Who cooked so hard on some random articles thumbnail?
Nah this is bullshit, and I’m shocked to see it coming from the EFF. If you can’t build your ML model without stealing other peoples’ work to do it, don’t fucking do it. The purpose of IP law is to ensure that people who create are compensated for their work, and I never thought in a million years I’d see the EFF arguing against the protection of people over business.
AI often gets painted as people vs businesses, but that’s not necessarily what it is in many cases. The EFF is arguing for fair use, which is something that they have stood for as long as I can remember. As the article argues, the businesses creating AIs can easily abide by this law, it’s the little guys training things that would be impacted the most.
Let’s say someone spends a decade plus on a small niche blog. The blog has decent readership and even modicum of commercial engagement in its niche.
Should I be allowed to openly use all the data on the blog to develop an AI powered AIBlog 2000 service that enables people to quickly and easily make SEO-optimized spam blogs (it wouldn’t be marketed that way, but that’s what it is) on a variety of topics; including the topic of the niche blog mentioned above?
Am I not giving the EFF enough benefit of the doubt? Is this more of a unique scenario that ignores the benefits of EFF’s approach?
What am I missing here?
AI owned by billionaires is something this world does not need. These should be accessible for anyone’s use.
Anyone have a link to the text of the bill?
Can’t speak for the relative merits of the bill. To be honest it doesn’t really matter, since it’s a bad idea to use any American services, be it from big tech or from startups.
However, I do have issues with the characterization of small startups leveraging “AI” in the article. Vast majority of startups add “AI powered” both as consumer marketing and a fundraising method. Even if they do actually use ML powered features, it is likely these features would simply be part of their package and marketed something along the lines of “automated recommendation for configuring [X]”. Many such features cannot even leverage public works since startups tend to focus on more niche use use cases of ML tech since it’s difficult to competing around something like LLMs.
Something about their framing of startups just sounds off.
