Through my reporting, I’ve come to understand two things: Artificial intelligence is a technology that takes many forms. It is in fact a multitude of technologies that shape-shift and evolve, not merely based on technical merit but with the ideological drives of the people who create them and the winds of hype and commercialization. While ChatGPT and other so-called large language models or generative AI applications have now taken the limelight, they are but one manifestation of AI, a manifestation that embodies a particular and remarkably narrow view about the way the world is and the way it should be. Nothing about this form of AI coming to the fore or even existing at all was inevitable; it was the culmination of thousands of subjective choices, made by the people who had the power to be in the decision-making room. In the same way, future generations of AI technologies are not predetermined. But the question of governance returns: Who will get to shape them?

There is a different way forward. Artificial intelligence doesn’t have to be what it is today. We don’t need to accept the logic of unprecedented scale and consumption to achieve advancement and progress. So much of what our society actually needs—better health care and education, clean air and clean water, a faster transition away from fossil fuels—can be assisted and advanced with, and sometimes even necessitates, significantly smaller AI models and a diversity of other approaches. AI alone won’t be enough, either: We’ll also need more social cohesion and global cooperation, some of the very things being challenged by the existing vision of AI development.

That tradition of anthropomorphizing continues to this day, aided by Hollywood tales combining the idea of “AI” with age-old depictions of human-made creations suddenly waking up. AI developers speak often about how their software “learns,” “reads,” or “creates” just like humans. Not only has this fed into a sense that current AI technologies are far more capable than they are, it has become a rhetorical tool for companies to avoid legal responsibility. Several artists and writers have sued AI developers for violating copyright laws by using their creative work—without their consent and without compensating them—to train AI systems. Developers have argued that doing so falls under fair use because it is no different from a human being “inspired” by others’ work. The omnipresent AI-to-human analogies have also fueled the sense that such software could become so capable that it surpasses us and comes to threaten our very existence. The fear of superintelligence is predicated on the idea that AI could somehow rise above us in the special quality that has made humans the planet’s superior species for tens of thousands of years.

Now, AI is the harbinger of the fourth industrial revolution. The keystone of the modern superpower. AGI, if ever reached, will solve climate change, enable affordable health care, provide equitable education. OpenAI is the poster child for this line of thought. It cannot say how the technology will deliver on these promises—only that the staggering price society needs to pay for what it is developing will someday be worth it.

It’s hard to fully convey the tragedy of losing a language. For the same reasons AI researchers first gravitated toward language to build their technologies, the loss of a language extends far beyond the loss of a form of communication. Each language encodes within it rich histories, cultures, knowledge; it is the collective product of millions of people across time grasping for the sounds and written forms to capture the subtlest observations about the universe, about life, about the human experience; to share with one another stunning beauty and painful failure; to teach a child, to learn from an elder; to express love.