In 1956 Richard Pinkerton published a short article in Scientific American with the title “Information Theory and Melody.”1 In this article, written for the general reader, Pinkerton describes a “banal”
monophonic melody generation procedure based on statistical patterns that he derived from a set of 39 “familiar nursery tunes.”2 A network diagram, its accompanying set of instructions, and a fair coin
suffice to recreate the results of Pinkerton’s experiments; readers of Scientific American had all the materials at their disposal to do so.
BANAL TUNE-MAKER produces simple, redundant melodies that sound like nursery tunes. A sequence of notes is obtained by following a path through the network, starting at the top and writing down the note (or rest [represented by a O]) attached to each segment traversed. Where there is a choice of paths, a coin is flipped. If it comes up heads, the black path is taken; if tails the colored path. Broken lines show the path from a junction where there is no choice.3
Shown in Figure 3.1 is the network diagram, while Figure 3.2 shows a transcription of the melody that results from this process. Figure 3.3 overlays the steps taken to generate the first measure of the notated music example, showing the sequence of coin flips that leads to the particular notated example. Pinkerton’s article is often cited as the earliest application of information theory to music
1. Richard Pinkerton, “Information Theory and Melody,” Scientific American 194 (1956): 77–86.
2. The source material for these tunes was The Golden Song Book by Catherine Tyler Wessells (Simon and Schuster), first published in 1945.
Figure 3.1: BANAL TUNEMAKER, corrected to show colored vertices where intended. (Adapted from Richard Pinkerton, “Information Theory and Melody,” Scientific
American 194 (1956), 78.)
Figure 3.2: Pinkerton’s BANAL TUNE. (In Richard Pinkerton, “Information Theory and Melody,” Scientific American 194 (1956), 84.)
Figure 3.3: BANAL TUNEMAKER with overlay showing the results of following the coin flip sequence HHT, which leads to the first measure of the tune that Pinkerton reproduced. (Adapted from Richard Pinkerton, “Information Theory and Melody,” Scientific
in bibliographic litanies that establish a pedigree for contemporary statistical research into music.4
Modest as the generated melodies are, Pinkerton’s experiment evidences a new way of conceiving of the composition of musical utterances in the twentieth century, one that allowed diverse features of a musical composition—in this case, the style of composition that a composition represents—to be described in terms of a statistical process.
Pinkerton introduces his basic, hand-computed algorithmic process with the following
deceptively straightforward claim: “Suppose we regard music simply as a form of communication.”5
At a glance, Pinkerton’s supposition might be mistaken for the kind of familiar platitude about music’s power to communicate that we tend to explain away as the continuing reverberation of centuries’ worth of baggage. However, the title’s invocation of information theory alone makes it clear that Pinkerton’s “communication” does not intend its common-sense or music-sense meaning. He does not posit musical communication as communication from some beyond or other (the divine, the past, the sublime), a position that has traditionally drawn on arguments that assert the language-like character of music.6 Neither is music to be understood as a non-linguistic space of
signification that nevertheless affords the interactive working-out of (homo)social, kinesthetic, or affective–empathic interpersonal relations—all functions that might be considered communicative, which have been ascribed to music by scholars in recent decades.7 In fact, Pinkerton’s claim is
one that is at once more narrow and more radical. Music is “simply a form of communication” precisely as much as it may be described with the help of the recent invention of a “theory-of”: Claude Shannon’s information theory of communication. In the large shadow cast by Shannon’s theory, “communication” came to signify a very particular set of affairs, one which schematized the
4. Joel E. Cohen, “Information Theory and Music,” Behavioral Science 7, no. 2 (1962): 137–63. Hiller cites, briefly, much of the work described below. Hiller and Isaacson, Experimental Music: Composition with an Electronic Computer, chap. 2.
5. Pinkerton, “Information Theory and Melody,” 77. 6. Or, indeed, music’s non-language-like character.
7. For each of these modes respectively see, for example: Edward Klorman, Mozart’s Music of Friends: Social Interplay in the Chamber Works (Cambridge: Cambridge University Press, 2016); Marc Leman, “Music, Gesture, and the Formation of Embodied Meaning,” in Musical Gestures: Sound, Movement, and Meaning, ed. Rolf Inge Godøy and Marc Leman (New York: Routledge, 2010), 126–53; Naomi Cumming, The Sonic Self: Musical Subjectivity and Signification (Bloomington, IA: Indiana University Press, 2000).
transmission of information-bearing messages between two parties under certain assumptions about the character of these messages.
Inaugurated by Claude Shannon in the mid-1940s, information theory is a mathematical field that provides a quantity for measuring the predictability of communications processes. Its principal assumption is that communication systems can be idealized as sequence of draws from a set of discrete symbols that is passed between sender and receiver.8 The relative likelihood of each
symbol in such messages mathematically determines the “information” of the message according to a deceptively simple equation. Messages that are hard to predict are high in information; messages that are easier to predict are low in information. This definition measures information in “bits,” a unit that now alludes to its fundamental role in constructing digital communication channels. Shannon developed the mathematics for this conception of information at Bell Labs in 1945 while working on cryptanalysis and communications security for their various government contracts. Shannon’s work was classified for the duration of the war; the earliest unclassified paper describing these concepts idea dates from 1948.9
Shannon’s definition of information and other quantities derived from it can be used to quantify and regulate properties of arbitrary signal sources. In turn, these mathematical techniques can be used to demonstrate the limits of a communication system’s robustness in the presence of noise or interference, to specify cryptographic systems that are provably secure against eavesdroppers, to develop theorems about the maximum theoretical and effective capacity of transmission media, and to design and prove the optimality of certain digital encoding and data compression schemes.10
These applications quickly showed that Shannon’s idea was highly generative within its originary 8. William Aspray, “The Scientific Conceptualization of Information: A Survey,” IEEE Annals of the History of Computing 7, no. 2 (April 1985): 117–40, https://doi.org/10.1109/MAHC.1985.10018.
