Building Intelligent User Interfaces for Human-AI Alignment

Fuente: arXiv
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1. Verfasser: Shi, Danqing
Format: Preprint
Veröffentlicht: 2026
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author Shi, Danqing
author_facet Shi, Danqing
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2602_11753
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Building Intelligent User Interfaces for Human-AI Alignment
Shi, Danqing
Human-Computer Interaction
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.
title Building Intelligent User Interfaces for Human-AI Alignment
topic Human-Computer Interaction
url https://arxiv.org/abs/2602.11753