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How Do UX Practitioners Communicate AI as a Design Material? Artifacts,
  Conceptions, and Propositions

How Do UX Practitioners Communicate AI as a Design Material? Artifacts, Conceptions, and Propositions

27 May 2023
K. J. Kevin Feng
Maxwell James Coppock
David W. McDonald
ArXivPDFHTML

Papers citing "How Do UX Practitioners Communicate AI as a Design Material? Artifacts, Conceptions, and Propositions"

8 / 8 papers shown
Title
Establishing Heuristics for Improving the Usability of GUI Machine
  Learning Tools for Novice Users
Establishing Heuristics for Improving the Usability of GUI Machine Learning Tools for Novice Users
Asma Z. Yamani
Haifa Al-Shammare
Malak Baslyman
26
0
0
14 May 2024
Canvil: Designerly Adaptation for LLM-Powered User Experiences
Canvil: Designerly Adaptation for LLM-Powered User Experiences
K. J. Kevin Feng
Q. V. Liao
Ziang Xiao
Jennifer Wortman Vaughan
Amy X. Zhang
David W. McDonald
43
16
0
17 Jan 2024
User Experience Design Professionals' Perceptions of Generative
  Artificial Intelligence
User Experience Design Professionals' Perceptions of Generative Artificial Intelligence
Jie Li
Hancheng Cao
Laura Lin
Youyang Hou
Ruihao Zhu
Abdallah El Ali
39
49
0
26 Sep 2023
Whither AutoML? Understanding the Role of Automation in Machine Learning
  Workflows
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
Doris Xin
Eva Yiwei Wu
D. Lee
Niloufar Salehi
Aditya G. Parameswaran
56
91
0
13 Jan 2021
Machine Learning Uncertainty as a Design Material: A
  Post-Phenomenological Inquiry
Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry
J. Benjamin
Arne Berger
Nick Merrill
James Pierce
40
91
0
11 Jan 2021
AutoML to Date and Beyond: Challenges and Opportunities
AutoML to Date and Beyond: Challenges and Opportunities
Shubhra (Santu) Karmaker
Md. Mahadi Hassan
Micah J. Smith
Lei Xu
Chengxiang Zhai
K. Veeramachaneni
76
225
0
21 Oct 2020
Trust in Data Science: Collaboration, Translation, and Accountability in
  Corporate Data Science Projects
Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects
Samir Passi
S. Jackson
171
108
0
09 Feb 2020
Improving fairness in machine learning systems: What do industry
  practitioners need?
Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miroslav Dudík
Hanna M. Wallach
FaML
HAI
192
743
0
13 Dec 2018
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