Sneak Preview: Editors’ Introduction: Lauren M.E. Goodlad and Matthew Stone “Beyond Chatbot-K: On Large Language Models, “Generative AI,” and Rise of Chatbots: An Introduction”

ABSTRACT:

This essay introduces the history of the “generative AI” paradigm, including its underlying political economy, key technical developments, and sociocultural and environmental effects. In concert with this framing it discusses the articles, thinkpieces, and reviews that make up part 1 of this two-part special issue (along with some of the content for part 2). Although large language models (LLMs) are marketed as scientific wonders, they were not designed to function as either reliable interactive systems or robust tools for supporting human communication or information access. Their development and deployment as commercial tools in a climate of reductive data positivism and underregulated corporate power overturned a long history in which researchers regarded chatbots as “misaligned” affordances for safe or reliable public use. While the technical underpinnings of these much-hyped systems are guarded as proprietary secrets that cannot be shared with researchers, regulators, or the public at large, there is ample evidence to show that their development depends on the expropriation and privatization of human-generated content (much of it under copyright); the expenditure of enormous computing resources (including energy, water, and scarce materials); and the hidden exploitation of armies of human workers whose low-paid and high-stress labor makes “AI” seem more like human “intelligence” or communication. At the same time, the marketing of chatbots propagates a deceptive ideology of “frictionless knowing” that conflates a person’s ability to leverage a tool for producing an output with that person’s active understanding and awareness of the relevant information or truth claims therein. By contrast, the best digital infrastructures for human writing enable human users by amplifying and concretizing their interactive role in crafting trains of contemplation and rendering this situated experience in shareable form. The essay concludes with reflections on alternative pathways for developing AI—including communicative tools—in the public interest.