Human-in-the-Loop Optimization for Inclusive Design: Balancing Automation and Designer Expertise

TL;DR

This paper advocates for an automated Human-in-the-Loop approach to inclusive design, shifting designer roles towards curating constraints for algorithmic optimization to efficiently create accessible, personalized interfaces.

Contribution

It introduces a novel HITL framework that combines constraint curation with adaptive feedback to improve scalable, personalized accessible design solutions.

Findings

Proposes a shift from direct prototyping to constraint-based optimization.

Highlights the potential for scalable, personalized accessibility improvements.

Raises ethical and transparency considerations in automated design processes.

Abstract

Accessible and inclusive design has gained increased attention in HCI, yet practical implementation remains challenging due to resource-intensive prototyping methods. Traditional approaches such as workshops, A-B tests, and co-design sessions struggle to capture the diverse and complex needs of users with disabilities at scale. This position paper argues for an automated, accessible Human-in-the-Loop (HITL) design optimization process that shifts the designer's role from directly crafting prototypes to curating constraints for algorithmic exploration. By pre-constraining the design space based on specific user interaction needs, integrating adaptive multi-modal feedback channels, and personalizing feedback prompts, the HITL approach could efficiently refine design parameters, such as text size, color contrast, layout, and interaction modalities, to achieve optimal accessibility. This approach promises scalable, individualized design solutions while raising critical questions about constraint curation, transparency, user agency, and ethical considerations, making it essential to discuss and refine these ideas collaboratively at the workshop.