Maryland Today: How AI Could Help Writers Spot Stereotypes

Maryland Today: How AI Could Help Writers Spot Stereotypes. “Studious Asians, sassy yet helpless women and greedy shopkeepers: These tired stereotypes of literature and film not only often offend the people they caricature, but can drag down what might otherwise have been a compelling narrative. Researchers at the University of Maryland’s Human-Computer Interaction Lab are working to combat these clichés with the creation of DramatVis Personae (DVP), a web-based visual analytics system powered by artificial intelligence that helps writers identify stereotypes they might be unwittingly giving fictional form among their cast of characters (or dramatis personae).”

Mashable: Virtual rapper FN Meka underscores how AI perpetuates racial stereotyping

Mashable: Virtual rapper FN Meka underscores how AI perpetuates racial stereotyping. “On Aug. 12, AI-powered rapper FN Meka signed a record deal with Capitol Records, becoming the first digital artist to sign with a major label. Eleven days later, the deal was terminated amidst calls that the character promoted ‘gross stereotypes’ of Black culture, as reported by the New York Times.” There are so many great rappers out there who don’t get enough recommendation. Why make a fake one?

The Drum: How Dove, Getty Images and Girl Gaze united to create a commercial image bank featuring real women

The Drum: How Dove, Getty Images and Girl Gaze united to create a commercial image bank featuring real women. “Dove recently partnered with Getty Images and Girl Gaze to create Project #ShowUs, the world’s first inclusive picture library of women in order to break beauty stereotypes. 900 global companies have gone on to use the resource, but launching it was not without its challenges.”

University of Pennsylvania: Penn Psychologists Tap Big Data, Twitter to Analyze Accuracy of Stereotypes

University of Pennsylvania: Penn Psychologists Tap Big Data, Twitter to Analyze Accuracy of Stereotypes. “What’s in a tweet? People draw conclusions about us, from our gender to education level, based on the words we use on social media. Researchers from the University of Pennsylvania, along with colleagues from the Technical University of Darmstadt and the University of Melbourne, have now analyzed the accuracy of those inferences. Their work revealed that, though stereotypes and the truth often aligned, with people making accurate assumptions more than two-thirds of the time, inaccurate characterizations still showed up.”