-2nd-december-at-the-capos-meeting">Tuesday 2nd December, at the <a href="https://inke.ca/re-defining-open-social-scholarship-in-an-age-of-generative-intelligence/">CAPOS meeting</a></h2> <p>I’m presenting my research on the Abstract Wikipedia project: <a href="https://michaelgfalk.quarto.pub/wikilambda-the-ultimate/">Wikilambda the Ultimate</a>.</p> <p>I’m giving a short reflection on the question, <a href="https://michaelgfalk.quarto.pub/what-would-it-take-for-ai-to-be-open/">What would it take for AI to be open?</a> (I’m greatly inspired by the <a href="https://www.swiss-ai.org/apertus">Swiss AI</a> project.)</p> <h2 id="wednesday-the-3rd-at-dha25-day-1">Wednesday the 3rd, at DHA25 Day 1</h2> <p>I’m presenting with Nick Thieberger and Peter Sefton on <em>ROCrate for a data commons</em>. I’m there mostly for my work on the <a href="https://figshare.unimelb.edu.au/projects/OHRM_Upload_Project/230466">OHRM Upload Project</a>.</p> <h2 id="thursday-the-4th-at-dha-day-2">Thursday the 4th, at DHA Day 2</h2> <p>I’m running a Critical Code Studies workshop with the <a href="https://anticodians.org">Anticodians</a>, where we will close-read Peter Norvig’s <a href="https://colab.research.google.com/drive/1slHI9tYeP4sSP-c1FCVnK0VFs3g_tejq"><em>lis.py</em> essay</a> (<a href="https://www.norvig.com/lispy.html">here’s the original</a>). To kick things off, I will give a lightning talk on <a href="https://michaelgfalk.quarto.pub/scheme-and-its-ideologies/">Scheme and its Ideologies</a>.</p> <p>In the afternoon, I will present some of the work that Niles Zhao and I have done on the <a href="https://homo-calculans.blog"><em>homo calculans</em></a> project. <a href="https://michaelfalk.io/homo-calculans-presentation">Here are the slides</a>.</p> <h2 id="friday-the-5th-at-dha-day-3">Friday the 5th, at DHA Day 3</h2> <p>I’m not presenting. (Phew!) But I’ll be chairing a panel with <a href="https://www.fiannualamorgan.com/">Finn Morgan</a> and Claire Loughnane, my colleagues from Melbourne, and Francesca Sidoti, my colleague on the <a href="https://wikihistories.net">wikihistories</a> project.</p>]]></content><author><name></name></author><category term="research"/><category term="digital-humanities"/><category term="presentations"/><summary type="html"><![CDATA[My presentations at the biennial meeting of Australasian DHers]]></summary></entry><entry><title type="html">A Plethora of Models</title><link href="https://michaelgfalk.github.io/blog/2025/a-plethora-of-models/" rel="alternate" type="text/html" title="A Plethora of Models"/><published>2025-10-08T00:00:00+00:00</published><updated>2025-10-08T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/a-plethora-of-models</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/a-plethora-of-models/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">The homo calculans corpus</title><link href="https://michaelgfalk.github.io/blog/2025/the-homo-calculans-corpus/" rel="alternate" type="text/html" title="The homo calculans corpus"/><published>2025-08-05T00:00:00+00:00</published><updated>2025-08-05T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/the-homo-calculans-corpus</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/the-homo-calculans-corpus/"><![CDATA[]]></content><author><name></name></author><summary type="html"><![CDATA[A corpus! A corpus! Thanks to the hard work of Niles Zhao, the homo calculans project now possesses a corpus of articles, books and chapters from the early years of the Computational Human Sciences. The field was vaster than either of us expected. When we started the project, I expected that we would be able to get essentially all the articles from the period that reported on computer-enabled research. Boy was I wrong. By the mid-1960s, there was already a large community of computational humanists and social scientists, and research methods were rapidly maturing. Experimentalism was rife. Computer power was, it seems, relatively abundant. In this post, I will just sketch the outlines of the corpus, relying on the metadata Niles has collected about the articles, books, and chapters, and the annotations he has made about research disciplines and the available hardware. Code corpus &lt;- readr::read_csv("corpus-2025-initial.csv",) |&gt; # normalise tags dplyr::mutate(tag = stringr::str_split(`Manual Tags`, ";")) |&gt; dplyr::mutate(tag = purrr::map(tag, \(t) stringr::str_trim(t))) corpus_n &lt;- nrow(corpus) corpus_n_with_text &lt;- corpus |&gt; dplyr::filter(!is.na(`File Attachments`)) |&gt; nrow() types_n &lt;- unique(corpus$`Item Type`) |&gt; length() What’s in it? In this present state, the corpus includes 399 academic texts. We have pdfs for 387 of these, though hopefully we will be able to increase this proportion before the project ends. The corpus includes 6 kinds of text, though it is dominated by Journal Articles, as shown in Figure&nbsp;1. Code corpus |&gt; ggplot2::ggplot(ggplot2::aes(`Item Type`)) + ggplot2::geom_bar() + ggplot2::scale_x_discrete(labels = c( "book" = "Book", "bookSection" = "Chapter", "conferencePaper" = "Conference Paper", "journalArticle" = "Journal Article", "magazineArticle" = "Magazine Article", "report" = "Report" )) Figure&nbsp;1: The items in the corpus are mostly journal