Andy Heredia | Searcharxiv

arXiv2026

The Pen: Episodic Cognitive Assistance via an Ear-Worn Interface

Wearable AI is often designed as always-available, yet continuous availability can conflict with how people work and socialize, creating discomfort around privacy, disruption, and unclear system boundaries. This paper explores episodic use of wearable AI, where assistance is intentionally invoked for short periods of focused activity and set aside when no longer needed, with a form factor that reflects this paradigm of wearing and taking off a device between sessions. We present The Pen, an ear-worn device resembling a pen, for episodic, situated cognitive assistance. The device supports short, on-demand assistance sessions using voice and visual context, with clear start/end boundaries and local processing. We report findings from an exploratory study showing how layered activation boundaries shape users' sense of agency, cognitive flow, and social comfort.

cs.HC↗

arXiv2025

Lessons Learned from Developing a Privacy-Preserving Multimodal Wearable for Local Voice-and-Vision Inference

Many promising applications of multimodal wearables require continuous sensing and heavy computation, yet users reject such devices due to privacy concerns. This paper shares our experiences building an ear-mounted voice-and-vision wearable that performs local AI inference using a paired smartphone as a trusted personal edge. We describe the hardware-software co-design of this privacy-preserving system, including challenges in integrating a camera, microphone, and speaker within a 30-gram form factor, enabling wake word-triggered capture, and running quantized vision-language and large-language models entirely offline. Through iterative prototyping, we identify key design hurdles in power budgeting, connectivity, latency, and social acceptability. Our initial evaluation shows that fully local multimodal inference is feasible on commodity mobile hardware with interactive latency. We conclude with design lessons for researchers developing embedded AI systems that balance privacy, responsiveness, and usability in everyday settings.

cs.HC↗