Preview, Accept or Discard? A Predictive Low-Motion Interaction Paradigm

TL;DR

This paper introduces PAD, a predictive AI-assisted interaction paradigm that reduces physical motion in computer input by allowing users to preview and select from ranked suggestions, aiming to mitigate repetitive strain injuries.

Contribution

The work presents a novel zero-click interaction method, PAD, which integrates AI predictions with user control to lower physical effort without sacrificing efficiency.

Findings

PAD significantly reduces hand motion compared to trackpad use.

Task completion times with PAD are comparable to traditional methods at high prediction accuracies.

PAD maintains user agency through preview and discard options.

Abstract

Repetitive strain injury (RSI) affects roughly one in five computer users and remains largely unresolved despite decades of ergonomic mouse redesign. All such devices share a fundamental limitation: they still require fine-motor motion to operate. This work investigates whether predictive, AI-assisted input can reduce that motion by replacing physical pointing with ranked on-screen suggestions. To preserve user agency, we introduce Preview Accept Discard (PAD), a zero-click interaction paradigm that lets users preview predicted GUI targets, cycle through a small set of ranked alternatives, and accept or discard them via key-release timing. We evaluate PAD in two settings: a browser-based email client and a ISO 9241-9 keyboard-prediction task under varying top-3 accuracies. Across both studies, PAD substantially reduces hand motion relative to trackpad use while maintaining comparable task times with the trackpad only when accuracies are similar to those of the best spell-checkers.