History of Technology

Aaron Mendon-Plasek, Yale Law School, "Creativity in an irrational world of inexhaustible meaning: early 1950s origins of machine learning as subjective decision-making, disunified science, and a remedy for what cannot be predicted."
 
Abstract
This paper explores why and how early 1950s machine learning researchers concerned with questions of pattern recognition came to see a range of ‘machine learning’ practices as a superior strategy for employing digital computers to perform creative non-numerical tasks and for identifying what was important in any decision-making process, including political decision-making, scientific inquiry, and self-knowledge. While ‘machine learning’ as a term-of-art and a set of practices constituted a trading zone well into the 1990s, for those working on pattern recognition the term ‘machine learning’ begun to take on a far narrower set of meanings by 1953 in which a learning program’s capacity to perform ‘creative’ work was its ability to redefine the scope of the tasks it was assigned. This paper investigates the local research problems, epistemological commitments, institutional contexts, and transnational exchange of what early 1950s researchers called ‘machine learning’ through three cases studies of early-career researchers imagining, building, and programming digital computers to ‘learn’ from 1950 to 1953. These physicists- and engineers-turned-pattern recognition researchers saw learning programs as potential interlocutors alongside humans to help identify significant differences, resolve contextual ambiguity, and explore epistemic possibility. In doing so, these and other researchers saw machine learning as rooted in a constructivist epistemology in which the possibility of machine ‘originality’ necessarily precluded machine (and even human) objectivity. While these appeals to nominalist strategies for handling poorly-understood, extraordinary complex, or even contradictory systems were often local contingent responses for expanding the uses of digital computers in the early 1950s, these responses quickly came to define what constituted both legitimate problems of knowledge in machine learning and a conception of efficacy rooted in the capacity to make meaning from contradictory information.
This article is a much revised and expanded version of the first chapter from my 2022 history dissertation entitled Genealogies of Machine Learning, 1950-1995 . I am looking for fresh perspectives on this work, including alternative empirical and computational approaches I might use to explore the networks of scientists, engineers, and institutions that I discuss. While I wrote this piece for a history of computing audience, I am actively examining other methods and mediums to share these ideas with a larger audience of historians of technology interested in the relationships between quantification, innovation and maintenance, and infrastructure, and how such technical practices play a role in the imagining of categories like race, gender, social problems, and political possibility. I am also interested in exploring how I might communicate the historical insights my article develops about early machine learning to a general audience interested in what contemporary AI can and can’t do, and how such debates say as much about us as they do about how AI might be regulated. Finally, I am interested in learning novel strategies media scholars have used in showing how the materiality of objects has served as a contingent but crucial component to the creation of abstractions used to imagine what Ian Hacking has called “human kinds.” I also hope that sharing my work with a working group will be an opportunity for me to begin to develop relationships with members affiliated with the Consortium who might be able to alert me to others working on complementary scholarly projects examining the links between quantification, computation, and creation, stabilization, and remaking of social categories.

IS THERE A CANON IN THE HISTORY OF TECHNOLOGY?
Please note new meeting time: third Tuesdays, 1-2:30 eastern time U.S. 
Please join us for our first meeting of the 2023-24 academic year. Two things are on the agenda: a brief discussion of the upcoming year's schedule, and then a more substantial reflection on the idea of a canon in the history of technology. 
We are posing two broad questions 1) whether there is a canon in history of technology, i.e., works with which we assume everyone is familiar -- perhaps Staudenmaier, Hughes's Networks of Power, etc. -- and how this has influenced work in the field; and 2) what works do people think that everyone should be familiar with now. A canon can help a field develop a unique and deep identity; a canon can also constrain work and artificially limit a field's boundaries. There may well be something to be said for a certain amount of incoherence in a discipline. 
Here are some more specific questions we hope to take up: Are there certain books or articles that should be regarded as essential reading in the field? What characteristics, if any, do these works have in common? Do they make important theoretical or methodological contributions to the field? Do they feature people, places, or technologies that have previously been overlooked by other historians? Are they particularly well-written or widely cited? Are they prominently featured in undergraduate or graduate syllabi? We invite participants to share their answers to these questions and provide examples of “canonical” case studies from their respective subfields.
 

Patrick McCray, University of California, Santa Barbara, "Designing Cultures" [Ch. 7 from READ ME: A Bookish History of Computing from Giant Brains to Everywhere Machines]
[Note: This chapter is from an unfinished book manuscript. Please do not circulate it outside of this working group.]

Julia Sanchez-Dorado, Technische Universität Berlin and Susan Sterrett, Wichita State University, "The meandering epistemic status of river models in American hydraulics (1922-1949)"
 
[Note: This article is still under review. Please do not circulate it outside of this working group.]

Jesse Smith, Science History Institute, "Behind the Scenes at the exhibit 'Downstream': Online and in person"
https://www.sciencehistory.org/downstream

Andrew Meade McGee, National Air and Space Museum, “The Electronic Origins of the Neoliberal Order: Computers, Digital Technologies, and the Re-Shaping of State-Market Relations, 1968-1988."

The Technology Working Group will not meet the week of January 16; the meeting has been cancelled.
Notice will follow shortly of the remaining program for the spring.

Hannah Conway, Harvard University, “Petroleum Sovereignty: Native Land & Life at the End of Louisiana’s Atchafalaya Basin since 1927”

SHOT: directions and themes in an ever-growing field: discussion led by Ben Gross, Linda Hall Library.

James Esposito, Ohio State University
"Canaries, Camouflets, and Carbon Monoxide: 'Proto Man' and Oxygen Breathing Apparatus in Britain’s Tunneling War 1915-1918"
An age-old technique of siege warfare, undermining saw wide use on the Western Front during World War I. Playing out as an intense “cat and mouse” game of detection, British and German tunnelers attempted to surreptitiously bomb each other in perfectly timed underground blasts known as camouflets. The omnipresent threat of being buried alive and poisoned by carbon monoxide redefined survival beneath the trenches, calling upon the services of the “Proto Man.” Donning oxygen artificial breathing apparatus and carrying a canary, the “Proto Man” was essential to survival in this extreme environment, a savior to many trapped underground. Britain’s success in the tunneling war came in large part due to the highly militarized mine rescuer “Proto Man” represented. British physiologist JS Haldane and mining expert Henry Briggs sought to improve the performance of these indispensable personnel, seeking to enhance both the technical qualities of the Proto breathing apparatus and the respiratory performance of individuals doing the heavy work of war. Although rescuers owed their lives to the canary, the birds died in droves. These fragile animals formed an invaluable facet of the “Proto Man” assemblage and were deemed incapable of replacement by any inanimate methods of gas detection. This article argues attempts at augmenting “Proto Man” were specifically focused on the fields of equipment engineering and laboratory study of respiratory performance, the only aspects of this posthuman assemblage deemed capable of improvement. What resulted was a strange hybrid of human, machine, and avian life exhibiting the limits of Edwardian science and the deep reliance of humans on animal sensing.