Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations

• DOI: 10.31234/osf.io/pzk8a
• Publication Date: 2022-04-26T17:11:55Z
• Authors: Jim Samuel; Rajiv Kashyap; Yana Samuel; A. Pelaez
• Keywords: Representation; Information processing theory

Explosive growth in big data technologies and artificial intelligence (AI) applications have led to increasing pervasiveness of information facets a rapidly growing array representations. Information facets, such as equivocality veracity, can dominate significantly influence human perceptions consequently affect performance. Extant research cognitive fit, which preceded the AI era, focused on effects aligning representation task performance, without sufficient consideration attendant challenges. Therefore, there is compelling need understand interplay these dominant with representations tasks, their We suggest that artificially intelligent adapt overcome limitations are necessary for complex environments. To this end, we propose test novel “Adaptive Cognitive Fit” (ACF) framework explains AI-augmented draw processing theory dissonance advance ACF set propositions. empirically validate propositions an economic experiment demonstrates machine learning simulation establishes viability using improve