Smart products 2.0: redefining user risks with multimodal generative AI

This commentary discusses developments in generative artificial intelligence (GenAI) and multimodal AI models that are increasingly transitioning from the digital space into the physical world of smart products, leading to what we term ‘smart products 2.0.’ The integration of multimodal generative AI models into smart products will introduce new risks for users, necessitating scientific research to inform effective policymaking aimed at safeguarding users. To better contextualize advancements that may influence and reshape user risks, and to guide such research, we propose a conceptual framework that considers GenAI-enabled products and services along the dimensions of type of user interaction, mode of user data processing, and agency transference. Building on this framework, we reflect on potential directions for future research to gain a deeper understanding of individual risk exposure and perception. In conclusion, we discuss some important considerations for policymakers that warrant attention already today.

Publication Details

Journal
BFH: ARBOR
Published
2025-01-01
DOI
https://doi.org/10.24451/dspace/11876
Primary Topic
Forest Ecology and Biodiversity Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart products 2.0: redefining user risks with multimodal generative AI

BFH: ARBOR
Forest Ecology and Biodiversity Studies
article

Smart products 2.0: redefining user risks with multimodal generative AI

article en

Abstract

This commentary discusses developments in generative artificial intelligence (GenAI) and multimodal AI models that are increasingly transitioning from the digital space into the physical world of smart products, leading to what we term ‘smart products 2.0.’ The integration of multimodal generative AI models into smart products will introduce new risks for users, necessitating scientific research to inform effective policymaking aimed at safeguarding users. To better contextualize advancements that may influence and reshape user risks, and to guide such research, we propose a conceptual framework that considers GenAI-enabled products and services along the dimensions of type of user interaction, mode of user data processing, and agency transference. Building on this framework, we reflect on potential directions for future research to gain a deeper understanding of individual risk exposure and perception. In conclusion, we discuss some important considerations for policymakers that warrant attention already today.

BFH: ARBOR
Openalex Percentile: Top 54%
Forest Ecology and Biodiversity Studies
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