← CHI 2026 map

CHI '26 · Honorable mention · full-paper review · confidence medium-high

Privacy is Not One-Click: Designing Robots That Adapt to Older Adults’ Changing Boundaries

Nishchal Jagadeesha , Chorong Park , Avery Kruppe , Yanfu Liu , Rua Mae Williams , Sooyeon Jeong , Anastasia Kouvaras Ostrowski

DOI PDF Program page Page JSON

This is a strong CHI honorable-mention style contribution: it reframes privacy as a changing practice rather than a fixed setting, and it turns that framing into three actionable design features. The main strength is the qualitative grounding; the main weakness is that the contribution remains conceptual and context-bounded.

Axes Lens

Rare contribution shape, typical evidence profile. The point here is not a score. It is to show what kind of claim the paper makes, and whether the evidence pattern is unusual or baseline in this 268 -review set.

Review Summary

This paper’s strongest contribution is not a new robot capability but a reframing of privacy for older adults in home social-robot settings. The abstract explicitly contrasts current one-time, universal consent mechanisms with a view of privacy as “temporal and situational” and requiring “continuous negotiations and revisions.” That is a meaningful departure from common-sense product thinking, because it treats privacy as something that evolves with context, relationships, and changing comfort rather than as a single configuration event. The paper then moves beyond diagnosis into design synthesis through a post-participatory-design speculative design process, yielding three concrete features: privacy profiles, real-time privacy feedback, and data ownership tools. That makes the contribution more than a conceptual critique; it offers a design-oriented vocabulary for future systems. At the same time, the evidence base is clearly qualitative and bounded. The paper’s own abstract says the authors conducted two participatory design workshops at assisted living facilities, and the limitation text identifies a homogeneous sample of fourteen older adults from a single Midwest U.S. region. So the work is best read as a grounded, normative design argument rather than a generalizable empirical law. I would classify the novelty as a design-space contribution with normative knowledge: it expands how CHI researchers might think about privacy mechanisms for older adults, but it does not validate a deployed system or demonstrate long-term behavioral outcomes. The overclaim risk is therefore moderate, mainly if readers interpret the three features as validated solutions rather than speculative design directions. Within those bounds, the paper is a credible and timely CHI contribution with clear relevance to privacy-sensitive home robotics. The methodological move is also notable: the authors explicitly use speculative design after participatory design, rather than as a substitute for it, to translate participant concerns into more concrete interaction concepts. That makes the paper useful to CHI readers interested in method as much as topic, because it shows how qualitative findings can be carried forward into a design vocabulary without pretending that the resulting concepts have already been field-tested. The limitation is important and well stated: the sample is homogeneous, the setting is assisted living, and the work does not yet establish feasibility or adoption in real homes. Those constraints do not weaken the paper’s core claim; they simply define it as a strong, situated design argument rather than an evaluated system contribution.

What Changed

Canon before

Prior CHI work on privacy in home technologies often treats consent and settings as one-time, universal controls; older-adult privacy in social-robot settings is less often framed as a changing, negotiated practice.

Departure from common sense

The paper argues that privacy for older adults in home social-robot settings should not be treated as a one-time checkbox or fixed setting. Instead, it is temporal, situational, and repeatedly renegotiated as circumstances and comfort levels change.

Actual novelty

The paper’s post-PD speculative design process produces three concrete privacy design features—privacy profiles, real-time privacy feedback, and data ownership tools—positioned as support for older adults’ multidimensional privacy experiences. The novelty is not a new robot platform, but a design-space expansion that turns qualitative privacy concerns into implementable interaction and data-governance directions for future home robots.

Evidence

The contribution is grounded in two participatory design workshops with fourteen older adults in assisted living facilities, followed by a research-team speculative design synthesis. The paper supports both the reframing of privacy as dynamic and the extraction of three design features, but it does not evaluate deployed prototypes or long-term outcomes. The evidence therefore supports a strong qualitative design argument rather than a validated intervention claim.

Limits

Method limits

The study relies on two participatory design workshops and a post-PD speculative design process rather than prototype deployment or controlled evaluation. The resulting design features are therefore conceptual recommendations, not experimentally validated interventions.

Deployment limits

The paper does not establish long-term effectiveness, usability, or adoption of the proposed privacy features in real homes or deployed robots. Translation into practice would require implementation and longitudinal testing.

Boundary conditions

Findings are grounded in older adults in assisted living facilities from a single Midwest U.S. region. The privacy framing may differ for other age groups, living arrangements, cultures, or robot use contexts.

Manual check: false

Position in field

This work positions privacy as an ongoing social practice in older-adult robot use, extending beyond static consent mechanisms toward adaptive, multidimensional design guidance for home social robots. It also argues for speculative design as a post-participatory-design method for turning lived privacy concerns into concrete design features.

Abstract

Social robots in the home bring new privacy risks and concerns for older adults. Yet, current technology privacy mechanisms typically use a one-time and universal consent mechanism (e.g., user agreement checkbox, browser cookie setting, etc.), lacking consideration of how privacy is holistically experienced. Designing for privacy requires a multidimensional approach to support how older adults experience privacy. To investigate older adult-centered privacy mechanisms for social robots, we conducted two participatory design (PD) workshops at local assisted living facilities. Our findings from these workshops suggest that older adults do not treat privacy as static, but as a temporal and situational practice that requires continuous negotiations and revisions. We subsequently conducted a post-PD speculative design (SD) process that extracted three design features for privacy—aware social robots-privacy profiles, real-time privacy feedback, and data ownership tools—that can support older adults’ multidimensional privacy experiences.