arXiv Open Access 2025

Reflection on Data Storytelling Tools in the Generative AI Era from the Human-AI Collaboration Perspective

Haotian Li Yun Wang Huamin Qu
Lihat Sumber

Abstrak

Human-AI collaborative tools attract attentions from the data storytelling community to lower the expertise barrier and streamline the workflow. The recent advance in large-scale generative AI techniques, e.g., large language models (LLMs) and text-to-image models, has the potential to enhance data storytelling with their power in visual and narration generation. After two years since these techniques were publicly available, it is important to reflect our progress of applying them and have an outlook for future opportunities. To achieve the goal, we compare the collaboration patterns of the latest tools with those of earlier ones using a dedicated framework for understanding human-AI collaboration in data storytelling. Through comparison, we identify consistently widely studied patterns, e.g., human-creator + AI-assistant, and newly explored or emerging ones, e.g., AI-creator + human-reviewer. The benefits of these AI techniques and implications to human-AI collaboration are also revealed. We further propose future directions to hopefully ignite innovations.

Topik & Kata Kunci

Penulis (3)

H

Haotian Li

Y

Yun Wang

H

Huamin Qu

Format Sitasi

Li, H., Wang, Y., Qu, H. (2025). Reflection on Data Storytelling Tools in the Generative AI Era from the Human-AI Collaboration Perspective. https://arxiv.org/abs/2503.02631

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