Arvind Narayanan, Professor of Computer Science, Princeton University
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Arvind Narayanan, Professor of Computer Science, Princeton University
Arvind Narayanan is a professor of computer science at Princeton and the director of the Center for Information Technology Policy. He co-authored a textbook on fairness and machine learning and is currently co-authoring a book on AI snake oil. He led the Princeton Web Transparency and Accountability Project to uncover how companies collect and use our personal information. His work was among the first to show how machine learning reflects cultural stereotypes, and his doctoral research showed the fundamental limits of de-identification. Narayanan is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE), twice a recipient of the Privacy Enhancing Technologies Award.
Princeton University’s Arvind Narayanan is an associate professor of computer science. He oversees the Princeton Web Transparency and Accountability Project, which aims to expose the methods used by businesses to gather and utilize our personal data. Over 150 courses across the world use the textbook and Massive Open Online Course on Bitcoin and cryptocurrency technology that Narayanan co-wrote. His dissertation study revealed the basic limitations of de-identification, and his latest work has demonstrated how machine learning reflects cultural preconceptions. Narayanan has won three awards: the Privacy Papers for Policy Makers Award three times, the Privacy Enhancing Technologies Award twice, and the Presidential Early Career Award for Scientists and Engineers (PECASE).
2023
Princeton starts a new program centered on large language models amid the AI boom. A recently launched Princeton effort seeks to attract expertise and allocate funds for the advancement of artificial intelligence (AI) in the fields of academia and research.
The Princeton Language and Intelligence Initiative (PLI) aims to investigate the societal and ethical implications of artificial intelligence (AI) and devise strategies to prevent any negative effects. The website states that PLI “seeks to develop fundamental understanding of large AI models; enable their application to research and education across academic disciplines.” Apart from serving as a platform for interdisciplinary collaboration between students, researchers, and teachers, PLI will also endeavor to establish a resilient local computer infrastructure, complete with its own staff and equipment.
A South Korea Central Bank study suggests AI could replace up to 4 million jobs, accounting for 14% of the country’s workforce, in the next two decades. Higher-income individuals and those with strong academic backgrounds are at risk. AI will increase demand for STEM disciplines, but also threaten knowledge work and improve productivity.
Latest Social posts of Arvind Narayanan
Thread on the double-edged nature of chatbots for learning. It definitely requires a strong understanding of their limitations. https://t.co/eI16J5fNTf
I use GPT-4 for all kinds of research assistance but writing seems to be one task for which it is worse than useless. It can't handle an original idea and usually rewrites it into insipid verbiage, presumably an averaged out version of stuff it's seen in training. https://t.co/HbpQV5Urpm
We must prepare for a world in which unaligned models exist, either because threat actors trained them from scratch or because they modified an existing model. We must instead look to defend the attack surfaces that attackers might target using such models https://t.co/Y8xdhnEumR
