Artificial Intelligence (AI) is a term coined in 1955 by John McCarthy, Stanford's first faculty member in AI, who described it as "the science and engineering of making intelligent machines." Today it is a broad term for computer systems that can perform tasks with human-like intelligence, such as understanding language, recognizing images, learning from data, reasoning, and making decisions. Modern AI often works by finding patterns in large amounts of data and using those patterns to generate predictions or responses. It can be narrow (good at a specific task) or more general-purpose, like today’s large language models that can handle many tasks.
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Machine Learning (ML) | AGI (Artificial General Intelligence) | Deep Learning

The new center will examine AI's real-world impacts on jobs, teams, and organizational performance.
The new center will examine AI's real-world impacts on jobs, teams, and organizational performance.


This brief demonstrates how real-time monitoring can address critical gaps in the oversight of radiological AI tools.
This brief demonstrates how real-time monitoring can address critical gaps in the oversight of radiological AI tools.


More than 200 academic teams submitted proposals to the AI for Organizations Grand Challenge, exploring how artificial intelligence will transform teamwork and collaboration.
More than 200 academic teams submitted proposals to the AI for Organizations Grand Challenge, exploring how artificial intelligence will transform teamwork and collaboration.


This brief examines the privacy risks foundation models pose to individuals and society, and governance mechanisms needed to address them.
This brief examines the privacy risks foundation models pose to individuals and society, and governance mechanisms needed to address them.

HAI Executive Director Russell Wald talks about the AI competition between the U.S. and China, and the advent of “world models” that predict what might happen in real-world environments.
HAI Executive Director Russell Wald talks about the AI competition between the U.S. and China, and the advent of “world models” that predict what might happen in real-world environments.

This white paper analyzes the varying ways AI tools can advance language digitization work, and provides recommendations for responsibly realizing the potential of AI in supporting the digital inclusion of digitally disadvantaged languages.
This white paper analyzes the varying ways AI tools can advance language digitization work, and provides recommendations for responsibly realizing the potential of AI in supporting the digital inclusion of digitally disadvantaged languages.
