02085nas a2200265   4500008004100000022001400041245010300055210006900158260001600227490000700243520114900250100002001399700002001419700001801439700002701457700001701484700002501501700001701526700002001543700001901563700002301582700002001605700001901625856017501644       2023                        eng d  a1388-195700aGenerative AI models should include detection mechanisms as a condition for public releaseAbstract0 aGenerative AI models should include detection mechanisms as a co  cJan-12-20230 v253 aThe 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.1 aKnott, Alistair1 aPedreschi, Dino1 aChatila, Raja1 aChakraborti, Tapabrata1 aLeavy, Susan1 aBaeza-Yates, Ricardo1 aEyers, David1 aTrotman, Andrew1 aTeal, Paul, D.1 aBiecek, Przemyslaw1 aRussell, Stuart1 aBengio, Yoshua  uhttps://link.springer.com/article/10.1007/s10676-023-09728-4?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20231028&utm_content=10.1007/s10676-023-09728-4