arXiv subjects

Niti Parikh

Publications and source records attributed to Niti Parikh.

4 recordsLinked to original sources

arXiv2026

Towards Considerate Human-Robot Coexistence: A Dual-Space Framework of Robot Design and Human Perception in Healthcare

The rapid advancement of robotics is reshaping what it means for humans and robots to coexist -- through expanded capabilities, more intuitive interactions, and deeper integration into real-world workflows. Beyond sharing physical space, this coexistence is increasingly characterized by organizational embeddedness, temporal evolution, social situatedness, and open-ended uncertainty. Because such coexistence extends beyond a single encounter, understanding healthcare robots requires looking beyond initial acceptance to how stakeholders' perceptions evolve through continued engagement. Yet, prior work has largely relied on single-point snapshots of attitudes and acceptance, offering limited insight into coexistence as a long-term, dynamic process. We address these gaps through in-depth follow-up interviews with nine participants from a 14-week co-design study on healthcare robots. We identify the human perception space, which includes four interpretive dimensions (i.e., degree of decomposition, source of evidence, scope of reasoning, and temporal orientation). We enrich the conceptual framework of human-robot coexistence by conceptualizing the mutual relationship between the human perception space and the robot design space as a co-evolving loop, in which human needs, design decisions, situated interpretations, and social mediation continuously reshape one another over time. Building on this, we propose considerate human-robot coexistence, arguing that humans act not only as design contributors but also as interpreters and mediators who actively shape how robots are understood and integrated across deployment stages. Our related prior work and supplementary materials, including the interview protocol, are available at https://byc-sophie.github.io/considerate-human-robot-coexistence/

cs.RO↗

arXiv2026

Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity Prototypes

Co-design is essential for grounding embodied artificial intelligence (AI) systems in real-world contexts, especially high-stakes domains such as healthcare. While prior work has explored multidisciplinary collaboration, iterative prototyping, and support for non-technical participants, few have interwoven these into a sustained co-design process. Such efforts often target one context and low-fidelity stages, limiting the generalizability of findings and obscuring how participants' ideas evolve. To address these limitations, we conducted a 14-week workshop with a multidisciplinary team of 22 participants, centered around how embodied AI can reduce non-value-added task burdens in three healthcare settings: emergency departments, long-term rehabilitation facilities, and sleep disorder clinics. We found that the iterative progression from abstract brainstorming to high-fidelity prototypes, supported by educational scaffolds, enabled participants to understand real-world trade-offs and generate more deployable solutions. We propose eight guidelines for co-designing more considerate embodied AI: attuned to context, responsive to social dynamics, mindful of expectations, and grounded in deployment. Project Page: https://byc-sophie.github.io/Towards-Considerate-Embodied-AI/

cs.HC↗

arXiv2024

The Communal Loom: Integrating Tangible Interaction and Participatory Data Collection for Assessing Well-Being

For most health or well-being interventions, the process of evaluation is distinct from the activity itself, both in terms of who is involved, and how the actual data is collected and analyzed. Tangible interaction affords the opportunity to combine direct and embodied collaboration with a holistic approach to data collection and evaluation. We demonstrate this potential by describing our experiences designing and using the Communal Loom, an artifact for art therapy that translates quantitative data to collectively woven artifacts.

cs.CY↗

arXiv2024

CRAFT@Large: Building Community Through Co-Making

CRAFT@Large (C@L) is an initiative launched by the MakerLAB at Cornell Tech to create an inclusive environment for the intercultural and intergenerational exchange of ideas through making. With our approach, we challenge the traditional definition of community outreach performed by academic makerspaces. Existing academic makerspaces often perform community engagement by only offering hourly, one-time workshops or by having community members provide a problem that is then used by students as a project assignment. These approaches position community members as occasional visitors and non-equal contributors, which not only conflict with the core values of co-creation but also limit the makerspaces' impact on connecting the universities and the communities. C@L explored an alternative approach in which we invited community members as long-term and equal co-makers into the academic makerspaces. In this article, we showcase two sets of collaborations that illustrate the continuity of people through co-making. We present how academic makerspaces can function as a hub that connects community members and partner organizations with the campus community in a long-term relationship.

cs.HC↗