Paper Number

ICIS2025-1118

Paper Type

Short

Abstract

As Artificial Intelligence (AI) in organizations triggered an unprecedented need for data to develop, train, and test models, research into data production intensified. Traditionally, scholars have investigated data for AI through the logic of referentiality which analyzes whether and how data that are used in AI represent real-world phenomena. However, the growth of synthetic data—data that exist without direct real-world referents—enabled by Generative AI (GenAI) problematizes this analytical emphasis and reveals the limits of referentiality in explaining the role of data in AI. This article develops an alternative approach based on the logic of functionalism which conceptualizes data in terms of what they do rather than what they represent. We elaborate on the functional logic and demonstrate its capacity to generate new insights into the role of data in AI settings.

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12-GenAI

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Dec 14th, 12:00 AM

From Referentiality to Functionalism: A New Logic for Theorizing Data in the Age of Generative AI

As Artificial Intelligence (AI) in organizations triggered an unprecedented need for data to develop, train, and test models, research into data production intensified. Traditionally, scholars have investigated data for AI through the logic of referentiality which analyzes whether and how data that are used in AI represent real-world phenomena. However, the growth of synthetic data—data that exist without direct real-world referents—enabled by Generative AI (GenAI) problematizes this analytical emphasis and reveals the limits of referentiality in explaining the role of data in AI. This article develops an alternative approach based on the logic of functionalism which conceptualizes data in terms of what they do rather than what they represent. We elaborate on the functional logic and demonstrate its capacity to generate new insights into the role of data in AI settings.

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