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Towards A Process Model for Co-Creating AI Experiences

Towards A Process Model for Co-Creating AI Experiences

15 April 2021
Hariharan Subramonyam
C. Seifert
Eytan Adar
ArXivPDFHTML

Papers citing "Towards A Process Model for Co-Creating AI Experiences"

8 / 8 papers shown
Title
AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development
AI Mismatches: Identifying Potential Algorithmic Harms Before AI Development
Devansh Saxena
Ji-Youn Jung
J. Forlizzi
Kenneth Holstein
J. Zimmerman
71
0
0
25 Feb 2025
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
49
16
0
17 Jan 2024
Unpacking Human-AI interactions: From interaction primitives to a design
  space
Unpacking Human-AI interactions: From interaction primitives to a design space
Konstantinos Tsiakas
Dave Murray-Rust
32
3
0
10 Jan 2024
Addressing UX Practitioners' Challenges in Designing ML Applications: an
  Interactive Machine Learning Approach
Addressing UX Practitioners' Challenges in Designing ML Applications: an Interactive Machine Learning Approach
K. J. Kevin Feng
David W. McDonald
HAI
23
11
0
23 Feb 2023
fAIlureNotes: Supporting Designers in Understanding the Limits of AI
  Models for Computer Vision Tasks
fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks
Steven Moore
Q. V. Liao
Hariharan Subramonyam
19
27
0
22 Feb 2023
Designerly Understanding: Information Needs for Model Transparency to
  Support Design Ideation for AI-Powered User Experience
Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience
Q. V. Liao
Hariharan Subramonyam
Jennifer Wang
Jennifer Wortman Vaughan
HAI
33
58
0
21 Feb 2023
Improving Human-AI Partnerships in Child Welfare: Understanding Worker
  Practices, Challenges, and Desires for Algorithmic Decision Support
Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support
Anna Kawakami
Venkatesh Sivaraman
H. Cheng
Logan Stapleton
Yanghuidi Cheng
Diana Qing
Adam Perer
Zhiwei Steven Wu
Haiyi Zhu
Kenneth Holstein
39
107
0
05 Apr 2022
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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