Facilitating Proactive and Reactive Guidance for Decision Making on the Web: A Design Probe with WebSeek
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.
697197c8c1c7409747bf95b7
Yanwei Huang
697197c8c1c7409747bf95b8
Arpit Narechania
claimed_verified
2026-02-09T08:37:07.221Z
69874103ffe2121b274f104d
https://cdn-avatars.huggingface.co/v1/production/uploads/69874103ffe2121b274f104d/i8z0bqi13kPmt6OU0yb1U.png
Arpit Narechania
arpitnarechania
user
arpitnarechania
Facilitating Proactive and Reactive Guidance for Decision Making on the Web: A Design Probe with WebSeek
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.
WebSeek is a mixed-initiative browser extension that enables interactive web data extraction and analysis with AI-assisted guidance and automation.