Meta's announcement of its No Language Left Behind model covering 200 languages, including 55 African languages, triggered investor withdrawals that forced small African language NLP startups to close, according to AI ethics researcher Timnit Gebru at the AI Now Institute.
"When OpenAI or Meta comes with an announcement of a big model, potential investors in these smaller organizations literally told them to close up shop," Gebru said. Investors dismissed the startups as obsolete, claiming "Facebook has solved it, so your little puny startup is not going to be able to do anything."
OpenAI representatives allegedly adopt aggressive tactics with small language AI organizations. "They basically threaten them by saying, 'OpenAI is going to put you out of business soon because we're going to make our models better in your language. You're better off collaborating with us and supplying us data for which we're going to pay you peanuts,'" Gebru revealed.
The pattern reflects what Gebru calls Big Tech's "one giant model for everything" approach, which threatens resource-efficient, task-specific AI development. "People came along and decided that they want to build a machine god," Gebru said, adding that the process involves "stealing data, killing the environment, exploiting labor."
AI researcher Abeba Birhane critiques the "AI for good" framing that accompanies such releases. "It's a way to paint a positive image of AI technologies, especially in light of the backlash—like the resist or refuse AI grassroots movement that's emerging," she said. The framing allows companies to deflect criticism by pointing to purported social benefits.
The critique exposes tension between compute-intensive universal models requiring massive resources and smaller organizations developing specialized solutions for specific languages and tasks. Global South AI organizations face particular vulnerability as Big Tech's resource concentration enables announcements that destabilize their funding regardless of actual product quality or local relevance.
The researchers' warnings come as the AI industry faces mounting scrutiny over resource usage, data practices, and labor conditions. Their analysis challenges whether centralized AI development serves broader technological progress or primarily consolidates corporate control while undermining diverse approaches to AI development worldwide.