{"id":43344,"date":"2021-05-26T10:00:16","date_gmt":"2021-05-26T15:00:16","guid":{"rendered":"https:\/\/www.publicbooks.org\/?p=43344"},"modified":"2026-01-16T20:17:24","modified_gmt":"2026-01-17T02:17:24","slug":"the-indifference-engine","status":"publish","type":"post","link":"https:\/\/www.publicbooks.org\/the-indifference-engine\/","title":{"rendered":"The Indifference Engine"},"content":{"rendered":"

What\u2019s next for the digital humanities? And how might they be part of changing our collective futures? As universities across the country reach the end of this unprecedented year, Public Books<\/em> and Digital Humanities at MIT present a four-part series<\/a> examining the role of the digital in the life of scholars and societies. In this moment of global reckoning around issues of virological, ecological, historical, and moral concern, some of the field\u2019s top thinkers here ask how digital media and methods continue to challenge, harm, sustain, and liberate\u2014and they show how investigations into the relationship between the digital and the human have only just begun.<\/p>\n

\u2014Stephanie Ann Frampton<\/a><\/p>\n

\n

The word indifference<\/em> used to mean \u201ca thing or matter of no essential importance.\u201d1<\/a><\/sup> In my field\u2014the digital humanities\u2014we tend to sell our work to administrators and students by stressing the value of STEM skills and data-driven research, in contrast to the tendency in the humanities at large to stress what is without price. This affects our research priorities and the choices our students make; we apply for grants, we advise students, by presenting a case for which white-hot fields\u2014artificial intelligence? cultural analytics? quantum computing?\u2014provide the clearest road map to the future.2<\/a><\/sup> This always entails prognostication and projection. How can we use the present to predict the future? Based on our understanding of the present, how can we seize on the tools and research that will be most useful in the future? Based on our understanding of the future, how can we pick out the tools and research that will be most useful for us in the present?<\/p>\n

A wiser essay might push back against the utilitarian idea that everything should be judged by what it adds to the marketplace. But what the heck\u2014let\u2019s embrace that idea.<\/p>\n

Here are three stories about endeavors that were \u201cuseless,\u201d and yet whose applications helped to shape the digital world. As this history suggests, nobody knows what will be useful in the future. That\u2019s why an<\/em> indifference<\/em>, to use the old phrase, can be an engine of innovation. And this, in turn, is why we so often find humanistic activities in the seeds and roots of STEM.<\/p>\n

We don\u2019t know what will turn out to be useful. But we do know that the future will have its roots in the humanities, which is a self-interested reason to give the humanities a future.<\/p>\n\n

\n\n
Related readings<\/div>\n\n
\n\n
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\n \"\"<\/a> <\/figure>\n <\/div>\n\n
\n\n
\n Essays<\/a>\n <\/div>\n\n
\n Opening the Anthropocene Archives<\/a>\n <\/h5>\n\n
\n \n \"James <\/a>\n \n James Lee <\/a>\n <\/div>\n \n <\/div>\n <\/div>\n <\/div>\n\n \n

In the 1940s, the linguist George Kingsley Zipf set his graduate students to what was surely a tedious and unwelcome task. He asked them to count the number of times every discrete word appears in James Joyce\u2019s novel Ulysses<\/em>. They found an unusual concordance to help them with this work: the Word Index to James Joyce\u2019s Ulysses<\/em> (1937), created by a team of linguists under the direction of Miles Hanley.3<\/a><\/sup><\/p>\n

You would be hard-pressed, I think, to imagine a book that is, on its face, more useless than the Word Index to James Joyce\u2019s “Ulysses”<\/em>, or a project more useless than the word-counting task of Zipf\u2019s graduate students. This he foisted on his underlings because he wanted to study natural language quantitatively and imagined that Ulysses<\/em>, famous for its streams of consciousness, might document the flow of natural language with special fidelity.4<\/a><\/sup><\/p>\n

Using the numbers his students compiled, Zipf graphed each word\u2019s frequency (the number of times it appears in the novel) against its ranking (whether it is, for instance, the first, tenth, or hundredth most frequently used word in the novel). He discovered that the frequency and ranking of the words in Ulysses<\/em> have an inverse relationship:\u00a0a small number of words appear extremely often, and a very large number of words appear very rarely.<\/p>\n

