How Much Automation Does a Data Scientist Want?

How Much Automation Does a Data Scientist Want?

7 January 2021

Horst Samulowitz

Michael J. Muller

Papers citing "How Much Automation Does a Data Scientist Want?"

15 / 15 papers shown

Title
Towards Feature Engineering with Human and AI's Knowledge: Understanding Data Science Practitioners' Perceptions in Human&AI-Assisted Feature Engineering Design Qian Zhu Dakuo Wang Shuai Ma April Yi Wang Zixin Chen Udayan Khurana Xiaojuan Ma 50 1 0 23 May 2024
Towards a Non-Ideal Methodological Framework for Responsible ML Ramaravind Kommiya Mothilal Shion Guha Syed Ishtiaque Ahmed 51 7 0 20 Jan 2024
Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling Haotian Li Yun Wang Q. V. Liao Huamin Qu 63 23 0 17 Apr 2023
Tracing and Visualizing Human-ML/AI Collaborative Processes through Artifacts of Data Work Jennifer Rogers Anamaria Crisan 27 7 0 05 Apr 2023
AutoML in The Wild: Obstacles, Workarounds, and Expectations Yuan Sun Qiurong Song Xinning Gui Fenglong Ma Ting Wang 21 13 0 21 Feb 2023
Natural Language to Code Generation in Interactive Data Science Notebooks Pengcheng Yin Wen-Ding Li Kefan Xiao Abhishek Rao Yeming Wen ... Paige Bailey Michele Catasta Henryk Michalewski Oleksandr Polozov Charles Sutton 33 57 0 19 Dec 2022
How Do Data Science Workers Communicate Intermediate Results? Rock Yuren Pang Ruotong Wang Joely Nelson Leilani Battle 38 5 0 07 Oct 2022
An Empirical Study on the Usage of Automated Machine Learning Tools Forough Majidi Moses Openja Foutse Khomh Heng Li 45 14 0 28 Aug 2022
Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation Vivian Lai Samuel Carton Rajat Bhatnagar Vera Liao Yunfeng Zhang Chenhao Tan 29 130 0 25 Apr 2022
Telling Stories from Computational Notebooks: AI-Assisted Presentation Slides Creation for Presenting Data Science Work Chengbo Zheng Dakuo Wang A. Wang Xiaojuan Ma 22 52 0 21 Mar 2022
Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks A. Wang Dakuo Wang Jaimie Drozdal Michael J. Muller Soya Park Justin D. Weisz Xuye Liu Lingfei Wu Casey Dugan 55 63 0 24 Feb 2021
How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Study David Piorkowski Soya Park A. Wang Dakuo Wang Michael J. Muller Felix Portnoy 38 131 0 13 Jan 2021
Data Vision: Learning to See Through Algorithmic Abstraction Samir Passi S. Jackson 137 111 0 09 Feb 2020
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI Dakuo Wang Justin D. Weisz Michael J. Muller Parikshit Ram Werner Geyer Casey Dugan Y. Tausczik Horst Samulowitz Alexander G. Gray 178 308 0 05 Sep 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,690 0 28 Feb 2017