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OpenAI claims New York Times 'hacked' ChatGPT to build copyright lawsuit
OpenAI said in a filing in Manhattan federal court on Monday that the Times caused the technology to reproduce its material through "deceptive prompts that blatantly violate OpenAI's terms of use". "The allegations in the Times's complaint do not meet its famously rigorous journalistic standards," OpenAI said. "The truth, which will come out in the course of this case, is that the Times paid someone to hack OpenAI's products." OpenAI did not name the "hired gun" whom it said the Times used to manipulate its systems and did not accuse the newspaper of breaking any anti-hacking laws. Representatives for the New York Times and OpenAI did not immediately respond to requests for comment on the filing. The Times sued OpenAI and its largest financial backer, Microsoft, in December, accusing them of using millions of its articles without permission to train chatbots to provide information to users.
Bias of AI-Generated Content: An Examination of News Produced by Large Language Models
Fang, Xiao, Che, Shangkun, Mao, Minjia, Zhang, Hongzhe, Zhao, Ming, Zhao, Xiaohang
Large language models (LLMs) have the potential to transform our lives and work through the content they generate, known as AI-Generated Content (AIGC). To harness this transformation, we need to understand the limitations of LLMs. Here, we investigate the bias of AIGC produced by seven representative LLMs, including ChatGPT and LLaMA. We collect news articles from The New York Times and Reuters, both known for their dedication to provide unbiased news. We then apply each examined LLM to generate news content with headlines of these news articles as prompts, and evaluate the gender and racial biases of the AIGC produced by the LLM by comparing the AIGC and the original news articles. We further analyze the gender bias of each LLM under biased prompts by adding gender-biased messages to prompts constructed from these news headlines. Our study reveals that the AIGC produced by each examined LLM demonstrates substantial gender and racial biases. Moreover, the AIGC generated by each LLM exhibits notable discrimination against females and individuals of the Black race. Among the LLMs, the AIGC generated by ChatGPT demonstrates the lowest level of bias, and ChatGPT is the sole model capable of declining content generation when provided with biased prompts.
New York Times op-ed says population decline may make 'climate change easier to combat'
During an appearance on "Fox and Friends First", Jimmy Failla shares his thoughts on Vice President Kamala Harris jet-setting to an event in Buffalo, York which focused on the Biden administration's green agenda. A New York Times newsletter published an article by staff editor Spencer Bokat-Lindell arguing that declining fertility rates and a shrinking population could be a good thing to help the world combat climate change. The article, titled "U.S. Population Growth Has Nearly Flatlined. Is That So Bad?", speculated that population decline may "actually bring welcome changes." "For a population to replenish itself in the absence of immigration, demographers estimate that there must be, on average, about 2.1 births per woman," Bokat-Lindell noted while pointing out that in the United States, the fertility rate has been below that since 2007.