Understanding Dark Patterns in Home IoT Devices.

Monica Kowalczyk, Johanna T. Gunawan, David R. Choffnes, Daniel J. Dubois, Woodrow Hartzog, Christo Wilson

Research output: Contribution to conferencePaperAcademic

Abstract

Internet-of-Things (IoT) devices are ubiquitous, but little attention has been paid to how they may incorporate dark patterns despite consumer protections and privacy concerns arising from their unique access to intimate spaces and always-on capabilities. This paper conducts a systematic investigation of dark patterns in 57 popular, diverse smart home devices. We update manual interaction and annotation methods for the IoT context, then analyze dark pattern frequency across device types, manufacturers, and interaction modalities. We find that dark patterns are pervasive in IoT experiences, but manifest in diverse ways across device traits. Speakers, doorbells, and camera devices contain the most dark patterns, with manufacturers of such devices (Amazon and Google) having the most dark patterns compared to other vendors. We investigate how this distribution impacts the potential for consumer exposure to dark patterns, discuss broader implications for key stakeholders like designers and regulators, and identify opportunities for future dark patterns study.

Original languageEnglish
Pages179:1-179:27
DOIs
Publication statusPublished - 2023
Externally publishedYes

Fingerprint

Dive into the research topics of 'Understanding Dark Patterns in Home IoT Devices.'. Together they form a unique fingerprint.

Cite this