With that sentence, written by the journalist Samantha Cole for the tech site Motherboard in December, 2017, a queasy new chapter in our cultural history opened. A programmer calling himself "deepfakes" told Cole that he'd used artificial intelligence to insert Gadot's face into a pornographic video. And he'd made others: clips altered to feature Aubrey Plaza, Scarlett Johansson, Maisie Williams, and Taylor Swift. Porn, as a Times headline once proclaimed, is the "low-slung engine of progress." It can be credited with the rapid spread of VCRs, cable, and the Internet--and with several important Web technologies.

University of Notre Dame researchers are developing a neural network to read ancient handwriting based on human perception to enhance deep learning transcription. Notre Dame's Walter Scheirer says the documents are written in archaic languages and long-unused styles dating back centuries. The project aims "to automate transcription in a way that mimics the perception of the page through the eyes of the expert reader and provides a quick, searchable reading of the text," he says. Scheirer's team combined traditional machine learning techniques with visual psychophysics, the measurement of links between physical stimuli and mental phenomena. They studied digitized ninth-century Latin manuscripts written by scribes in Switzerland's Cloister of St. Gall, with readers inputting manual transcriptions into a software interface while their reaction times were measured.

The Abbey Library of St. Gall in Switzerland is home to approximately 160,000 volumes of literary and historical manuscripts dating back to the eighth century--all of which are written by hand, on parchment, in languages rarely spoken in modern times. To preserve these historical accounts of humanity, such texts, numbering in the millions, have been kept safely stored away in libraries and monasteries all over the world. A significant portion of these collections are available to the general public through digital imagery, but experts say there is an extraordinary amount of material that has never been read--a treasure trove of insight into the world's history hidden within. Now, researchers at University of Notre Dame are developing an artificial neural network to read complex ancient handwriting based on human perception to improve capabilities of deep learning transcription. "We're dealing with historical documents written in styles that have long fallen out of fashion, going back many centuries, and in languages like Latin, which are rarely ever used anymore," said Walter Scheirer, the Dennis O. Doughty Collegiate Associate Professor in the Department of Computer Science and Engineering at Notre Dame.

Researchers at the University of Notre Dame are using artificial intelligence to develop an early warning system that will identify manipulated images, deepfake videos and disinformation online. The project is an effort to combat the rise of coordinated social media campaigns to incite violence, sew discord and threaten the integrity of democratic elections. The scalable, automated system uses content-based image retrieval and applies computer vision-based techniques to root out political memes from multiple social networks. "Memes are easy to create and even easier to share," said Tim Weninger, associate professor in the Department of Computer Science and Engineering at Notre Dame. "When it comes to political memes, these can be used to help get out the vote, but they can also be used to spread inaccurate information and cause harm."