IImagine if the world’s response to climate change was based solely on speculative predictions from experts and CEOs rather than rigorous—if still imperfect—climate science models. “Two degrees of warming will come soon, but it will change the world less than we all think,” someone might say. “Two degrees of warming is not coming. This will take a long time”, another might counter.
This is more or less the world we live in with artificial intelligence, with Sam Altman, CEO of OpenAI saying that AI systems that can perform any task a human can perform will be developed in the “reasonably near future,” while Yann LeCun, chief AI scientist at Facebook, argues that human-level AI systems “will take a long time.”
Jaime Sevilla, a 28-year-old Spanish researcher, is trying to change that. It is unclear whether and how the capabilities of the most advanced AI systems will continue to rapidly progress and what the effects of these systems will be on society. But given how important AI already is, it’s worth trying to bring some of the rigor that characterizes climate science to predicting the future of AI, says Sevilla. “Even if innovation in AI stops, this is already a technology that will affect the lives of many people,” he says. “That should be excuse enough for us to take this seriously.”
See more information: 4 Charts That Show Why AI Progress Is Unlikely to Slow Down
To do this, in 2022, Sevilla founded Epoch AI, a non-profit research organization that investigates historical trends in AI and uses these trends to help predict how the technology might develop in the future. “We want to do something similar for artificial intelligence to what William Nordhaus, the Nobel laureate, did for climate change,” he says. “He laid the foundation for rigorous study and thoughtful action guided by evidence. And we want to do the same. We want to follow in his footsteps.”
Seville grew in Torrejón de Ardoz, an industrial suburb of Madrid. His early interest in technology led him to graduate in mathematics and computer engineering from the Complutense University of Madrid. There, he inadvertently planted the first seeds of Epoch AI – in his junior year, he returned to high school to give a presentation on rationality and artificial intelligence, impressing Pablo Villalobos, a student in the audience who would go on to be Epoch’s first volunteer employee. THERE.
In 2020, Sevilla began his doctorate. in artificial intelligence at the University of Aberdeen. Stuck at home by COVID-19 restrictions and feeling out of place as a sun-loving Spaniard in dreary Scotland, he had time to think more seriously about where AI could go. “Surprisingly, there hasn’t been anyone who has done a systematic analysis of what the trend has been in machine learning over the last few years,” he says. “I thought, well, if no one is doing it, then I might as well start.”
He and Villalobos began spending their free hours poring over hundreds of academic papers, documenting the amount of computing power and data used to train significant AI models. Feeling confident in the importance of this work but daunted by the size of the task, Sevilla put out a call for volunteers, whose interviewees became the initial Epoch AI team. Together, the small group documented critical information from every significant AI model ever created. When they Published Based on their findings in early 2021, the reaction was overwhelmingly positive, with the article going viral in certain niches of the internet. Encouraged, Sevilla interrupted his doctorate, sought funding from philanthropic donorsand in April 2022 Epoch AI was born.
Since then, the organization, where Sevilla is director, has grown to 13 employees, spread across the world. Team morale is maintained through a vibrant Slack culture and occasional retreats where the small team strategizes and sings karaoke. It’s a humble operation that only became professional two years ago, but Epoch AI’s work has already been widely used by governments trying to understand the rapid progress of AI. The Government of the Netherlands’ vision on generative AI cites the work of Epoch AI, as well as a report commissioned by the UK government report which aims to synthesize evidence on the safety of advanced AI systems.
Two of the most significant efforts to put barriers around advanced AI models – the EU AI Law and President Joe Biden’s Executive Order on AI – have set a limit in terms of computing power used to train an AI model, above which stricter rules apply. Epoch AI’s database of AI models has been an invaluable resource for policymakers undertaking such efforts, says Lennart Heim, a researcher at the nonprofit think tank RAND Corporation, who was a member of Epoch AI’s founding group and still is. affiliated with the organization. “I think it’s fair to say that there is no other database in the world that is as exhaustive and rigorous.”
Epoch AI researchers now aim to go a step further, using their research into historical trends to inform predictions about the future impacts of AI. For example, in a paper Published in November 2022, Epoch AI analyzed how the amount of data fed into AI models was increasing over time and estimated how much useful data is readily available to AI developers. The researchers then pointed out that AI developers could soon run out of data unless they find new ways to power their creations. Other to study tries to predict when AI systems that, if widely available, would result in social changes comparable in magnitude to the industrial revolution – their model estimated that such an outcome has a 50% probability of occurring by 2033. This is just one model – Sevilla emphasizes Epoch AI team members’ personal predictions for such an event range from a year from now to a century from now.
See more information: When will AI be able to surpass us? Depends on who you ask
Such uncertainty underscores that despite Epoch AI’s efforts to bring rigor to the issue, there remains enormous unpredictability around how AI will impact society. Seville hopes his organization will catalyze a broader effort to resolve the issue. “We want to motivate everyone to think more rigorously about AI – to take seriously the possibility that this technology could bring dramatic changes in the coming decades,” he says, “and to try to rely on real evidence or good scientific thinking when doing so.” decisions around technology.”
This story originally appeared on Time.com read the full story