Zipf had unintentionally discovered a law. Today it\u2019s called Zipf\u2019s law, and researchers have found it to have applications in all kinds of information ecosystems, from library science to financial trading. In the information age, it has helped us to understand databases, internet traffic, video streaming, chat rooms, and social networks. In fact, the most famous rules concerning social networks\u2014that the value of a social network is equal to the square of the number of its nodes; that nodes in a social network have dramatically uneven importance\u2014derive their reasoning from Zipf\u2019s law.5<\/a><\/sup><\/p>\n

We owe our knowledge of this law to a linguist\u2019s idle inquiry into Ulysses<\/em>; to his willingness to read a novel dramatically <\/em>against the usual rules, for no reason except for his interest in the way people talk.
\n<\/p>\n

\n
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We don\u2019t know what will turn out to be useful. But We do know that the future will have its roots in the humanities.<\/p>\n<\/blockquote>\n<\/figure>\n


\nThe second story: In 1916, a wealthy eccentric hired Elizebeth Smith, a recently graduated English major who lived in Chicago, to study William Shakespeare\u2019s First Folios. Smith\u2019s patron wanted her to find hidden clues in the plays that would prove that the plays were written not by Shakespeare, but by Sir Francis Bacon.<\/p>\n

Shakespeare wrote Shakespeare\u2019s plays. No serious scholar doubts this. One might think, then, that Smith was on a fool\u2019s errand. The verdict of history, however, has been that her work was far from a waste of time. Her efforts as a historian trying to answer a question about Shakespeare and Sir Francis Bacon obliged her to become an expert in cryptography, because Bacon himself was an expert in cryptography. Smith worked, with others her patron hired for the same task, at a facility called Riverbank, which became a school for researching the history of codes and ciphers.<\/p>\n

During the First World War, Riverbank scholars trained American military personnel to create ciphers. For part of the war, as Jason Fagone notes in a marvelous book on Smith, the Riverbank team \u201cdid all of the codebreaking for every part of the U.S. government: for the State Department, the War Department (army), the navy, and the Department of Justice.\u201d6<\/a><\/sup> In 1921, Smith and William Friedman, a Riverbank scholar she had recently married, started a new career in Washington, DC, working for the government.7<\/a><\/sup> They helped to shape the methods of emerging spy and law-enforcement agencies like the Federal Bureau of Investigation, the Office of Strategic Services (later the Central Intelligence Agency), and the National Security Agency.<\/p>\n

The Friedmans\u2019 heirs today are the cryptanalysts and cypherpunks who build and crack cryptographic codes. Was studying Shakespeare a waste of their time?<\/p>\n\n

\n\n
Related readings<\/div>\n\n
\n\n
\n
\n \"\"<\/a> <\/figure>\n <\/div>\n\n
\n\n
\n Essays<\/a>\n <\/div>\n\n
\n Who Gets to Be a Writer?<\/a>\n <\/h5>\n\n
\n \n Claire Grossman <\/a>, et al.\n <\/div>\n \n <\/div>\n <\/div>\n <\/div>\n\n \n

Our third story concerns Edmond Locard, a French investigator in the early 20th century.8<\/a><\/sup> Locard admired the Sherlock Holmes stories of Sir Arthur Conan Doyle; today, Locard is often called the father of modern forensics. As such, detective stories helped to inspire the modern science of detection.<\/p>\n

The originator of the detective genre was the 19th-century writer Edgar Allan Poe.9<\/a><\/sup> The literature scholar Paul Grimstad argues persuasively that Poe started workshopping the genre in an article he wrote in 1836 about a chess-playing machine that he suspected was a hoax\u2014as in fact it was. That piece got him started on a way of thinking about thinking that led to his writing the first \u201canalytic detective story.\u201d10<\/a><\/sup><\/p>\n

In this chain of influence, who was wasting their time? Was Poe wasting his time when he wrote what readers might have seen as a rather niche and self-indulgent article about a Victorian artificial-intelligence system? Or was he wasting his time when, intrigued by the literary possibilities of his article\u2019s gimmick\u2014putting deductive and inductive reasoning on display\u2014he wrote a locked-door mystery starring the detective Monsieur Dupin? Was Conan Doyle wasting his time when, drawing on Poe\u2019s example, he wrote the Holmes stories? Was Locard when he read the Holmes stories and thought about how a science of detection might work in real life?<\/p>\n

The forensic professionals who examine security logs, network traffic, and hard drives work in a technological field that has its origins in literary writing. To adapt a phrase from Robert Darnton, literature does not merely reflect on history; literature causes history.11<\/a><\/sup>
\n<\/p>\n

