[Linganth] CFA: Narrating AI Past, Present, and Future

[Babcock, Joshua]

Dear colleagues,

On behalf of my co-editor, Beth Semel, and me, I’m excited to share the
following CFA for a special issue, “Narrating AI Past, Present, and
Future.” Following a successful pair of AAA panels on this theme in New
Orleans and an initial expression of interest from the International
Journal of the Sociology of Language, we plan to submit our special issue
proposal later this year, with an intended publication date of late 2027 or
early 2028.

Below, please find the abstract, instructions, and timeline for submitting
your proposed contributions. We look forward to receiving your submissions!
Questions? Feel free to get in touch with Josh (joshua_babcock at brown.edu)
and Beth (bsemel at princeton.edu).

Best,

Josh & Beth

--
Narrating AI Past, Present, and Future

AI has changed everything. AI “itself” is also constantly changing, whether
to an unprecedented degree or in unprecedented ways. The change is
impossible to keep up with, or is so fast that every attempt at study is
outdated before it’s begun. Ethnography is seen as poorly suited to deal
with this constant, unprecedented change, and even critical scholars of
language seem to forget that “newness and emergence are not self-evident
features or properties of the phenomena about which they are
predicated…[but] are effects of ideological work” (Babcock forthcoming, 1).

Claims like these resound both in and outside the academy, often cloaked in
seemingly analytical language that obscures their interpretive and
empirical paucity. This special issue adopts a different tack. While
contemporary “data- and compute-intensive technologies that travel under
the sign of AI” (Suchman 2023, 4) may present genuinely new
techno-scientific, machinic affordances, many of the supposed novelties
associated with this diverse category of technology are anything but—nor
are the narratives, values, or interpretations assigned to them by
individuals, groups, and institutions across both expert-technical and
nonexpert domains. Authors in this issue explore how regimes of value,
narratives, and metaphors reflexively framed as belonging to prior
social-space-times continue to haunt systems and statistical techniques
labeled as “AI” in the present, not despite but because of diverse
narratives asserting its radical novelty (Choi and Babcock 2024).

We ask: what linguistic and semiotic resources do individuals, groups, and
institutions draw on to construct or deconstruct the novelty of so-called
AI technologies? How are AI technologies—symbolic, connectionist,
generative, and otherwise—embedded in and co-constitutive of collective
lifeworlds in ways that are neither determining and determined nor
independent of history? What enfleshed, immaterialized, or absented
agencies trail behind or snake through these technologies? How do epistemic
and systemic violences—racism, sexism, anti-Blackness, white supremacy,
ableism, and other intersectionally compounding oppressive structures
(Noble 2018; Benjamin 2019; Semel 2022; 2026; Seaver 2022; Wilf 2023)—haunt
and interpenetrate with the functioning and uses of, as well as narratives
about, them? And how does the functioning of “AI” get rendered inscrutable
in some contexts—made “invisible by its own success” (Latour 1999,
304)—while in others opened wide to explanations with varying degrees of
“truth,” “facticity,” or other forms of legitimization?

This special issue contributes to ethnographic explorations of AI by
bringing together grounded-theoretical approaches that attend to how AI is
in the world, how the world is in AI, and how situated social actors make
sense of the relationships between the two. While language is important, we
heed ongoing calls to extend scholarly attention beyond the speech event
(Wortham and Reyes 2015) and decenter language, “not [to] abandon our
disciplinary commitments [but to] refin[e] them through ‘critical
humility’” (Duchêne 2026, 175–76). Similarly, we take neither newness nor
continuity as given, nor do we treat AI as a monolith. Instead, we track
“the social organization of linguistic behavior” (Fishman 1972, 1) as it is
co-constituted by, and co-constitutive of, technological actants as well as
“attitudes…and overt behaviors toward” (ibid) technologies, language, and
their users.

Timeline and Next Steps

Interested contributors should send titles, abstracts (150 words), and
short bios (100 words) to Josh (joshua_babcock at brown.edu) and Beth (
bsemel at princeton.edu) by Friday, August 28, 2026. Decisions will be
returned on Friday, September 4, together with feedback on the abstracts.
Other key dates are as follows:


   -

   Friday, September 25, 2026: Final, revised abstracts due to Josh and Beth
   -

   Friday, December 11, 2026: Full papers due to Josh and Beth


References

Babcock, Joshua. Forthcoming. “New and Emergent Languages.” In The
Routledge Handbook of Linguistic Anthropology, 2nd Edition, edited by Nancy
Bonvillain and Inmaculada García-Sánchez. London: Routledge.

Benjamin, Ruha. 2019. Race After Technology: Abolitionist Tools for the New
Jim Code. New York: Polity Press.

Choi, Elina, and Joshua Babcock. 2024. “American Paranoia: Media Narratives
of AI as an ‘Amoral Superman.’” CaMP Anthropology, September 30. <
https://campanthropology.org/2024/09/30/american-paranoia-media-narratives-of-ai-as-an-amoral-superman/
>

Duchêne, Alexandre. 2026. “Problems with Problems and Solutions in Applied
Linguistics: Some Considerations and Propositions.” In 60 Years of Applied
Linguistics: Toward More Engaged Research, edited by Grégory Miras, Colón
de Carvajal, Nathalie Blanc, and Shona Whyte, pp 168–80. John Benjamins
Publishing Company.

Fishman, Joshua A. 1972. The Sociology of Language: An Interdisciplinary
Social Science Approach to Language in Society. Rowley, Mass.: Newbury
House.

Latour, Bruno. 1999. Pandora’s Hope: Essays on the Reality of Science
Studies. Cambridge, Massachusetts: Harvard University Press.

Noble, Safiya Umoja. 2018. Algorithms of Oppression: How Search Engines
Reinforce Racism. New York: NYU Press.

Seaver, Nick. 2022. Computing Taste: Algorithms and the Makers of Music
Recommendation. Chicago: University of Chicago Press.

Semel, Beth M. 2022. “Listening Like a Computer: Attentional Tensions and
Mechanized Care in Psychiatric Digital Phenotyping.” Science, Technology, &
Human Values 47 (2): 266-90.

Semel, Beth M. 2026. “The Talking Lure: Raciolinguistic Ideologies of
Reception and the Listening Subjects of American Vocal Biomarker AI.” Current
Anthropology 67 (4): 1–21.

Suchman, Lucy. 2023. “The Uncontroversial ‘Thingness’ of AI.” Big Data &
Society 10 (2): 1–5.

Wilf, Eitan. 2023. The Inspiration Machine: Computational Creativity in
Poetry and Jazz. Chicago: University of Chicago Press.

Wortham, Stanton, and Angela Reyes. 2015. Discourse Analysis Beyond the
Speech Event. London/New York: Routledge.

-- 

Joshua Babcock (he/him/his)

Assistant Professor, Department of Anthropology


Brown University, Box 1921, Providence, RI 02912

joshua_babcock at brown.edu

joshuababcock.com
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