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Grammy Chief Harvey Mason Clarifies New AI Rule: We’re Not Giving an Award to a Computer
Grammy Chief Harvey Mason Clarifies New AI Rule: We’re Not Giving an Award to a Computer
The full wording of the ruling follows: The GRAMMY Award recognizes creative excellence. Only human creators are eligible to be submitted for consideration for, nominated for, or win a GRAMMY Award. A work that contains no human authorship is not eligible in any Categories. A work that features elements of A.I. material (i.e., material generated by the use of artificial intelligence technology) is eligible in applicable Categories; however: (1) the human authorship component of the work submitted must be meaningful and more than de minimis; (2) such human authorship component must be relevant to the Category in which such work is entered (e.g., if the work is submitted in a songwriting Category, there must be meaningful and more than de minimis human authorship in respect of the music and/or lyrics; if the work is submitted in a performance Category, there must be meaningful and more than de minimis human authorship in respect of the performance); and (3) the author(s) of any A.I. material incorporated into the work are not eligible to be nominees or GRAMMY recipients insofar as their contribution to the portion of the work that consists of such A.I material is concerned. De minimis is defined as lacking significance or importance; so minor as to merit disregard.
the human portion of the of the composition, or the performance, is the only portion that can be awarded or considered for a Grammy Award. So if an AI modeling system or app built a track — ‘wrote’ lyrics and a melody — that would not be eligible for a composition award. But if a human writes a track and AI is used to voice-model, or create a new voice, or use somebody else’s voice, the performance would not be eligible, but the writing of the track and the lyric or top line would be absolutely eligible for an award.”
·variety.com·
Grammy Chief Harvey Mason Clarifies New AI Rule: We’re Not Giving an Award to a Computer
The $2 Per Hour Workers Who Made ChatGPT Safer
The $2 Per Hour Workers Who Made ChatGPT Safer
The story of the workers who made ChatGPT possible offers a glimpse into the conditions in this little-known part of the AI industry, which nevertheless plays an essential role in the effort to make AI systems safe for public consumption. “Despite the foundational role played by these data enrichment professionals, a growing body of research reveals the precarious working conditions these workers face,” says the Partnership on AI, a coalition of AI organizations to which OpenAI belongs. “This may be the result of efforts to hide AI’s dependence on this large labor force when celebrating the efficiency gains of technology. Out of sight is also out of mind.”
This reminds me of [[On the Social Media Ideology - Journal 75 September 2016 - e-flux]]:<br>> Platforms are not stages; they bring together and synthesize (multimedia) data, yes, but what is lacking here is the (curatorial) element of human labor. That’s why there is no media in social media. The platforms operate because of their software, automated procedures, algorithms, and filters, not because of their large staff of editors and designers. Their lack of employees is what makes current debates in terms of racism, anti-Semitism, and jihadism so timely, as social media platforms are currently forced by politicians to employ editors who will have to do the all-too-human monitoring work (filtering out ancient ideologies that refuse to disappear).
Computer-generated text, images, video, and audio will transform the way countless industries do business, the most bullish investors believe, boosting efficiency everywhere from the creative arts, to law, to computer programming. But the working conditions of data labelers reveal a darker part of that picture: that for all its glamor, AI often relies on hidden human labor in the Global South that can often be damaging and exploitative. These invisible workers remain on the margins even as their work contributes to billion-dollar industries.
One Sama worker tasked with reading and labeling text for OpenAI told TIME he suffered from recurring visions after reading a graphic description of a man having sex with a dog in the presence of a young child. “That was torture,” he said. “You will read a number of statements like that all through the week. By the time it gets to Friday, you are disturbed from thinking through that picture.” The work’s traumatic nature eventually led Sama to cancel all its work for OpenAI in February 2022, eight months earlier than planned.
In the day-to-day work of data labeling in Kenya, sometimes edge cases would pop up that showed the difficulty of teaching a machine to understand nuance. One day in early March last year, a Sama employee was at work reading an explicit story about Batman’s sidekick, Robin, being raped in a villain’s lair. (An online search for the text reveals that it originated from an online erotica site, where it is accompanied by explicit sexual imagery.) The beginning of the story makes clear that the sex is nonconsensual. But later—after a graphically detailed description of penetration—Robin begins to reciprocate. The Sama employee tasked with labeling the text appeared confused by Robin’s ambiguous consent, and asked OpenAI researchers for clarification about how to label the text, according to documents seen by TIME. Should the passage be labeled as sexual violence, she asked, or not? OpenAI’s reply, if it ever came, is not logged in the document; the company declined to comment. The Sama employee did not respond to a request for an interview.
In February, according to one billing document reviewed by TIME, Sama delivered OpenAI a sample batch of 1,400 images. Some of those images were categorized as “C4”—OpenAI’s internal label denoting child sexual abuse—according to the document. Also included in the batch were “C3” images (including bestiality, rape, and sexual slavery,) and “V3” images depicting graphic detail of death, violence or serious physical injury, according to the billing document.
I haven't finished watching [[Severance]] yet but this labeling system reminds me of the way they have to process and filter data that is obfuscated as meaningless numbers. In the show, employees have to "sense" whether the numbers are "bad," which they can, somehow, and sort it into the trash bin.
But the need for humans to label data for AI systems remains, at least for now. “They’re impressive, but ChatGPT and other generative models are not magic – they rely on massive supply chains of human labor and scraped data, much of which is unattributed and used without consent,” Andrew Strait, an AI ethicist, recently wrote on Twitter. “These are serious, foundational problems that I do not see OpenAI addressing.”
·time.com·
The $2 Per Hour Workers Who Made ChatGPT Safer