Bridging Data Analysis and Communication with Human-AI Collaboration

PhD Thesis Proposal Defence


Title: "Bridging Data Analysis and Communication with Human-AI Collaboration"

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 will explore 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:                   Friday, 3 May 2024

Time:                   3:00pm - 5:00pm

Venue:                  Room 5501
                        Lifts 25/26

Committee Members:      Prof. Huamin Qu (Supervisor)
                        Prof. Chiew-Lan Tai (Chairperson)
                        Prof. Cunsheng Ding
                        Dr. Yangqiu Song