Privacy First: Designing Responsible and Inclusive Social Robot Applications for in the Wild Studies
This research paper investigates privacy-sensitive social robotics by deploying a user registration and login system for a Pepper social robot in a government-managed innovation center. The study examines user preferences between facial recognition and QR code access methods, analyzing how transparency and contextual integrity impact trust and technology adoption. Findings show that while the majority of participants chose facial recognition for convenience, offering an alternative like a QR code is critical for users concerned about data privacy.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Roboticists, researchers, and developers designing social robot applications should read this to understand how to incorporate privacy-by-design and inclusive access methods.
What the document contains
The paper addresses the design, deployment, and evaluation of a cross-platform user registration and login system for social robots deployed in public spaces. It examines user choices between facial recognition and QR code access, evaluating privacy regulations, transparency, trust, and user sentiment.
The document does not provide commercial service implementations, long-term deployment metrics beyond initial registration preferences, or legislative enforcement mechanisms.
- Deploying social robots in shared public spaces introduces critical privacy challenges regarding the collection of biometric data.
- The majority of study participants selected facial recognition over a QR code alternative due to its convenience, ease of use, and speed.
- Providing a non-biometric alternative like a QR code is essential for maintaining inclusiveness and accommodating users with privacy concerns or low trust.
- High transparency regarding data collection practices helps align with contextual integrity and fosters user trust in the system.
· I. INTRODUCTION · II. ROBOTS AS SHARED RESOURCES: PRIVACY, TRANSPARENCY AND TRUST · III. REGISTRATION SYSTEM DESIGN · IV. STUDY DESIGN · V. REGISTRATION PROCESS · VI. RESULTS · VII. DISCUSSION · VIII. LIMITATIONS AND CONCLUSIONS
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
0/5Clear responsibility for AI outcomes
screening score · 2026-10-23
Fairness
4/5Non-discrimination and equitable treatment
Our main differentiation from the aforementioned works is to offer our users different methods to access the system to guarantee maximum inclusiveness
III. REGISTRATION SYSTEM DESIGN
screening score · 2026-10-23
Human Oversight
0/5Humans remain in control of consequential decisions
screening score · 2026-10-23
Privacy
4/5Protection of personal data and private life
Importantly, all registered faces were stored locally on the robot and never transmitted on the internet. Also, the system removed all other information collected from users at the end of the registration process.
V. REGISTRATION PROCESS - A. On-site Robot Registration
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
screening score · 2026-10-23