Sayash Kapoor, Professor & Doctoral Candidate, Princeton University
Kapoor is a Ph.D. candidate at Princeton University’s Center for Information Technology Policy. His research critically investigates machine learning methods and their use in science and has been featured in WIRED, the Los Angeles Times, and Nature, among other media outlets. At Princeton, Kapoor organized The Reproducibility Crisis in ML-based Science, a workshop that saw more than 1,700 registrations. He has worked on machine learning in several institutions and academia, including Facebook, Columbia University, and EPFL Switzerland.
Kapoor is a doctoral candidate at the Center for Information Technology Policy at Princeton University. Among other media venues, his study has been covered in WIRED, the Los Angeles Times, and Nature. It critically examines machine learning techniques and their use in science. More than 1,700 people registered for Kapoor’s workshop, The Reproducibility Crisis in ML-based Science, at Princeton. He has experience in academia and several organizations, such as Facebook, Columbia University, and EPFL Switzerland, where he has worked on machine learning. He received an Impact Recognition award from ACM CSCW and a Best Paper Award from ACM FAccT.
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 Sayash Kapoor
Humans in the loop are not enough to fix algorithms. When push comes to shove, companies choose profits over people.
The latest example: UnitedHealth forced employees to cut off care based on an algorithm's prediction. If they disagree, they're fired.https://t.co/m75rUmlgUT
Foundation models have profound societal impact, but transparency about these models is waning. Today, we are launching the Foundation Model Transparency Index, which offers a deep dive into the transparency practices and standards of key AI developers.https://t.co/B7b5Z71EjXpic.twitter.com/JXBeaQHqnX
