Who benefits from artificial intelligence? This fundamental question, which has come to the fore during the AI boom of the past few years, was front and center at a conference at MIT on Wednesday, as speakers and audience members grappled with the many dimensions of AI’s impact.
In one of the conference’s keynote speeches, journalist Karen Hao ’15 called for a change in the way AI is developed, including moving away from the large-scale use of data, data centers, and models used to develop tools under the rubric of “general artificial intelligence.”
“This scale is unnecessary,” said Hao, who has become a prominent voice in AI debates. “You don’t need this AI scale and calculate to get the benefits.” Indeed, he added, “If we really want AI to be broadly beneficial, we urgently need to move away from this path.”
Hao previously worked at The Wall Street Journal again MIT Technology Reviewand author of the 2025 book, “Empire of AI.” He reported extensively on the growth of the AI industry.
In his remarks, Hao revealed the staggering size of the datasets now being used by major AI companies to develop large language models. He also emphasized other trade-offs to this growth, such as greater energy consumption and the outsourcing of hyper-scale data centers, which also consume a lot of water. Using his reporting, Hao also noted the number of people from input work performed by gig-economy workers around the world, manually inputting data into hyper-scale models.
Conversely, Hao offered, an alternative to AI may exist in the example of AlphaFold, a Nobel prize-winning tool used to identify protein structures. This represents the idea of ”a small, task-specific AI model that addresses a well-scoped problem that lends itself to AI computing power,” Hao said.
He added: “It is trained on highly selected data sets that are only relevant to the problem at hand: protein folding and amino acid sequence. …
In the second keynote speech, scholar Paola Ricaurte emphasized the desirability of purpose-driven AI approaches, revealing a number of key concepts for assessing the usefulness of AI.
“There is no idea of having a technology that will not respond to the communities that will use it,” said Ricaurte.
He is a professor at the Tecnologico de Monterrey in Mexico and works at the Berkman Klein Center for Internet and Society at Harvard University. Ricaurte has also served on expert committees such as the Global Partnership for AI, UNESCO’s AI Ethics Experts Without Borders, and the Women for Ethical AI project.
The event was hosted by the MIT Program in Women’s and Gender Studies. Manduhai Buyandelger, program director and professor of anthropology, gave introductory remarks.
Titled “Gender, State, and AI: A Symposium and Design Workshop,” the event was held in the conference space at the MIT Schwartzman College of Computing, and more than 300 people attended keynote discussions. There was also a part of the event dedicated to discussion groups, and an afternoon design session, in different subject areas.
In his speech, Hao criticized the vagueness of the AI discourse, suggesting that it hinders a thoughtful discussion about the direction of the industry.
“Part of the challenge in talking about AI is the complete lack of clarity in the term ‘artificial intelligence,'” Hao said. “It’s like the word ‘transportation.’ You could refer to anything from a bicycle to a rocket.” As a result, he said, “when we talk about achieving its benefits, we actually have to be very specific. Which AI technology are we talking about, and which ones do we want more of?”
In his opinion, small-sized tools – more like a bicycle, by analogy – are more useful every day. As another example, Hao mentioned a climate change AI project, which focuses on tools that can help improve energy efficiency in buildings, track emissions, improve supply chains, predict severe weather, and more.
“This is the idea of AI that we should be building on,” Hao said.
In closing, Hao encouraged audience members to be active participants in AI-related discourse and projects, saying that the technology’s trajectory had not yet been paved, and that public intervention mattered.
Quoting author Rebecca Solnit, Hao suggested to the audience that “Hope is putting oneself in the position of not knowing what will happen, and that in the place of uncertainty there is room to do something.” He also noted that, “Each of you has a big role to play in shaping the development of technology.”
Ricaurte, likewise, encouraged those attending the event to be active participants in AI issues, noting that the technology will work best when the pressing daily needs of all citizens are taken into account.
“We have a responsibility to make hope possible,” said Ricaurte.
