HAI Privacy and Data Policy Fellow Jennifer King provides insight into the data used to train large language models, and the risks these foundation models pose to everyone’s privacy.
It’s time for a shared, value-neutral way of talking about AI’s risks and opportunities, with policymaker education like HAI’s recent AI Boot Camp being a good start.
HAI’s “Advancing Technology for a Sustainable Planet" conference highlighted the concerns about the environmental impact of AI along with proposed solutions for how regulation might help.
Percy Liang, Director of HAI’s Center for Research on Foundation Models, says what’s needed are broader community standards to guide research and decisions.
“Whether it’s an AI tool or whether it’s a person making that suggestion, there’s an art to that data communication,” says HAI Faculty Affiliate Danton Char.
CRFM Director Percy Liang explains the urgent need to develop community norms that guarantee research access and help guide the future of AI responsibly.
Erik Brynjolfsson, Senior Fellow at HAI and Director of the Stanford Digital Economy Lab, says that “having an AI pretend to be sentient is going to happen way before an AI is actually sentient.”
Following HAI's 2021 launch of the Center for Research on Foundation Models and the term "foundation models" itself, this Economist special series on foundation models explores the opportunities and risks, and what it means for the future of AI.
Erik Brynjolfsson, director of the Stanford Digital Economy Lab within HAI, remains optimistic that the tidal wave of transformation from AI will increase productivity.
Percy Liang, director of Stanford HAI’s Center for Research on Foundation Models, comments on the power and risks of large-scale AI models such as Google’s LaMDA.
