Whether you're a small restaurant or not you have to ensure that you're not stealing your ingredients. So why is this any different?

What about the 1-2 person creative startups? Who is protecting their works in a society that devalues artists so much that "starving artist" is an expectation?

The idea that you shouldn't be expected to know what data you're using to train your systems and that doing so is "an impossible task" is so normalized that its hard to know that this was not always the case even in the field of AI.

Data theft and scraping became completely normalized, along with the exploitation of crowdworkers, with the advent of photo sharing and other platforms and others like amazon mechanical turk.

So now NOT exploiting people and stealing data is the anomaly.

"A.I. Training Is Like Reading And It’s Very Likely Fair Use"

These people are unbelievable.

@timnitGebru You're echoing an argument that was once leveled against search engines: the right to access information is presumed as long as it isn't hidden behind a paywall or excluded from indexing.

Consider the requirements for object recognition, where YOLO models typically need at least 1,000 training images of the target object, alongside images that do not depict it. Citing relevant examples in the output becomes impractical. While image LLMs may operate on fewer inputs, they still offer a rich diversity. In contrast, a text-based LLMs might align more closely with your expectations; for instance, Perplexity.ai generates responses and links to sources it deems relevant.

However, it’s crucial that training data undergoes meticulous curation to eliminate noise, or we risk developing flawed AI systems—something all too common in many chatbots today. This challenge will persist until AI systems evolve to effectively self-filter out the noise, making them truly intelligent.