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This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
This seminar pairs a case study of AI diffusion with an organizational approach to technological changes in the workplace.
As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.
As AI moves beyond language into systems that can perceive, understand, and act in the physical world, a new frontier is emerging: world models—AI systems that build and maintain working representations of real environments to predict how they change in response to action.
Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.
Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.
Watch live!
This Symposium hosted by the U.S. Department of Commerce and National Institute of Standards and Technology, Stanford Institute for Human-Centered Artificial Intelligence (HAI), and the FinRegLab, will bring together leaders from government, industry, civil society, and academia to explore potential opportunities and challenges posed by artificial intelligence and machine learning deployment across different economic sectors, with a particular focus on financial services and healthcare.
The event is designed to address how these technologies relate to ensuring inclusive economic growth, supporting financial inclusion, and mitigating risks such as bias and unfairness. It will feature presenters and panelists on the cutting edge of researching fairness and explainability in AI, as well as those working to develop policies and frameworks to evaluate and assess the goals of improving the trustworthiness, inclusiveness, and equity of AI deployment.
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