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

arXiv: https://arxiv.org/abs/2601.15100 · HTML: https://mlsanity.com/paper/2601.15100/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jan 2026.

## Built on by (most cited first, 1 of 1)

- [Designing Proactive Thought Partners for Writing](https://mlsanity.com/paper/2609.01588/) (2026)

## Abstract (arXiv)

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.