Abstract
Generative AIs have mushroomed, exhibiting astonishing text and image generation abilities. At the same time, these systems also show surprising weaknesses in terms of information accuracy, ability to solve simple maths problems, or the visualisation of simple objects. In this essay we take the so-called “lone banana problem”, the inability of Midjourney to generate a picture of a single banana (instead of a bunch), as our starting point to problematise our common-sense understanding, and related expectations, of generative AI. Through problematisation we highlight that many of the traditional IS assumptions of how systems represent real-world phenomena, and how algorithms work, need to be set aside for understanding generative AI more authentically. We suggest conceiving of generative AI as style engines that encode all aspects of the world - objects, properties, appearances - as styles available for creation. We discuss what this alternative conception affords, and implications for the IS discipline.
Recommended Citation
Riemer, Kai and Peter, Sandra, "What the Lone Banana Problem reveals about the Nature of Generative AI" (2023). ACIS 2023 Proceedings. 86.
https://aisel.aisnet.org/acis2023/86