AI ethics researchers Timnit Gebru and Abeba Birhane are mounting a systematic critique of how major AI companies market their technology, arguing that 'AI for good' messaging serves as a deflection strategy against grassroots resistance movements.
"AI for good allows companies to say 'Look, we're doing something good! Everything about AI is not bad. And you can't criticize us,'" said Birhane in a new AI Now Institute publication examining the framing.
The critique coincides with documented cases of Big Tech announcements destroying smaller AI organizations focused on underserved languages. When Meta released its No Language Left Behind model claiming automatic translation across 200 languages including 55 African languages, investors told small African language NLP startups to shut down.
"[Investors] were like, 'Facebook has solved it, so your little puny startup is not going to be able to do anything,'" Gebru said, describing a pattern where Big Tech model releases trigger investor pressure on competing startups.
OpenAI representatives have allegedly taken a more direct approach. "When they speak to people at OpenAI and other places, 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,'" Gebru reported, adding that the companies offer to purchase data from these organizations for minimal compensation.
Gebru characterized the dominant AI development paradigm as fundamentally extractive. "People came along and decided that they want to build a machine god and then claimed that they are doing it. And then they end up stealing data, killing the environment, exploiting labor in that process," she said.
The researchers argue that resource-intensive large language models concentrate power with well-funded corporations while making AI development inaccessible to organizations serving marginalized communities. This criticism comes as AI companies face increasing regulatory scrutiny, with Anthropic recently challenging security labels and the UK trialing social media restrictions for youth.
The AI Now Institute publications highlighting these issues represent growing academic pushback against corporate narratives that position AI development as universally beneficial while obscuring competitive practices that eliminate specialized alternatives.