For all the coverage and writing about AI and LLMs out there, I found myself absolutely shocked to open up our next guest’s paper and think: wait — is this a history of linguists and philosophers in the 1950s????
As a historian will tell you: nothing comes from nowhere! And while AI and LLMs might seem very shiny and new, they are older than you think. That’s why I’m very excited to introduce you to this week’s guest, Amira Moeding a PhD Candidate in History at the University of Cambridge.
Amira’s work looks at the intellectual history of Artificial Intelligence. I began by asking: why is it so shocking to begin with a history and philosophy of linguistics when talking about LLMs? Why did IBM want these early natural language processors to be so energy intensive (hint: to make money)? What is machine empiricism, how does it relate to the invention of Big Data, and why does it limit the way we see and understand the world around us?
Amira held fellowships with Cambridge Digital Humanities and the Cluster of Excellence “Matters of Activity” at Humboldt Universität zu Berlin. They have worked on critical theory, philosophy of science, feminist philosophy, post-colonial theory and the history of law in settler colonial contexts before turning to data and Big Data. Their paper “Machine Empiricism” together with Professor Tobias Matzner is forthcoming. Until June they were employed as an Research Assistant at the Computer Science Department (Computerlab) at the University of Cambridge in this project.
Be sure to take a listen!
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From the Episode
Mentioned in the Episode:
Neda Atonasoki and Kalindi Vora, Surrogate humanity: Race, robots, and the politics of technological futures. (Durham, N.C.: Duke University Press, 2019).
Emily Bender and Alex Hanna, The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want. (London: Penguin Random House, 2025).
Emily Bender and Alexander Koller. "Climbing towards NLU: On meaning, form, and understanding in the age of data." Proceedings of the 58th annual meeting of the association for computational linguistics. 2020.
Catherine D’Ignazio and Lauren Klein, Data Feminism. (Cambridge, MA: MIT Press, 2020).
Max Horkheimer, Traditional and Critical Theory. (New York: Herder and Herder, 1972).
Jaqueline Leon, Automating Linguistics (Cham: Springer Nature, 2021).
Xiaochang Li, Divination Engines: A Media History of Text Prediction. (New York: NYU PhD Dissertation, 2017)
John McCarthy (2007), “Technology and the Role of Women.”: https://web.archive.org/web/20130616014507/http://www-formal.stanford.edu/jmc/future/women.html
John McCarthy (1998 April), “What Futures Shall We Make?” https://web.archive.org/web/20130907215746/http://www-formal.stanford.edu/jmc/future/index.html
John McCarthy, 1995. Moving Mars Closer to the Sun.
For more on Robert Mercer, Cambridge Analytica and its models:
OR https://www.theguardian.com/politics/2017/feb/26/robert-mercer-breitbart-war-on-media-steve-bannon-donald-trump-nigel-farage (note Michal Kosinski is still working at Stanford)
Daniel Rosenberg, “Data Before the Fact.” Raw Data is an Oxymoron. Ed. Lisa Gitelman (Cambridge, MA: MIT Press, 2013).
Daniel Rosenberg, "Data as word." Historical Studies in the Natural Sciences. Vol. 48, No. 5 (2018): 557-567.
More From Amira Modeing:
Their future research group: https://www.biblhertz.it/en/modern-computer-vision
https://www.languagesciences.cam.ac.uk/news/language-sciences-incubator-fund-projects-announced-april-2024 (for more see: https://www-cambridge-org.ezp.lib.cam.ac.uk/engage/coe/article-details/6733a1cd5a82cea2fae8e6e1 and plenty more to come).
They also organized this fun event in Venice with Matteo Pasquinelli:https://www.unive.it/web/en/14779/home#c140545
Amira does rarely use social media (not so much out of conviction they just rarely really enjoy it) but you can reach them at: alam2@cam.ac.uk.
A super cool small language model called ‘Botchen’ for German speakers created by a super cool person, Aurelie Herbelot (without building on ‘Big Tech’ models at all): https://aurelieherbelot.net/outreach/
The Commission for the History and Philosophy of Computing HaPoC:
https://hapoc.org/
What I’m Reading
Thirsty data centres are sucking up Britain’s scarce water supplies
ICE Is Using a New Facial Recognition App to Identify People, Leaked Emails Show
Masked immigration agents challenge local police, sow fear in L.A.
This Website Lets Anyone Use Facial Recognition to Instantly Identify Cops
Trump Administration Limiting Public Access to US National Archives
Trans Refugees: What Trans People Need to Know About Finding Safety Abroad
Finally, Some Good News