Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience

Author:

Liao Q. Vera1ORCID,Subramonyam Hariharan2ORCID,Wang Jennifer3ORCID,Wortman Vaughan Jennifer4ORCID

Affiliation:

1. Microsoft Research, Canada

2. Stanford University, United States

3. Microsoft, United States

4. Microsoft Research, United States

Publisher

ACM

Reference105 articles.

1. 2019. Amazon AWS Machine Learning Services. https://aws.amazon.com/machine-learning/. 2019. Amazon AWS Machine Learning Services. https://aws.amazon.com/machine-learning/.

2. 2019. Google AI for Developers. https://cloud.google.com/products/ai. 2019. Google AI for Developers. https://cloud.google.com/products/ai.

3. 2019. Google People + AI Guidebook.pair.withgoogle.com/guidebook. 2019. Google People + AI Guidebook.pair.withgoogle.com/guidebook.

4. 2019. Hugging Face Models. https://huggingface.co/models. 2019. Hugging Face Models. https://huggingface.co/models.

5. 2019. IBM Design for AI. https://www.ibm.com/design/ai/. 2019. IBM Design for AI. https://www.ibm.com/design/ai/.

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