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arXiv · 2601.15100

Facilitating Proactive and Reactive Guidance for Decision Making on the Web: A Design Probe with WebSeek

Yanwei Huang·Arpit Narechania
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Abstract

Web AI agents such as ChatGPT Agent and GenSpark are increasingly used for routine web-based tasks, yet they still rely on text-based input prompts, lack proactive detection of user intent, and offer no support for interactive data analysis and decision making. We present WebSeek, a mixed-initiative browser extension that enables users to discover and extract information from webpages to then flexibly build, transform, and refine tangible data artifacts-such as tables, lists, and visualizations-all within an interactive canvas. Within this environment, users can perform analysis-including data transformations such as joining tables or creating visualizations-while an in-built AI both proactively offers context-aware guidance and automation, and reactively responds to explicit user requests. An exploratory user study (N=15) with WebSeek as a probe reveals participants' diverse analysis strategies, underscoring their desire for transparency and control during human-AI collaboration.

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Yanwei Huang, Arpit Narechania. 2026-01-21. Facilitating Proactive and Reactive Guidance for Decision Making on the Web: A Design Probe with WebSeek. https://arxiv.org/abs/2601.15100

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