A fantastic article by Amy Goodchild about the nature of generative art. She digs into three key pillars: randomness, rules, and natural systems.

A great discussion about the relationship between AI and data visualization (more on it). Will we need a speedometer to visualize how fast a car is going when it’s driving itself?

A framework for designers who work with products based on AI, by Nadia Pret. It contains patterns and methods to design them.

How AI designers are bridging the gap between user needs and technological capabilities at Meta.

A talk by Josh Clark on using machine-generated content, insight, and interaction as design material in your everyday work.

These 18 guidelines can help you design AI systems and features that are more human-centered. How to use them in a creative process.

People+AI research initiative. How might we make it easier for engineers to build and understand machine learning systems? How can AI aid and augment professionals in their jobs? Can design thinking open up new applications for AI?

In a study of people interacting with systems built on machine-learning algorithms, users had weak mental models and difficulties making the UI do what they want.

This one-day workshop explores several issues in the domain of generative models for creativity and design. 32 papers were published.

Class Central analyzed online courses on machine learning and selected the best.