CSET's Josh A. Goldstein was recently quoted in a WIRED article about state-backed hacking groups using fake LinkedIn profiles to steal information from their targets. Goldstein provides insight by highlighting the issues in the disinformation space.
An article published in OODA Loop cited a report by CSET's Josh Goldstein, Micah Musser, and CSET alumna Katerina Sedova in collaboration with OpenAI and Stanford Internet Observatory. The report explores the potential misuse of language models for influence operations in the future, and provides a framework for assessing mitigation strategies.
BBC News cited a report authored by CSET's Josh Goldstein, Micah Musser, and CSET alumna Katerina Sedova in partnership with OpenAI and Stanford Internet Observatory. Alongside the report, BBC News quoted Josh Goldstein regarding the current status of AI systems.
WIRED highlighted CSET Research Analyst Micah Musser in an article that references a report published by CSET, in collaboration with OpenAI and Stanford Internet Observatory. The report examines the potential misuse of language models in influence operations in the future and offers a framework for evaluating potential countermeasures.
A report by CSET's Josh Goldstein, Micah Musser, and CSET alumna Katerina Sedova in collaboration with OpenAI and Stanford Internet Observatory was cited in an article published by The New York Times about the potential dangers of AI-powered chatbots.
A report by CSET's Josh Goldstein, Micah Musser, and CSET alumna Katerina Sedova in collaboration with OpenAI and Stanford Internet Observatory was cited in an article published by Grid. The report examines the potential misuse of language models for influence operations in the future and proposes a structure for evaluating possible solutions to this problem.
A report by CSET’s Josh Goldstein, Micah Musser, and CSET alumna Katerina Sedova in collaboration with OpenAI and Stanford Internet Observatory was cited in an article published on Medium. The report explores how language models could be misused for influence operations in the future, and it provides a framework for assessing potential mitigation strategies.
Josh A. Goldstein, Girish Sastry, Micah Musser, Renée DiResta, Matthew Gentzel, and Katerina Sedova
| January 2023
Machine learning advances have powered the development of new and more powerful generative language models. These systems are increasingly able to write text at near human levels. In a new report, authors at CSET, OpenAI, and the Stanford Internet Observatory explore how language models could be misused for influence operations in the future, and provide a framework for assessing potential mitigation strategies.
In an interview with CyberScoop, Research Fellow Josh A. Goldstein discussed his research, in collaboration with Open AI and Stanford's Internet Observatory, on the use of large language models to deploy propaganda.
Artificial intelligence offers enormous promise to advance progress and powerful capabilities to disrupt it. This policy brief is the second installment of a series that examines how advances in AI could be exploited to enhance operations that automate disinformation campaigns. Building on the RICHDATA framework, this report describes how AI can supercharge current techniques to increase the speed, scale, and personalization of disinformation campaigns.
This website uses cookies.
To learn more, please review this policy. By continuing to browse the site, you agree to these terms.
This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.