9. E. M. Rogers, “Claude Shannon’s Cryptography Research During World War II and the Mathematical Theory of Communication,” in Proceedings of the 28th International Carnahan Conference on Security Technology (Albuquerque, NM, 1994), 3, https://doi.org/10.1109/CCST.1994.363804. For shannon’s first unclassified paper, see @shannon1948a.
10. For an overview of the development of various applications of Shannon’s theory, see James Gleick, The Information: A History, a Theory, a Flood (New York: Pantheon Books, 2011). For a recent and accessible (though stylized) biography of Shannon, see Jimmy Soni and Rob Goodman, A Mind at Play: How Claude Shannon Invented the Information Age (New York: Simon & Schuster, 2017).
field and its success stoked optimism that it would be equally generative if applied outside of telecommunications engineering.
This thinking was partly justified by the fact that Shannon’s scheme modeled communication as a sequential transmission from sender to receiver, so long as the message’s constituents are drawn from some discrete symbol set: alphabetic characters, binary digits, ideographs, staff-notation signs, and so on. Shannon built on earlier work, generalizing earlier results from telegraphy so that they were applicable to “any system, physical or biological, in which information is being transferred or manipulated through time and space.”11 The generality of Shannon’s definition of information
explains why a critical–interpretative tradition centered on his work could be initiated almost immediately: in the landmark re-publication of this paper one year later as A Mathematical Theory
of Communication (1949), Shannon’s essay was preceded a short but profoundly influential essay
by Warren Weaver.12 In this essay, Weaver speculated about the broader applicability of information
theory to a variety of fields of cultural production:
The word communication will be used here in a very broad sense to include all of the procedures by which one mind may affect another. This, of course, involves not only written and oral speech, but also music, the pictorial arts, the theater, the ballet, and in fact all human behavior. […] The language of this memorandum will often appear to refer to the special, but still very broad and important, field of the communication of speech; but practically everything said applies equally well to music of any sort, and to still or moving pictures, as in television.13
Together, these two essays described the mathematical tools that are often interchangeably referred to as information theory or communications theory. The mathematical generality of the model that Shannon proposed, taken along with Weaver’s optimism about it, ensured that the theory was fungible in hundreds of disciplines. In turn, its rapid adoption in diverse research context fueled beliefs—warranted or otherwise—that the explanatory domain of information theory was boundless.
11. Aspray, “The Scientific Conceptualization of Information: A Survey,” 122.
12. Weaver’s essay first appeared in print as an article in Scientific American. It was prepared at the request of Chester Barnard, then the president of the Rockefeller foundation. Rogers, “Claude Shannon’s Cryptography Research During World War II and the Mathematical Theory of Communication.”, 3.
13. Weaver, (1964 [1949]), 3–4. By contrast, in the earlier target piece to which Weaver’s was the companion, Shannon preferred the more neutral term “output” to describe the results of such communicative “procedures.”
Extensions of the principles of information theory to describe natural or human communicative processes have been justifiably viewed with some skepticism. Creative uses of information theory beyond the immediate electro-technical dispostif imagined in Shannon’s analyses have been characterized as a “misapplication” of the theory by scientists.14 By music historians and critics,
music-as-information has been viewed as symptomatic of the conceptual reductionism demanded by scientistic investigation in order that it may measure and quantify; such denatured talk about music has been dismissed as the consequence of indulging the physics envy of theorists.
These two families of objections share a kind of absolutism concerning the proper explanations and explananda of their respective disciplines. In this chapter, I plot a course between these two positions, with a view to showing that it is possible to adopt a critical posture on the matter without committing either to a strict interpretation of information theory as properly pertaining only to artificial communications systems or to the equally (yet differently) “strong” claims of music’s resistance to codification or quantification. In fact, alternately giving credence to each of these positions highlights those claims made by the authors that I discuss below that cannot be addressed fully with reference to either scientific or musical justification alone. This separability problem attests to the radical interdisciplinarity of their research program, and perhaps to that of scientific or laboratory research with human subjects more generally.
Pinkerton’s experiments with the stochastic generation of melodies under the sign of information theory raise the following questions, which are thematic to the discussion of the research which follows. What features of music made it seem like a domain of human behavior worth applying information theory to in the first instance? What arguments were marshaled to justify the musical adaptations of experiments and demonstrations that were originally designed for the analysis of artificial communications systems? Where were the sites—to include actual research laboratories, music departments but also publication venues, and forums for music—in which this “informatization” of musical behavior took place, and which advocates, critics, and institutions were
recruited in this process? 14. Rogers, 3.