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the activities that commentaries on S.T.E.M. and the humanities tend to discount as useless have been powerful drivers of the economy and shapers of the modern world.<\/p>\n<\/blockquote>\n<\/figure>\n


\nResearchers in the digital humanities often explain the field to outsiders in terms of either the humanities discovering tech (algorithms perform a \u201cdistant reading\u201d of Hamlet<\/em>) or tech discovering the humanities (sociological analysis reveals algorithms to be saturated with human bias). However, I have often seen the field facilitate a different phenomenon: technological tools and norms and methods rediscovering<\/em> the humanistic world from which they first sprang.<\/p>\n

The arts drive tech so often that it should be a clich\u00e9. The art of weaving provided technical inspiration to Charles Babbage, creator of the Difference Engine and the Analytical Engine, and Ada Lovelace, whose algorithm for the Analytical Engine has earned her recognition as the first computer programmer.12<\/a><\/sup> The philosopher Ted Nelson\u2019s experimental, cutup writings about literary hypertext, which links information in sprawling networks rather than in \u201crigid hierarchies and matrices,\u201d gave Tim Berners-Lee a toolkit for the design of the World Wide Web.13<\/a><\/sup> Punk saved the internet by instilling the young people who became internet insiders in the 1980s and 1990s with a do-it-yourself ethos, a distrust of authority, and a general rebelliousness toward the utility-maximizing engines of the establishment, which together define hacker culture even today; it helped the hacker ethic to catch on outside the privileged spheres of Stanford and MIT. Low-art ephemera, like records and zines, shaped the high-tech world for decades\u2014even if, as so often happens, the establishment eventually co-opted the counterculture that opposed it.14<\/a><\/sup><\/p>\n

I would love to challenge the idea that a field is valuable in proportion to the number of dollars it adds to the economy. But sometimes it\u2019s worth entertaining this flawed premise, because it provides a chance to show that the activities that commentaries on STEM and the humanities tend to discount as useless have been powerful drivers of the economy and shapers of the modern world.<\/p>\n

Tech is not separate from poetry and politics and other (as a programmer might claim they are) indifferences; merely forgetful of them. The digital humanities helps us to see how they work together.<\/p>\n

Correction: July 27, 2021<\/strong><\/p>\n

This article has been edited to clarify Zipf’s law.<\/em><\/p>\n

This article was commissioned by Carolyn Dever<\/a> and Stephanie Ann Frampton<\/a><\/em>.<\/p>\n

