REIsearch NEWS

30/03/2019

New AI fake text generator may be too dangerous to release, say creators

The Guardianc reports the creators of a revolutionary AI system that can write news stories and works of fiction – dubbed “deepfakes for text” – have taken the unusual step of not releasing their research publicly, for fear of potential misuse. OpenAI, an nonprofit research company backed by Elon Musk, Reid Hoffman, Sam Altman, and others, says its new AI model, called GPT2 is so good and the risk of malicious use so high that it is breaking from its normal practice of releasing the full research to the public in order to allow more time to discuss the ramifications of the technological breakthrough. At its core, GPT2 is a text generator. The AI system is fed text, anything from a few words to a whole page, and asked to write the next few sentences based on its predictions of what should come next. The system is pushing the boundaries of what was thought possible, both in terms of the quality of the output, and the wide variety of potential uses. When used to simply generate new text, GPT2 is capable of writing plausible passages that match what it is given in both style and subject. It rarely shows any of the quirks that mark out previous AI systems, such as forgetting what it is writing about midway through a paragraph, or mangling the syntax of long sentences. The amount of data GPT2 was trained on directly affected its quality, giving it more knowledge of how to understand written text. It also led to the second breakthrough. GPT2 is far more general purpose than previous text models. By structuring the text that is input, it can perform tasks including translation and summarisation, and pass simple reading comprehension tests, often performing as well or better than other AIs that have been built specifically for those tasks. That quality, however, has also led OpenAI to go against its remit of pushing AI forward and keep GPT2 behind closed doors for the immediate future while it assesses what malicious users might be able to do with it. “We need to perform experimentation to find out what they can and can’t do,” said Jack Clark, the charity’s head of policy. “If you can’t anticipate all the abilities of a model, you have to prod it to see what it can do. There are many more people than us who are better at thinking what it can do maliciously.”  

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