This work uses the embodied, Jewish identities of its three authors, and the experimental methodology of kibbitzing as a form of collective inquiry and self-reflexive praxis in order to demonstrate the limitations of chatbots to produce humorous narratives from an explicitly Jewish epistemology. ‘Kibbitzing’ is a Yiddish term, meaning a lively, informal way of thinking and talking together. It’s somewhere between joking, arguing and exchanging ideas. It is grounded in our relationships, histories and biases; kibbitzing is how we make shared meaning together through many voices.
Kibbitzing values contradiction, humour and the messiness of human conversation. Unlike AI chatbots, which follow scripted, dialogic, question-and-answer routines based on quantifiable patterns in data, kibitzing is unpredictable, non-linear and intentionally disorganized” (Laywine, Simon & Sinnreich, 2025).
We contrast the affordances of large language models (LLMs) and their associated chatbots with the context-based logics of Jewish joke craft and storytelling. This article goes on to demonstrate the risk of cultural erasure that is posed by the positivist, denotative meanings associated with ChatGPT’s attempts at producing jokes for, or about, Jews.
Article: Laughing to keep from [user input undefined]: ChatGPT, Jewish humor, and cultural erasure
In a subsequent article (forthcoming in Critical AI), we argue that generative AI’s positivistic and denotative logics treat identity as an additive construct, which is functionally incommensurate with intersectional frameworks when users aim to generate content that pertains to multiple formulations of identity. We analyze the outputs of text-to-image generator MidJourney and the large language model (LLM) ChatGPT for “shadow ontologies” of ethnicity, race, gender, and sexuality. We situate our argument within discourses on intersectionality driven by Black feminist scholars and queer theory critiques of social classification systems.
Article: What’s with all the Tapestries?: Intersectionality and the Discursive Vacuum of Generative AI
Our ongoing work aims to systemize and refine our kibitzing methodology through the use of recording technology, video, transcription, and creative annotation.
- Nathaniel Laywine, Assistant Professor, York University
- Victoria Simon, Associate Professor, Felician University
- Aram Sinnreich, Professor, American University
