Intelligence and Imitation: Mind, Mechanism, Mimesis

Inaugural Workshop on Humanities of AI (WHAI)
Johns Hopkins University, April 24-26, 2026

As a creative aspiration, the Greek notion of mimesis (“imitation”) manifested not only in artistic works imitating reality and philosophical speculations but also in scientific theories and mechanical artifacts. Plato and Aristotle’s nous as a non-bodily principle of intelligibility underwriting cosmic order and thought; Hobbes and LaMettrie’s machinelike mind and world; the Jaquet-Droz family’s musical automata; Wolfgang von Kempelen’s chess-playing Turk; Norbert Wiener’s cybernetic analogy between human, animal, and machine; Japanese roboticist Masahiro Mori’s observation of the revulsion to imperfect verisimilitude (Bukimi no Tani: “uncanny valley”); and Soviet semiotician Yuri Lotman’s culture as collective mind, exemplify the broad relevance of “imitations” to science, literature, and culture.

Developments in artificial intelligence (AI) participate in the legacy of mimesis but also complicate and challenge it. In the course of AI’s research history, AIs have variously been claimed to represent, simulate, assist, improve upon, provide a surrogate for, or replace the functioning of human minds. Concepts such as “optimization,” “satisficing,” and “superintelligence” run orthogonal to the classical concept of mimesis.

At the same time, developments in science and society have deeply challenged both mimesis and mindedness as concepts and ideals. Darwinian and embodied cognitive approaches challenge the primacy of abstract reasoning over embodiment; and reflections on human labor’s relation to material (re-)production, social stratification, and human experience from Marx, Wallerstein, Pasquinelli and others call into question the social “value-added” of material imitations as well as the veracity of accounts of “intelligent” labor’s nature and origins. Deep divisions in the societal uptake of AI – exemplified in anti-AI activism, dueling governance regimes, and popular critical slang like “AI slop” – exemplify and give opportunity to inform these theoretical challenges.

Orientation to these developments requires approaches that scholars in the humanities may be uniquely positioned to provide. We hereby announce a three‑day workshop on “Intelligence and Imitation: Mind, Mechanism, Mimesis” for presentation and discussion of new humanities research engaging with this theme.

Our aim is to foster a collective critical engagement with AIs in their history, socioeconomic context, architecture, and other dimensions of significance with the assistance of resources from literature, philosophy, history, or other humanities fields. We invite contributions from both early‑career (including graduate students) and established academic researchers, whose work-in-progress projects straddle disciplinary boundaries to illuminate aspects of the diverse mind-machine relations exemplified in AI’s history, current reality, and imagined futures.

Some possible avenues of investigation include:

Mimesis and mechanical imitation from antiquity to the transformer
Transformer architecture and the hermeneutic circle of understanding
Political economy and ideology of digital infrastructures sustaining LLMs
New histories and historical perspectives on literary cybernetics and natural language processing (NLP)
Hybridity and joint agency between humans and LLMs
Anthropomorphism and human relations with the (in)animate
Emotional AI as mimesis or optimization

In addition to presented papers, some time at the conference will be devoted to reflection on “humanities of AI” as a research domain, including its current state and possible futures, disciplinary articulation, conditions of success, relations with natural and social sciences, and potential impact on sociotechnical systems involving AI.


Featured Speakers

Yulia Frumer, Bo Jung and Soon Young Kim Professor of East Asian Science, Johns Hopkins University; Author of “Cognition and emotion in Japanese humanoid robots,” History & Technology (2018) and Making Time: Astronomical Time Measurement in Tokugawa Japan (Univ. of Chicago Press, 2018)

Steven Gross, Professor of Philosophy, Johns Hopkins University; Author of Meaning without Representation: Expression, Truth, Normativity, and Naturalism (Oxford Univ. Press, 2015)

N. Katherine Hayles, Distinguished Research Professor at the University of California, Los Angeles, and the James B. Duke Professor Emerita from Duke University; Author of Bacteria to AI: Human Futures with Our Nonhuman Symbionts (Univ. of Chicago Press, 2025), Unthought: The Power of the Cognitive Nonconscious (Univ. of Chicago Press, 2017) and How We Think: Digital Media and Contemporary Technogenesis (Univ. of Chicago Press, 2015)

Matthew L. Jones, Smith Family Professor of History, Princeton University; Author (with Chris Wiggins) of How Data Happened: A History from the Age of Reason to the Age of Algorithms (Norton, 2023)

Matthew Kirschenbaum, Commonwealth Professor of AI and English, University of Virginia; Author of Bitstreams: The Future of Digital Literary Heritage (Univ. of Pennsylvania Press, 2021)

Patrick McCray, Professor of History, University of California, Santa Barbara, Kluge Chair in Technology and Society (2025) at the Library of Congress (2025); Author of README: A Bookish History of Computing from Electronic Brains to Everything Machines (MIT Press, 2025)

Alexander Williams Tolbert, Assistant Professor of Data and Decision Sciences, Emory University; Author of “Why Causal Inference is Necessary for Algorithmic Fairness,” Synthese (2025) and “Causal Agnosticism about Race: Variable Selection Problems in Causal Inference,” Philosophy of Science (2024).



Submission Instructions

Submit a single Word or PDF file to Jiantong Liao (jliao20@jh.edu) by January 31 containing: (i) an abstract roughly 300 words; (ii) a short bio including your name, institutional affiliation, and contact email; and (iii) up to five key words. Decisions will be communicated within one month of the deadline. Authors of accepted abstracts will be asked to send up to 3000 words (a short paper or portion of a paper-in-progress) for distribution before the workshop. Questions may be directedto the address above.


Supporting Institutions

Alexander Grass Humanities Institute, Johns Hopkins University
(https://krieger.jhu.edu/humanities-institute/)

Center for Equitable AI & Machine Learning Systems (CEAMLS), Morgan State University
(https://www.morgan.edu/ceamls)


Organizing Committee

Jiantong Liao (Chair)
PhD Student, German Program, Department of Modern Languages and Literatures
jliao20@jh.edu

Ksenia Tatarchenko (Faculty Sponsor)
Faculty, Medicine, Science & Humanities Program, Johns Hopkins University
ktatarc1@jh.edu

Phillip Honenberger (Faculty Sponsor)
AI Ethicist & Researcher, Center for Equitable AI & ML Systems (CEAMLS), Morgan State University
jaywilliam.honenberger@morgan.edu