Yet another sad story shows that futuristic AI-based products are backed by sweat & pain of low-waged human workers.

A fantastic initiative — it shows source images in the training data of models like Stable Diffusion that led to an image you've just generated.

Fawzi Ammache explores solutions and challenges of paying artists for their contributions to train AI models.

Josh W Comeau thinks about increasingly-impressive demos from tools like GPT-4, and thinks if front-end developers should worry that by the time they're fluent in HTML/CSS/JS, there won't be any jobs left for them. He disagrees with that and believes it's similar to no-code website builders which exist since 1996. New algorithm-driven tools will make developmers more productive. Christian Heilmann has similar thoughts.

Arvind Sanjeev shows how private user data leaks into machine learning data — from medical records and smart home photos to real faces.

A creepy story of Hollie Mengert — her commercial illustrations were used to train a neural network and let anyone to literally clone the style. Andy Bayo contacted code author Ogbogu Kalu. Comments are disgusting — people just don't respect Hollie's work.

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.

Aaron Hertzmann draws interesting parallels between today's algorithm-driven design tool boom and other branches of arts and culture for past centuries. He thinks current state is just interim and shows on-spot analogies.

Brilliant thinking by Alexander Wales on how tools like DALL-E and Midjourney influence professional illustrators and artists. It'll kick the economy of these professions in the stomach for sure. However, art as self-expression will stay for sure. Erik Hoel has a similar take.

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.