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Dodge last Live programming sessions on stage, AI refresher courses, an obstacle course of gadgets, and people walking around you with glowing green muted disco-style headphones blasting UN panel discussions into your ears, and you can take a pause for breath. But you may find yourself in the mesh zone, on a swivel seating device called the UFOTECH that looks more like the kind of lazy Susan you might encounter in a Chinese restaurant than the mesh seat it was designed to operate on.
This is it Artificial Intelligence for Good SummitOrganized by the United Nations International Telecommunication Union (ITU), representatives from the public and private sectors attempt to discuss how technology can be harnessed for the benefit of humanity, rather than at its expense.
As Silicon Valley executives and AI lab leaders testify before lawmakers in Washington about the dangers of superintelligence, and the White House imposes chip export controls, the United Nations AI for Good Summit — now in its 10th year — is focusing on more idealistic goals.
“We are convinced that artificial intelligence, if deployed responsibly, can help solve humanity’s most pressing problems – from hunger to disease to global warming,” said Doreen Bogdan Martin, Secretary-General of the ITU, in a keynote speech on the conference’s main stage. “Today, that idea is being tested, including by the challenges that AI itself brings, even as we strive to use it for good.”
What is good – and what is the benefit to humanity – was the question throughout the conference, which spread across a massive 106,000 square meter conference center on the edge of Geneva’s airport district. The sessions were buoyed by a drumbeat of concern that the reckless proliferation of unchecked corporate monopolies is already exacerbating global inequality and eroding human rights.
For some on the front lines, the tech industry’s utopian veneer has already faded. Speaking on the sidelines of the event, Giulio Coppi, chief humanitarian officer at campaign group Access Now, pointed to the humanitarian and public sectors’ over-reliance on big technology. “We have to get out of the age of innocence,” says Coby, calling on organizations to stop treating tech companies “like your best friends.” He points to a decade of murky deals worth millions of dollars financed with public money. “You can’t even explain what’s inside your technology stack, because it keeps changing,” he warns.
Opposition to Kobe was muted compared to some: pro-Palestine activists She stormed the stage During a keynote speech by Werner Vogels, Amazon’s chief technology officer, he claimed that the company’s technology was being used by Israel against Palestinians, before it was eventually removed from the venue.
“When we talk about artificial intelligence, we love the hype, we get excited about it,” says Vijay Janappa Reddy, an engineering professor at Harvard University, over the din of competing sessions during a presentation. “The damn thing never makes it to practice.” The problem, he says, is that “good” is too vague a standard to engineer. “When you’re an engineer, good means nothing. I can’t build you anything good. An airplane that flies for five minutes is no good.”
Much of the global discussion about AI now revolves around access: who can use the models, who can buy chips, and who is excluded from the computational economy. It’s part of the reason the Trump administration is doing this Implemented and then removedAnd export controls on leading border AI models, and China as well It is said that he thinks Which makes open weight models less open. Tighter access and exclusion of poor countries could leave them dependent on foreign infrastructure platforms and standards.
In a session on AI devices and the widening digital divide, speakers argued that computing is no longer just a technology problem, but a development problem. “If we mean AI for good, and we mean computing for all, we must realize that it is about development infrastructure, not just technology,” says Syed Munir Khusraw, president of the Institute for Policy, Advocacy and Governance. Others pointed out that most of the big language models are still English-centric, making smaller, homegrown LLM programs running on cheaper hardware necessary if AI is to serve communities outside affluent markets.
