Foundation Model Use for Technology Diffusion Monitoring

Mucha TomaszSeppälä Timo

Abstract

Foundation models (FMs) challenge our assumptions about how organizations can develop and use machine learning (ML) technologies in their business activities. Foundation models are trained on broad data sets and can be adapted to a variety of new tasks. While these types of models do not present technological novelty, they exhibit novel properties and capabilities from the sociotechnical perspective that make them particularly interesting for IS scholars and practitioners. Considering the development and leveraging of FMs from the user perspective constitutes a virtually untapped IS research area with high practical relevance. In this TREO talk we present a research project exploring this perspective and which is currently in a design phase.

Association for Information Systems, ICIS 2022, TREO Papers, p. 1047.

Julkaisun tietoja

Tuloksia tutkimuksesta
BRIE-ETLA 2019-2022
Tutkimusryhmä
Yritysten uudistuminen
Päiväys
02.12.2022
Julkaisija / sarja
Association for Information Systems, ICIS 2022, TREO Papers.
Kieli
Englanti
Julkaisu ladattavissa
aisel.aisnet.org