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alt="The “Faces in Things” dataset is a comprehensive, human-labeled collection of over 5,000 pareidolic images. The research team trained face-detection algorithms to see faces in these pictures, giving insight into how humans learned to recognize faces within their surroundings (Credits: Alex Shipps/MIT CSAIL)."
CSAIL article

In 1994, Florida jewelry designer Diana Duyser discovered what she believed to be the Virgin Mary’s image in a grilled cheese sandwich, which she preserved and later auctioned for $28,000. But how much do we really understand about pareidolia, the phenomenon of seeing faces and patterns in objects when they aren’t really there? 

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A system developed by MIT CSAIL researchers can oversee a team of both human and AI agents, communicating with team members to align roles and accomplish a common goal (Credits: Alex Shipps/MIT CSAIL).
CSAIL article

On a research cruise around Hawaii in 2018, Yuening Zhang SM ’19, PhD ’24 saw how difficult it was to keep a tight ship. The careful coordination required to map underwater terrain could sometimes led to a stressful environment for team members, who might have different understandings of which tasks must be completed in spontaneously changing conditions. During these trips, Zhang considered how a robotic companion could have helped her and her crewmates achieve their goals more efficiently.

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“Personhood credentials allow you to prove you are human without revealing anything else about your identity,” says Tobin South (Credits: MIT News; iStock).
CSAIL article

As artificial intelligence agents become more advanced, it could become increasingly difficult to distinguish between AI-powered users and real humans on the internet. In a new white paper, researchers from MIT, OpenAI, Microsoft, and other tech companies and academic institutions propose the use of personhood credentials, a verification technique that enables someone to prove they are a real human online, while preserving their privacy.