“人工智能是非洲智慧”:训练人工智能的工人正在反击
'AI is African intelligence': The workers who train AI are fighting back

原始链接: https://www.404media.co/ai-is-african-intelligence-the-workers-who-train-ai-are-fighting-back/

迈克尔·杰弗里·亚洲的经历凸显了人工智能兴起背后隐藏的人为代价。在肯尼亚,亚洲每天花费数小时标记色情内容并参与模拟的在线关系——本质上为人工智能性机器人提供劳动力——而报酬微薄。这项工作由算法控制,要求改变人物设定,对他的身心造成严重损害,导致失眠、创伤后应激障碍和性功能障碍,最终破坏了他的个人生活。 现在,作为数据标注者协会(DLA)秘书长,亚洲倡导改善这些经常被剥削的工人的工作条件。数据标注者对于训练和完善人工智能至关重要,但他们获得的报酬极低,缺乏足够的心理健康支持,尽管他们驱动着Meta、OpenAI和Gemini等科技巨头的估值。 DLA正在争取公平工资、福利以及结束限制性保密协议,将这种情况定义为现代跨国公司延续的殖民剥削。由于数据标注是肯尼亚科技劳动力中的重要组成部分,该运动寻求更广泛的团结以及对人工智能依赖弱势劳动力的伦理影响的认识。

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原文

Every day, Michael Geoffrey Asia spent eight consecutive hours at his laptop in Kenya staring at porn, annotating what was happening in every frame for an AI data labeling company. When he was done with his shift, he started his second job as the human labor behind AI sex bots, sexting with real lonely people he suspected were in the United States. His boss was an algorithm that told him to flit in and out of different personas.

“It required a lot of creativity and fast thinking. Because if I’m talking to a man, I’m supposed to act like a woman. If I’m talking to a woman, I need to act like a man. If I’m talking to a gay person, I need to act like a gay person,” he told me at a coworking space I met him at in Nairobi. After doing this for months, he, like other data labelers, developed insomnia, PTSD, and had trouble having sex. 

“It got to a point where my body couldn’t function. Where I saw someone naked, I don’t even feel it. And I have a wife, who expects a lot from you, a young family, she expects a lot from you intimately. But you can’t, like, do it,” Asia said. “It fractured a lot of things for me. My body is like, not functioning at all.”

Asia eventually hit a breaking point and stopped working for AI companies. He is now the secretary general of a Kenyan organization called the Data Labelers Association (DLA) and the author of “The Emotional Labor Behind AI Intimacy,” a testimony of his time working as the real human labor behind AI sex bots. As part of the DLA, Asia has been working to organize workers to fight for better pay, better mental health services, an end to draconian non-disclosure agreements, and better benefits for a workforce that often earns just a few dollars a day. Data labelers train, refine, and moderate the outputs of AI tools made by the largest companies in the world, yet they are wildly underpaid and haven’t benefitted from the runaway valuations of AI companies. 

Last month, the DLA held one of its largest events at the Nairobi Arboretum, sign up new members, and to help them tell their stories.  

These workers are required to stare at horrific content for many hours straight with few mental health resources, are largely managed by opaque algorithms, and, crucially, are the workers powering the runaway valuations of some of the richest and most powerful companies in the world.

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Do you know anything else about data labeling or the human labor behind AI? I would love to hear from you. Using a non-work device, you can message me securely on Signal at jason.404. Otherwise, send me an email at [email protected].

“You can’t understand where you’re positioned if you don’t understand your history,” Angela, one of the day’s speakers, told the workers who had assembled there (many of the speakers at the event did not give their full names). “When you think of colonialism, we were under British Imperial East Africa Company […] so literally, we are working under a company. We are just products, part of their operation. Stakeholders, we can say, but we are at the bottom of the bottom.”

“These multinationals are coming to rule and dominate here,” she added. “It’s a very unfortunate supply chain, and my call today as data labelers is to build up on this—as we are fighting for labor rights, we are also fighting for the environment […] we are fighting big companies. We are fighting the British imperialist companies of today. It’s Apple, it’s Meta, it’s Gemini. Those are the ones we’re still fighting. It’s a call for solidarity and expanding our thinking beyond what we are doing, beyond our labor.”

In my few days in Kenya earlier this year, where I was traveling to speak at a conference about AI and journalism, it was immediately clear that data labelers make up a significant portion of the country’s tech workforce. Nearly everyone I spoke to there had either been a data labeler (or a content moderator) themselves or knows someone who has. Leaving the airport in Nairobi, you immediately drive by Sameer Business Park, an office complex that houses Sama, a San Francisco-headquartered “data annotation and labeling company” that has contracted with Meta, OpenAI, and many other tech giants. Sama has been sued repeatedly for its low pay and the fact that many of its workers suffer PTSD from repetitively looking at graphic content. For years, a giant sign outside its office read: “Samasource THE SOUL OF AI.” My Uber driver asked why I was going to a random office building in Nairobi’s Central Business District—I told her I was going to interview a data labeler. “Oh, I do data labeling too,” she said.

Michael Geoffrey Asia. Image: Jason Koebler

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