Artists can search machine learning databases for links to their work and flag them for removal. It's a part of a bigger Spawning initiative — they're building tools for artist ownership of their training data, allowing them to opt into or opt out of the training of large AI models, set permissions on how their style and likeness is used, and offer their own models to the public.

This experiment shows how words like "assertive" and "gentle" are mapped to stereotypes and biases in models like Stable Diffusion and DALL-E 2 (review). Bloomberg has a good long-read article about this problem.

Under current law, only natural persons may be named as an inventor in a patent application.

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?

AI is like photography in the 19th century–struggling to be accepted as its own art form. Aaron Hertzmann discusses tricky situations in art world.