6/1/2023 0 Comments Mist recent menu d spot![]() The Objective: Introduce the brand-new Signal Spectre full-suspension, full-carbon bike via a high-risk eight-day launch on the biggest stage of all. ![]() ![]() “Generated texts, like those produced by ChatGPT, begin with human-provided prompts. The Challenge: Complete the 2023 Absa Cape Epic, the toughest MTB stage race in the world, with an eye on the prize in the new Working Class Hero Category. “Our method not only gamifies the task, making it more engaging, it also provides a more realistic context for training,” says Dugan. The study results show that participants scored significantly better than random chance, providing evidence that AI-created text is, to some extent, detectable. Trainees identify and describe the features of the text that indicate error and receive a score. Each example then transitions into generated text, asking participants to mark where they believe this transition begins. The Penn model significantly refines the standard detection study into an effective training task by showing examples that all begin as human-written. This task involves simply classifying a text as real or fake and responses are scored as correct or incorrect. In standard methods, participants are asked to indicate in a yes-or-no fashion whether a machine has produced a given text. This training game is notable for transforming the standard experimental method for detection studies into a more accurate recreation of how people use AI to generate text. The study uses data collected using Real or Fake Text?, an original web-based training game. Over time, given enough examples and explicit instruction, we can learn to pick up on the types of errors that machines are currently making.” “People start with a certain set of assumptions about what sort of errors a machine would make, but these assumptions aren’t necessarily correct. “We’ve shown that people can train themselves to recognize machine-generated texts,” says Callison-Burch. The study, led by Chris Callison-Burch, associate professor in the Department of Computer and Information Science (CIS), along with Liam Dugan and Daphne Ippolito, students in CIS, provides evidence that AI-generated text is detectable. In a peer-reviewed paper, the authors demonstrate that people can learn to spot the difference between machine-generated and human-written text.īefore you choose a recipe, share an article, or provide your credit card details, it’s important to know there are steps you can take to discern the reliability of your source. These new tools raise society-wide concerns about artificial intelligence’s role in reinforcing social biases, committing fraud and identity theft, generating fake news, spreading misinformation and more.Ī team of researchers at Penn’s School of Engineering and Applied Science is seeking to empower tech users to mitigate these risks. Yet while apprehensions about employment and schools dominate headlines, the truth is that the effects of large-scale language models such as ChatGPT will touch virtually every corner of our lives.
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