Machine Learning Education for Artists, Musicians, and Other Creative Practitioners
By Rebecca Feibrink | A paper aiming to provide foundation for the research and practice of machine learning education for creative practitioners.
Measuring trends in Artificial Intelligence
Andrew Ng Explains Enterprise AI Strategy
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
User data is not objective
Data Science and Design Thinking Belong Together
Marry Data Science with User Research. Ethical Design Depends on It.
Simultaneous Triangulation: Mixing User Research & Data Science Methods
AI x User Research - Newsletter #2
Speculative Everything
SpeculativeEdu | Interview: Nick Baerten
Design Jobs of 2050
From Hype to Practice: Revealing the Effects of AI in Service Design
Want to Reduce Fear of AI? Start with Service Design
Service Design in the Age of Automation
The Evidence of Design 2.0 - An Impactful Service Identity Designed with AI
AI x Service Design - Newsletter #1
Do something interesting
Tech Ethics Curricula: A Collection of Syllabi | by Casey Fiesler | Medium
Systems Smart Enough To Know When They're Not Smart Enough | Big Medium
Stanford Institute for Human-Centered Artificial Intelligence |
Spotify Design - Simultaneous Triangulation: Mixing User Research & Data Science Methods
Robots Are Wrong Too—Confusion Mapping for the Worst Case
Rehearsing the Future - Editorial by Google Design
Predictably Smart - Google Design
Material Design Patterns for machine learning-powered features - Google
Machine Learning for Designers - O'REILLY
Machine Ethics Toolkit – Run your own DIY Workshop
Interpretable Machine Learning | A Guide for Making Black Box Models Explainable
IBM Design for AI