Generative AI models should include detection mechanisms as a condition for public release

The new wave of ‘foundation models’—general-purpose generative AI models, for production of text (e.g., ChatGPT) or images (e.g., MidJourney)—represent a dramatic advance in the state of the art for AI. But their use also introduces a range of new risks, which has prompted an ongoing conversation ab...

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Detalles Bibliográficos
Autores: Knott, Alistair, Pedreschi, Dino, Chatila, Raja, Chakraborti, Tapabrata, Leavy, Susan, Baeza Yates, Ricardo, Eyers, David, Trotman, Andrew, Teal, Paul D., Biecek, Przemyslaw, Russell, Stuart, Bengio, Yoshua
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/70210
Acceso en línea:http://hdl.handle.net/10230/70210
http://dx.doi.org/10.1007/s10676-023-09728-4
Access Level:acceso abierto
Palabra clave:Generative AI
AI regulation
AI ethics
AI social impacts
Foundation models
Descripción
Sumario:The new wave of ‘foundation models’—general-purpose generative AI models, for production of text (e.g., ChatGPT) or images (e.g., MidJourney)—represent a dramatic advance in the state of the art for AI. But their use also introduces a range of new risks, which has prompted an ongoing conversation about possible regulatory mechanisms. Here we propose a specific principle that should be incorporated into legislation: that any organization developing a foundation model intended for public use must demonstrate a reliable detection mechanism for the content it generates, as a condition of its public release. The detection mechanism should be made publicly available in a tool that allows users to query, for an arbitrary item of content, whether the item was generated (wholly or partly) by the model. In this paper, we argue that this requirement is technically feasible and would play an important role in reducing certain risks from new AI models in many domains. We also outline a number of options for the tool’s design, and summarize a number of points where further input from policymakers and researchers would be required.