Bridging Data Analysis and Storytelling with Human-AI Collaborative Tools

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Bridging Data Analysis and Storytelling with Human-AI Collaborative 
Tools"

By

Mr. Haotian LI


Abstract:

Working with data has become common across various disciplines, from natural 
science to business. For these data workers, communicating data insights and 
knowledge from data analysis through data stories plays a crucial role in 
enhancing collaboration in teams and raising public awareness. However, 
creating clear, coherent, and engaging data stories requires diverse skills 
and considerable time for human authors. To address this challenge, this 
thesis investigates how to introduce artificial intelligence (AI) to 
effectively reduce human effort and streamline data analysis and 
communication.

In the first part of this thesis, we built theoretical foundations for 
human-AI collaboration in bridging data analysis and storytelling. We 
conducted an interview study to gain insights into the expected AI roles and 
challenges when telling data stories. Based on the findings from the 
interview, the human-AI collaboration in data storytelling tools is 
formalized as a framework with two dimensions: the roles of collaborators and 
the stages of collaboration. With the framework, various insights and 
opportunities in designing human-AI collaborative tools are unveiled through 
a comprehensive literature review.

The second part of this thesis presents research on instantiating the 
theories into interactive tools for real-world applications. First, we 
designed Notable to bridge data analysis and data storytelling in 
computational notebooks with on-the-fly assistance, including automatic data 
fact documentation, story organization, and slide creation. Our second work 
explored enhancing the alignment between humans and AI in story organization 
with meta relations, which delineate connections between data story pieces 
using meta information beyond datasets, such as domain knowledge and 
narrative intent.

With the two parts of this thesis, we hope to contribute knowledge and 
experience as cornerstones to boost effective and seamless collaboration 
between humans and AI for data analysis and communication in the coming era 
of large-scale AI systems.


Date:                   Monday, 22 July 2024

Time:                   2:00pm - 4:00pm

Venue:                  Room 5501
                        Lifts 25/26

Chairman:               Dr. Weiyin HONG (ISOM)

Committee Members:      Prof. Huamin QU (Supervisor)
                        Prof. Cunsheng DING
                        Prof. Xiaofang ZHOU
                        Prof. Fugee TSUNG (IEDA)
                        Dr. Duen Horng CHAU (Georgia Tech)