Computer Science

Real or fake text? We can learn to spot the difference

Penn computer scientists prove that people can be trained to tell the difference between AI-generated and human-written text. Their new paper debuts the results of the largest-ever human study on AI detection.

From Penn Engineering Today

PIK Professor Kevin Johnson named University Professor

Kevin Johnson, who has appointments in the Perelman School of Medicine and the School of Engineering and Applied Science, and a secondary appointment in the Annenberg School for Communication, will become the David L. Cohen University Professor.

Katherine Unger Baillie



In the News


Philadelphia Inquirer

New Penn AI master’s program aims to prep students for ‘jobs that we can’t yet imagine’

Chris Callison-Burch of the School of Engineering and Applied Science discusses Penn’s new online master’s program in artificial intelligence.

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The Observer

The University of Pennsylvania is the first Ivy to offer an AI master’s

The School of Engineering and Applied Science has announced its first master’s degree in artificial intelligence, led by Chris Callison-Burch.

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Technical.ly Philly

Penn Engineering rolls out an online master’s degree in AI, first in Ivy League

The School of Engineering and Applied Science has announced the first graduate program in artificial intelligence among Ivy League universities, led by Chris Callison-Burch.

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NBC Philadelphia

Penn Engineering announces first Ivy League Master’s degree in AI

The School of Engineering and Applied Science has announced the first graduate program in artificial intelligence among Ivy League universities, led by Chris Callison-Burch.

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Technical.ly Philly

Penn professor on gen AI’s rapacious use of energy: ‘One of the defining challenges of my career’

Benjamin Lee of the School of Engineering and Applied Science says that hardware and infrastructure costs are growing at high rates for generative AI.

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Big Think

Can we stop AI hallucinations? And do we even want to?

Chris Callison-Burch of the School of Engineering and Applied Science says that auto-regressive generation can make it difficult for language learning models to perform fact-based or symbolic reasoning.

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