Designing the User Experience of Machine Learning Systems
Papers from the 2017 AAAI Spring Symposium
Mike Kuniavsky, Elizabeth Churchill, Molly Wright Steenson, Organizers
Technical Report SS-17-04
This technical report has been published as a section in The 2017 AAAI Spring Symposium Series: Technical Reports.
Contents
Interactive Machine Learning for End-User Innovation
Francisco Bernardo, Michael Zbyszynski, Rebecca Fiebrink, Mick Grierson
When User Experience Designers Partner with Data Scientists
Fabien Girardin, Neal Lathia
Challenges in Providing Automatic Affective Feedback in Instant Messaging Applications
Chieh-Yang Huang, Ting-Hao Kenneth Huang, Lun-Wei Ku
An Experimentation Engine for Data-Driven Fashion Systems
Ranjitha Kumar, Kristen Vaccaro
A Portable Navigation System with an Adaptive Multimodal Interface for the Blind
Jacobus Cornelius Lock, Grzegorz Cielniak, Nicola Bellotto
Communicating Machine Learned Choices to E-Commerce Users
Narayanan Seshadri, Gyanit Singh, Justin House, Mukesh Nathan, Nish Parikh
The Role of Design in Creating Machine-Learning-Enhanced User Experience
Qian Yang
Not-so-Autonomous, Very Human Decisions in Machine Learning: Questions When Designing for ML
Henriette Cramer, Jenn Thom
Design implications for Designing with a Collaborative AI
Janin Koch
DJ Bot: Needfinding Machines for Improved Music Recommendations
Nikolas Martelaro, Wendy Ju
Exploring Synergies between Visual Analytical Flow and Language Pragmatics
Vidya Setlur, Melanie Tory
Dice in the Black Box: User Experiences with an Inscrutable Algorithm
Aaron Springer, Victoria Hollis, Steve Whittaker
Reimagining the Goals and Methods of UX for ML/AI
Philip van Allen
How Anticipatory Design Will Challenge Our Relationship with Technology
Joël van Bodegraven
Privacy by Design in Machine Learning Data Collection: A User Experience Experimentation
Jonathan Vitale, Meg Tonkin, Suman Ojha, Mary-Anne Williams, Xun Wang, William Judge
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