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Overview
The Guidelines for Human-AI Interaction synthesize more than 20 years of thinking and research in human-AI interaction. Developed in a collaboration between Aether, Microsoft Research, and Office, the guidelines were validated through a rigorous, 4-step process described in the CHI 2019 paper, Guidelines for Human-AI Interaction. They recommend best practices for how AI systems should behave upon initial interaction, during regular interaction, when they’re inevitably wrong, and over time.
We hope you can use these Guidelines for Human-AI Interaction throughout your design process as you evaluate existing ideas, brainstorm new ones, and collaborate with the multiple disciplines involved in creating AI.
Resources
Intro to the guidelines:
- Microsoft Docs: Introduction to guidelines for human-AI interaction
- Medium Post: Guidelines on human-AI interaction
How to use the guidelines:
- In the creative design process. Medium Post: AI Guidelines in the Creative Process: How we’re putting the human-AI guidelines into practice at Microsoft
- During software and AI model development. Microsoft Research Blog: How to build effective human-AI interaction: Considerations for machine learning and software engineering
- To discover open software development and AI research challenges. Tutorial at the AAAI 2020 Conference on Artificial Intelligence: How to build effective human-AI interaction
Why and how the guidelines were developed:
- Original research article from the ACM CHI 2019 Conference on Human Factors in Computing Systems (Best Paper Honorable Mention): Guidelines for Human-AI Interaction
- Summary on the Microsoft Research Blog: Guidelines for human-AI interaction design
Assets:
- Printable poster (PDF)
- Poster image (JPG)
- Printable cards – English (PDF)
- Printable cards – Chinese (PDF)
- Interactive cards with examples of the guidelines in practice
Please let us know how you are using these guidelines. Send feedback to aiguidelines@microsoft.com.
People
Derek DeBellis
Data Scientist II
Office Planning & Research
Daniel S. Weld
Thomas J. Cable / WRF Professor
Paul G. Allen School of Computer Science & Engineering