  1. Oxford English Dictionary<\/em>, 2nd ed. (1989), s.v.<\/em> \u201cindifference,\u201d entry xi. \u21a9<\/a><\/li>
  2. On their first visit to office hours, my students often tell me they want to study \u201cartificial intelligence and\u201d x<\/em>, with x<\/em> being medicine or whatever field they want to have a career in. \u21a9<\/a><\/li>
  3. Miles L. Hanley et al., Word Index to James Joyce\u2019s “Ulysses” <\/em>(University of Wisconsin Press, 1937). Even at the time of publication, researchers saw this book as an odd duck. One reviewer wrote in 1937, \u201cOut-of-the-way adventures in research have an unholy fascination for me. The latest is the\u00a0Word Index to James Joyce\u2019s “Ulysses” <\/em>by Professor Miles L. Hanley of the University of Wisconsin.\u201d Untitled book review, Colophon<\/em>, vol. 2, no. 4 (1937), p. 622. As an aside, the book\u2019s acknowledgments section shows the heroic labors of women credited as amanuenses. Hanley writes, \u201cBy far the largest amount of individual work was done by Miss Theresa Fein, who supervised most of the alphabetizing, the proofreading, and the verification of references. She was principally responsible for the typewritten copy from which the final stencils were made; and, with the help of others, she also prepared Appendix I\u201d (xi). \u21a9<\/a><\/li>
  4. The edition of Ulysses<\/em> that Hanley used (Random House) contained 260,430 words in total. Hanley\u2019s book indexed 29,899 discrete words, meaning that if you gather all the instances of \u201cthe\u201d into one \u201cthe,\u201d all the instances of \u201cdog\u201d into one \u201cdog,\u201d and so forth, you end up with 29,899 words. Zipf\u2019s students counted the number of times each of those 29,899 discrete words appears. \u21a9<\/a><\/li>
  5. See, for example, Lada Adamic and Bernardo Huberman, \u201cZipf\u2019s Law and the Internet,\u201d Glottometrics<\/em>, vol. 3 (2002); and Alexander Saichev, Yannick Malevergne, and Didier Sornette, Theory of Zipf\u2019s Law and Beyond<\/em> (Springer, 2010). \u21a9<\/a><\/li>
  6. This group also wrote foundational cryptological texts. \u201cBetween 1917 and 1920,\u201d writes Fagone, Riverbank\u2019s press published \u201ceight pamphlets,\u201d largely authored by Elizebeth Smith Friedman and William Friedman, \u201cthat described new kinds of codebreaking strategies. These were little books with unassuming titles on plain white covers. Today they are considered to be the foundation stones of the modern science of cryptology.\u201d The Woman Who Smashed Codes: A True Story of Love, Spies, and the Unlikely Heroine Who Outwitted America\u2019s Enemies<\/em> (HarperCollins, 2017), p. 77. \u21a9<\/a><\/li>
  7. Smith took Friedman\u2019s name upon their marriage. \u21a9<\/a><\/li>
  8. Locard\u2019s Exchange Principle\u2014\u201cEvery contact leaves a trace\u201d\u2014remains the basis of forensic science today. As Matthew Kirschenbaum notes, this principle \u201cis more, not less<\/em>, true in the delicate reaches of computer systems.\u201d Mechanisms: New Media and the Forensic Imagination<\/em> (MIT Press, 2012), p. 49. \u21a9<\/a><\/li>
  9. The first detective story on record is Poe\u2019s \u201cThe Murders in the Rue Morgue\u201d (1841). \u21a9<\/a><\/li>
  10. Poe argued that a human was hiding inside the machine and directing its moves, which was in fact the case. As Grimstad notes, Poe\u2019s presentation of this argument is an example of inferential reasoning, worked up, in part, for literary purposes: he believed that readers would enjoy following him along this inferential chain of reasoning about what would be required for an automaton to engage in deductive thought. To summarize in modern terms: with deductive reasoning, as with classical programming, one takes data and rules and uses them to find results, whereas with inductive reasoning, as with machine learning, one takes data and results\u2014how a chess machine plays\u2014and uses them to find rules. A machine in Poe\u2019s time could engage in deductive reasoning, in the sense that it could solve mathematical problems, but it could not engage in the kind of inductive reasoning that Poe displays in his essay. \u201cWhat a machine must be able to do in order to play chess,\u201d says Grimstad, \u201cis the very thing Poe is doing in making inferences based on observation alone.\u201d Experience and Experiential Writing: Literary Pragmatism from Emerson to the Jameses<\/em> (Oxford University Press, 2013), p. 45. \u21a9<\/a><\/li>
  11. Robert Darnton, \u201cWhat Is the History of Books?,\u201d Daedalus<\/em>, vol. 111, no. 3 (1982), p. 81. \u21a9<\/a><\/li>
  12. Famously, Lovelace compared the Analytical Engine\u2019s operations to \u201cthe principle which Jacquard devised for regulating, by means of punched cards, the most complicated patterns in the fabrication of brocaded stuffs.\u201d She added, \u201cWe may say most aptly that the Analytical Engine weaves algebraical patterns<\/em> just as the Jacquard-loom weaves flowers and leaves.\u201d Ada Lovelace, \u201cTranslator\u2019s Notes to M. Menabrea\u2019s Memoir,\u201d in Scientific Memoirs<\/em>, by Luigi Federico Menabrea, vol. 3 (1843), p. 712. \u21a9<\/a><\/li>
  13. See, for example, Ted Nelson, Literary Machines<\/em> (Mindful, 1981); and Tim Berners-Lee and Mark Fischetti, Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by Its Inventor<\/em> (HarperCollins, 1999), pp. 3\u20136. \u21a9<\/a><\/li>
  14. See Elyse Graham, A Unified Theory of Cats on the Internet<\/em> (Stanford University Press, 2020). \u21a9<\/a><\/li><\/ol><\/div>","protected":false},"excerpt":{"rendered":"

    Nobody knows what will be useful in the future. And this is why we so often find humanistic activities in the seeds and roots of STEM.<\/p>\n","protected":false},"author":13,"featured_media":43394,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[2018,422,14,20,150,69],"pbpartner":[2015],"section":[1145,1366],"pbseries":[],"class_list":["post-43344","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-essays","tag-digital-humanities-at-mit","tag-higher-education","tag-history","tag-literature","tag-novel","tag-technology","pbpartner-digital-humanities-mit","section-digital-humanities","section-higher-education"],"acf":[],"yoast_head":"\nThe Indifference Engine - Public Books<\/title>\n<meta name=\"description\" content=\"Nobody knows what will be useful in the future. 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