Building Intelligent User Interfaces for Human-AI Alignment

2026-02-12

AI Summary

This study addresses a critical gap in AI alignment research by foregrounding the user interface—not as a mere implementation detail, but as a central component of the alignment process. The work proposes a structured reference model to systematically analyze how interfaces mediate human-AI value alignment. Through human-computer interaction analysis, an initial survey of six interface types, and two in-depth case studies, the framework’s validity is empirically substantiated. The findings reveal key mechanisms by which interface design actively shapes alignment outcomes, thereby establishing both a theoretical foundation and practical guidance for developing intelligent interactive systems that effectively support value alignment.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Philosophy and Ethics of AI: Morality & Value-based AI
• Intelligent Robots: Human-Robot Interaction

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Aligning AI systems with human values fundamentally relies on effective human feedback. While significant research has addressed training algorithms, the role of user interface is often overlooked and only treated as an implementation detail rather than a critical factor of alignment. This paper addresses this gap by introducing a reference model that offers a systematic framework for analyzing where and how user interface contributions can improve human-AI alignment. The structured taxonomy of the reference model is demonstrated through two case studies and a preliminary investigation featuring six user interfaces. This work highlights opportunities to advance alignment through human-computer interaction.

Problem

• human-AI alignment
• user interface
• human feedback
• human-computer interaction
• alignment

Innovation

• human-AI alignment
• user interface
• human-computer interaction
• reference model
• structured taxonomy