Abstract

Abstract Can we have personal robots without giving away personal data? Besides, what is the role of a robots Privacy Policy in that question? This work explores for the first time privacy in the context of consumer robotics through the lens of information communicated to users through Privacy Policies and Terms and Conditions. Privacy, personal and non-personal data are discussed under the light of the human–robot relationship, while we attempt to draw connections to dimensions related to personalization, trust, and transparency. We introduce a novel methodology to assess how the “Organization for Economic Cooperation and Development Guidelines Governing the Protection of Privacy and Trans-Border Flows of Personal Data” are reflected upon the publicly available Privacy Policies and Terms and Conditions in the consumer robotics field. We draw comparisons between the ways eight consumer robotic companies approach privacy principles. Current findings demonstrate significant deviations in the structure and context of privacy terms. Some practical dimensions in terms of improving the context and the format of privacy terms are discussed. The ultimate goal of this work is to raise awareness regarding the various privacy strategies used by robot companies while ultimately creating a usable way to make this information more relevant and accessible to users.

Highlights

  • We live in an era where collaborative robots have become an essential element of the industrial shop floor [1], and health-care robots are deployed to fight a global virus outbreak [2]

  • We investigate how the privacy guidelines developed by the Organization for Economic Cooperation and Development (OECD) are reflected upon the publicly available Privacy Statements and Terms and Conditions in the consumer robotics field

  • We look into the context of trust and transparency in human–robot interaction

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Summary

Introduction

We live in an era where collaborative robots have become an essential element of the industrial shop floor [1], and health-care robots are deployed to fight a global virus outbreak [2]. We notice a booming increase in human–robot interactions where humans share workspaces, collaborative tasks, and, eventually, significant parts of their daily living environments with robots [5]. These human–robot interactions are as good as the data we feed them. A trustworthy relationship in a human–robot interaction scenario is greatly dependent on the way such expectations are managed. How could those records be used in a way that respects user privacy?

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