"In the end, the real problem is arguably not that the data labelers shared the images on social media. Rather, it’s that this type of AI training set—specifically, one depicting faces—is far more common than most people understand, notes @milamiceli, a sociologist and computer scientist who has been interviewing distributed workers contracted by data annotation companies for years....The data labelers found this work “really uncomfortable,” she adds.
DAIR & our collaborators call on @facctconference@FAccT to divest from Israeli apartheid, occupation & genocide. Get our zines on the complicity of the conference's sponsors, & a #NoTechForGenocide pin if you haven't done so already.
"When I heard the released demo, I was shocked, angered and in disbelief that Mr. Altman would pursue a voice that sounded so eerily similar to mine that my closest friends and news outlets could not tell the difference...Mr. Altman even insinuated that the similarity was intentional, tweeting a single word 'her' - a reference to the film in which I voiced a chat system, Samantha, who forms an intimate relationship with a human."
"I’ve written about relationships between tech companies and the military before, so I shouldn’t have been surprised by anything I saw or heard at this conference. But when it ended, and I departed DC for home, it felt like my life force had been completely sucked out of my body."
Angie Wang's illustrated essay for the New Yorker, wondering whether her child's early attempts at speech were the same as LLMs, was a finalist for the 2024 Pulitzer Prize. "A toddler has a life, and learns language to describe it. An L.L.M. learns language but has no life of its own to describe," she writes.
"But while authorities generally pitch facial recognition as a tool to capture terrorists or wanted murderers, the technology has also emerged as a critical instrument in a very particular context: punishing protesters." by Darren Loucaides
"Experts who reviewed the policy changes at The Intercept’s request said OpenAI appears to be silently weakening its stance against doing business with militaries. “I could imagine that the shift away from ‘military and warfare’ to ‘weapons’ leaves open a space for OpenAI to support operational infrastructures as long as the application doesn’t directly involve weapons development narrowly defined,” said Lucy Suchman, ...
"Microsoft increased worldwide water consumption by a whopping 34 percent — up to almost 1.7 billion gallons annually — last year, which outside researchers told the AP is most likely due to increased AI training. That's dwarfed by Google, which used 5.6 billion gallons last year, a 20 percent jump that's also likely attributable to machine learning." Via Tech Won't Save Us.
@alex and @emilymbender will be discussing large language models and AI Hype on September 21 at 8pm PDT/4pm UK on LinkedIn Live. More details on event page.
"At the center of the concerns...is a fear shared by members of both the public and private sectors that Congress has become so preoccupied with the long-term, existential threats of AI that it’s skipping right over all of the immediate risks that AI ethicists and civil rights advocates have been warning about for years: Things like algorithmic profiling by law enforcement and AI-enabled bias in school admissions, healthcare, insurance, and other sensitive areas."
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