Economic Anthropology in the Era of Generative Artificial Intelligence
Sheldon, Zachary, Kumar, Peeyush
–arXiv.org Artificial Intelligence
To model Callon's position in the form of an LLM, one need only train the model on the already available textual corpus of post-industrial Western capitalism, given that any performed instance of the discourse token "economics" or "the economy" will form the statistically average center of attention for an associative network of other, token-level terms. However, although token-level linguistic performatives of the kind described by Callon have played a historically outsized role in the economies of capitalist states, the power of the performative token does not exhaust the concept of economics as a field of human "social creativity", understood as the linguistically/symbolically mediated, historically/mythologically self-consciousness agency of intelligent beings conceptualizing and transforming their own conditions of existence (Graeber 2012). Marcel Mauss, on the other hand, acknowledged the formal autonomy of generative exchange as an existentially human practice that took up various "forms and reasons" across different cases, opening the possibility for theorizing type-level conceptual distinctions based on their functional parallelism across diverse societies, and, in Mauss's own radical argument, even identifying deficiencies in the dominant form of exchange from the perspective of non-dominant forms. Insofar as reflective attention to ethnographic type-tokens like kula, potlach, or mana enhances human economic anthropologists' capacity to recognize patterns of value-creation and transformation within any new set of ethnographic data, a Maussian methodology can meaningfully inform the mechanics of machine learning and provide a touchstone for the integration of anthropological knowledge with AI research. In a future publication, Sheldon will elaborate on this contrast between the "flat ontology" of Actor Network Theory and the "depth ontology" that continues to be generatively employed by logicians, mathematicians, and computer scientists (as well as mystics, magicians, and illusionists), both ancient and modern.
arXiv.org Artificial Intelligence
Oct-19-2024