articles, as expected. Which disciplines are represented? Who was doing this research in the 1950s and 60s? Which disciplines were at the forefront? We were hoping to be able to give crisp, empirical answers to these questions, but the literature turned out to be so large that is has proven hard to sample the population. For now, we can just see which disciplines appear to be represented in the corpus that we have. Niles tagged the items in Zotero, which is great because it is flexible, but not so great because the tags are unstructured. First we need to sort the tags into two groups: discipline tags and technology tags. Code # Get list of tags for categorisation corpus |&gt; tidyr::unnest(c(tag)) |&gt; dplyr::distinct(tag) |&gt; dplyr::mutate(tag_category = "") |&gt; readr::write_csv("all-tags.csv") # Import categorised tags tag_categories &lt;- readr::read_csv("all-tags-categorised.csv") Once we have (very roughly) categorised the tags, we can take a look at the summary statistics. Figure&nbsp;2 shows the disciplines represented in the corpus. The corpus already suggests new lines of inquiry. The social science disciplines are not so surprising, but it is intriguing to note the presence of many Visual Arts and Musiology articles. These disciplines do not feature heavily in the mainstream historiography of Digital Humanities, which has tended to focus on early efforts in literature and linguistics. Code disciplines &lt;- corpus |&gt; tidyr::unnest(c(tag)) |&gt; dplyr::left_join(tag_categories, by="tag") |&gt; dplyr::filter(tag_category == "discipline", !is.na(tag)) |&gt; dplyr::group_by(tag) |&gt; dplyr::filter(dplyr::n() &gt; 1) disciplines |&gt; ggplot2::ggplot(ggplot2::aes(y=tag)) + ggplot2::geom_bar() + ggplot2::labs( y="Discipline", x=glue::glue("Number of Articles (n = {nrow(disciplines)}).") ) Figure&nbsp;2: Musicology and Visual Arts have probably been overlooked in the early history of CHS. Disciplines with only one article excluded. What computers were in use? Code computers &lt;- corpus |&gt; tidyr::unnest(c(tag)) |&gt; dplyr::left_join(tag_categories, by="tag") |&gt; dplyr::filter(tag_category == "computer", !is.na(tag)) The computer tags also paint an intriguing picture of the early period of CHS. 74 distinct models of computer are mentioned in the corpus—we may find more as we dig deeper. Although there are many models in the corpus, a few big brands or lines of computer dominate, as shown in Figure&nbsp;3. Code computers |&gt; dplyr::select(tag) |&gt; dplyr::mutate( tag=stringr::str_remove(tag, "Computer: "), brand=stringr::str_extract(tag, "\\w+") ) |&gt; ggplot2::ggplot(ggplot2::aes(y=brand)) + ggplot2::geom_bar() + ggplot2::labs( y="Brand", x=glue::glue("Models Mentioned (n = {nrow(computers)} mentions in {length(unique(computers$Key))} articles)") ) Figure&nbsp;3: Unsurprisingly, IBM dominated the early days of CHS. Figure&nbsp;3 will be unsurprisng to readers familiar with the history of computers. IBM was the dominant manufacturer of large computers in this period. By the mid-sixties, mini-computers were becoming more popular, two of the most famous brands being Control Data Corporation (CDC) and Digital Equipment Corporation (who manufactured the PDP line of computers). The Illiac computers present a fascinating case of early use of computation in the Human Sciences. As well as a statistical machine, it was a machine for musical composition, and was used to create the Illiac Suite (Hiller and Baker 1964). You can listen to part of the suite on Spotify: Where to from here? Next, we need to tidy up the corpus a bit, and get the text of the articles into R. Then we can get to the meat of the homo calculans project—the discourse of Computational Human Sciences in the 1950s and 60s. What did these early pioneers think they were doing? How did they justify there strange experiments in computational method? I am excited to find out… Image credit: Alice (Betsy) E. D. Gillies and Donald B. Gillies with the ILLIAC I at the Digital Computer Lab, Urbana Illinois, circa 1958. By SystemBuilder. CC BY-SA 4.0, permalink References Hiller, Lejaren A., and Robert A. Baker. 1964. “Computer Cantata: A Study in Compositional Method.” Perspectives of New Music 3 (1): 62. https://doi.org/10.2307/832238.]]></summary></entry><entry><title type="html">Descending further</title><link href="https://michaelgfalk.github.io/blog/2025/descending-further/" rel="alternate" type="text/html" title="Descending further"/><published>2025-07-30T00:00:00+00:00</published><updated>2025-07-30T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/descending-further</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/descending-further/"><![CDATA[]]></content><author><name></name></author></entry><entry><title type="html">The uses of error</title><link href="https://michaelgfalk.github.io/blog/2025/the-uses-of-error/" rel="alternate" type="text/html" title="The uses of error"/><published>2025-07-29T00:00:00+00:00</published><updated>2025-07-29T00:00:00+00:00</updated><id>https://michaelgfalk.github.io/blog/2025/the-uses-of-error</id><content type="html" xml:base="https://michaelgfalk.github.io/blog/2025/the-uses-of-error/"><![CDATA[]]></content><author><name></name></author></entry></feed>