OpenAI Says Russia and China Used Its A.I. in Covert Campaigns
- OpenAI said on Thursday that it had identified and disrupted five online campaigns that used its generative artificial intelligence technologies to deceptively manipulate public opinion around the world and influence geopolitics.
- The efforts were run by state actors and private companies in Russia, China, Iran and Israel, OpenAI said in a report about covert influence campaigns. The operations used OpenAI’s technology to generate social media posts, translate and edit articles, write headlines and debug computer programs, typically to win support for political campaigns or to swing public opinion in geopolitical conflicts.
Once a Sheriff’s Deputy in Florida, Now a Source of Disinformation From Russia (AI tools)
- With the help of commercially available artificial intelligence tools, including OpenAI’s ChatGPT and DALL-E 3, he has filled the sites with tens of thousands of articles, many based on actual news events. Interspersed among them are also bespoke fabrications that officials in the United States and European Union have attributed to Russian intelligence agencies or the administration of President Vladimir V. Putin.
Fake News Reports and Videos Seek to Undermine the Paris Olympics (More traditional active measures)
- Microsoft estimates that Storm-1679 produces three to eight faked videos a week, in English and French, with many impersonating the BBC, Al Jazeera and other broadcasters. The group appears to respond quickly to news events, like protests in New Caledonia, a French territory in the Pacific. Others focus on the prospect of a terrorist attack in Paris.
Why this year’s election interference could make 2016 look cute
- For more than a year, FBI Director Christopher A. Wray has warned about a wave of election interference that could make 2016 look cute. No respectable foreign adversary needs an army of human trolls in 2024. AI can belch out literally billions of pieces of realistic-looking and sounding misinformation about when, where and how to vote. It can just as easily customize political propaganda for any individual target. In 2016, Brad Parscale, Donald Trump’s digital campaign director, spent endless hours customizing tiny thumbnail campaign ads for groups of 20 to 50 people on Facebook. It was miserable work but an incredibly effective way to make people feel seen by a campaign. In 2024, Brad Parscale is software, available to any chaos agent for pennies. There are more legal restrictions on ads, but AI can create fake social profiles and aim squarely for your individual feed. Deepfakes of candidates have been here for months, and the AI companies keep releasing tools that make all of this material faster and more convincing.
Mapping the Increasing Use of LLMs in Scientific Papers
- Scientific publishing lays the foundation of science by disseminating research findings, fostering collaboration, encouraging reproducibility, and ensuring that scientific knowledge is accessible, verifiable, and built upon over time. Recently, there has been immense speculation about how many people are using large language models (LLMs) like ChatGPT in their academic writing, and to what extent this tool might have an effect on global scientific practices. However, we lack a precise measure of the proportion of academic writing substantially modified or produced by LLMs. To address this gap, we conduct the first systematic, large-scale analysis across 950,965 papers published between January 2020 and February 2024 on the arXiv, bioRxiv, and Nature portfolio journals, using a population-level statistical framework to measure the prevalence of LLM-modified content over time. Our statistical estimation operates on the corpus level and is more robust than inference on individual instances. Our findings reveal a steady increase in LLM usage, with the largest and fastest growth observed in Computer Science papers (up to 17.5%). In comparison, Mathematics papers and the Nature portfolio showed the least LLM modification (up to 6.3%). Moreover, at an aggregate level, our analysis reveals that higher levels of LLM-modification are associated with papers whose first authors post preprints more frequently, papers in more crowded research areas, and papers of shorter lengths. Our findings suggests that LLMs are being broadly used in scientific writings.
SBIRs
- Submitted the MORS presentation
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