OBJECTIFYING THE PLATFORM SOCIETY: INVESTIGATING USERS’ PERCEPTION OF SMART SPEAKERS' ALGORITHMIC SUGGESTIONS AND DATA PROCESSING

  • Elisabetta Locatelli Università Cattolica del Sacro Cuore, Italy
Keywords: platform society, smart speakers, domestication, algorithms, data

Abstract

Smart speakers are one the latest products of platforms and have the capability to quickly connect platforms, algorithms, people, and households together. The frame of $2 was developed to understand the agency of platforms (corporations based on technological infrastructures guided by algorithms) that have influence on the whole society itself. We can argue, thus, that smart speakers can be conceptualized as devices that objectify the logics of platform society into households because they are produced and programmed by a platform that provides also the operating system and the personal assistant installed, becoming an extension of the platform itself. Due to the fast diffusion of smart speakers, there is the need to investigate their adoption process and user’s perception of algorithmic selection and data processing. The research here presented was one of the first about the subject in Italy and studied the diffusion of smart speakers in Italy with a multi-sided methodology. It let to investigate also the role of smart speakers in reproducing the power of algorithms into households. Research results showed that users were taking for granted some algorithmic logic and appreciated it (like for basic information search or for music selection). They indicated also that the mechanisms of voice interaction made clear some limits of the algorithmic customization and led users to start to be more conscious of it (for example about news selection or vocal search for purchases) and to elaborate strategies to reduce its influence.

Published
2020-10-05
How to Cite
Locatelli, E. (2020). OBJECTIFYING THE PLATFORM SOCIETY: INVESTIGATING USERS’ PERCEPTION OF SMART SPEAKERS’ ALGORITHMIC SUGGESTIONS AND DATA PROCESSING. AoIR Selected Papers of Internet Research, 2020. https://doi.org/10.5210/spir.v2020i0.11262
Section
Papers L