More than a year ago, as the spread of COVID locked down NYC and medical education moved online, VP&S students in APAMSA the Asian Pacific American Medical Students Association found themselves grappling with yet another challenge: a rise in anti-Asian discrimination and bias.
APAMSA co-presidents Hueyjong Shih and Jingwen Zhang were a few months into medical school at the time.
Fellow VP&S medical students who identify as Asian American Pacific Islander (AAPI) were uncertain about where to turn and confided in Shih and Zhang about incidents of racism ranging from verbal harassment and shunning on the subway to microaggressions during their clinical experiences (Zhang wrote candidly about her experiences for Ms. Magazine).
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Researchers test detection methods for AI-generated content
Is the news you’re reading online generated by a human or by artificial intelligence? College of Information Sciences and Technology researchers analyzed eight different state-of-the-art natural language generators (NLG) to identify whether each had a distinct writing style that could be discovered by machine classifiers in an effort to expose security threats they may introduce.
Image: Adobe Stock: Rawpixel Ltd.
Artificial intelligence generators can craft text that mimics a human author, improving the user experience in platforms such as medical chatbots, online customer service and virtual psychotherapy sessions.
Often times, these realistic texts are difficult to distinguish from those generated by humans. But as these techniques become more sophisticated and prevalent, so do the opportunities for fraudulent use.