Legal Obligation and Ethical Best Practice: Towards Meaningful Verbal Consent for Voice Assistants

TY - CHAP

T1 - Legal Obligation and Ethical Best Practice: Towards Meaningful Verbal Consent for Voice Assistants

AU - Seymour, William

AU - Coté, Mark

AU - Such, Jose

N1 - Funding Information: This work was undertaken as part of the Secure AI Assistants project through Engineering and Physical Sciences Research Council grant EP/T026723/1. We would also like to thank Perry Keller and Hana Kopecka for reviewing drafts of the manuscript. Publisher Copyright: © 2023 ACM.

PY - 2023/4/10

Y1 - 2023/4/10

N2 - To improve user experience, Alexa now allows users to consent to data sharing via voice rather than directing them to the companion smartphone app. While verbal consent mechanisms for voice assistants (VAs) can increase usability, they can also undermine principles core to informed consent. We conducted a Delphi study with experts from academia, industry, and the public sector on requirements for verbal consent in VAs. Candidate requirements were drawn from the literature, regulations, and research ethics guidelines that participants rated based on their relevance to the consent process, actionability by platforms, and usability by end-users, discussing their reasoning as the study progressed. We highlight key areas of (dis)agreement between experts, deriving recommendations for regulators, skill developers, and VA platforms towards crafting meaningful verbal consent mechanisms. Key themes include approaching permissions according to the user's ability to opt-out, minimising consent decisions, and ensuring platforms follow established consent principles.

AB - To improve user experience, Alexa now allows users to consent to data sharing via voice rather than directing them to the companion smartphone app. While verbal consent mechanisms for voice assistants (VAs) can increase usability, they can also undermine principles core to informed consent. We conducted a Delphi study with experts from academia, industry, and the public sector on requirements for verbal consent in VAs. Candidate requirements were drawn from the literature, regulations, and research ethics guidelines that participants rated based on their relevance to the consent process, actionability by platforms, and usability by end-users, discussing their reasoning as the study progressed. We highlight key areas of (dis)agreement between experts, deriving recommendations for regulators, skill developers, and VA platforms towards crafting meaningful verbal consent mechanisms. Key themes include approaching permissions according to the user's ability to opt-out, minimising consent decisions, and ensuring platforms follow established consent principles.

UR - http://www.scopus.com/inward/record.url?scp=85160015580&partnerID=8YFLogxK

U2 - 10.1145/3544548.3580967

DO - 10.1145/3544548.3580967

M3 - Conference paper

T3 - Conference on Human Factors in Computing Systems - Proceedings

BT - 2023 CHI Conference on Human Factors in Computing Systems

PB - ACM

ER -