The latest AI Experts news
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Arvind Narayanan
Description: Arvind Narayanan is a computer scientist and associate professor at Princeton University. Narayanan is recognized for his research on data de-anonymization. Arvind said he wanted a browser extension that replaces circuit brains, humanoid robots, and all the other gruesome imagery in AI news articles with images of regression lines. Arvind has an excellent AI engagement rate which makes him a fixture in AI news. -
Solon Barocas
Description: Principal Researcher in the New York City lab of Microsoft Research and Professor in the Department of Information Science at Cornell University. He is also a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University.His research explores ethical and policy issues in artificial intelligence, particularly fairness in machine learning, methods for bringing accountability to automated decision-making, and the privacy implications of inference. He co-founded the annual workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) and later established the ACM conference on Fairness, Accountability, and Transparency (FAccT). -
Sergey Levine
Description: Sergey is a professor in the Department of Electrical Engineering and Computer Science at UC Berkeley. In his research, he focuses on the intersection between control and machine learning, with the aim of developing algorithms and techniques capable of equipping machines with the ability to autonomously acquire the skills necessary to perform tasks. complex tasks. He is interested in how learning can be used to acquire complex behavioral skills, in order to endow machines with greater autonomy and intelligence. He thinks in particular that the notions of perception and control are key concepts to obtain robots with behavior similar to humans. -
Jurgen Schmidhuber
Description: Very early on, Professor Jürgen Schmidhuber's goal was to build a self-improving artificial intelligence (AI) smarter than him, and then to retire. The deep learning neural networks in his lab have revolutionized machine learning and AI. It has helped improve speech recognition on all Android phones. It has also helped make machine translation more efficient through Google Translate and Apple's Facebook, Siri and Quicktype on all iPhones, as well as Amazon's Alexa. His team were the first to win official computer vision competitions using deep neural networks, with superhuman performance. In 2012, they had the first deep neural network to win a medical imaging competition. He introduced unsupervised opposing neural networks that fight each other in a minimax game to achieve artificial curiosity. He now aims to create the first practical general-purpose AI. AI expert Gary Marcus says thanks to Jürgen the community is starting to pay more attention to neurosymbolic approaches to AI -
Jascha Sohl-Dickstein
Description: Jascha is a senior research scientist in the Google Brain group, where he leads a research team whose interests span machine learning, physics and neuroscience. His recent work is focused on the theory of over-parameterized neural networks, the meta-training of learning optimizers and the understanding of the capacities of large language models. Previously, he was a visiting scholar in Surya Ganguli's lab at Stanford University and an academic resident at Khan Academy. He is very concerned with the field on social networks, currently having the highest AI engagement rate measured by Cafiac in the community of AI Experts. It solicits contributions from tasks to a collaborative benchmark designed to measure and extrapolate the capabilities and limitations of large language models. -
Niloufar Salehi
Description: Niloufar Salehi is an Assistant Professor at the School of Information at UC, Berkeley. Her research interests are in social computing, technologically mediated collective action, digital labor, and computer supported cooperative work. Her work has been published and received awards in first venues in human-computer interaction including CHI and CSCW. Through building computational social systems in collaboration with existing communities, controlled experiments, and ethnographic fieldwork, her research contributes the design of alternative social configurations online. -
Veena Dubal
Description: Law professor Veena Dubal's research focuses on the intersection of law, technology and precarious work. Within this broad framework, she uses empirical methodologies and critical theory to understand the impact of digital technologies and emerging legal frameworks on the lives of workers, the co-constitutive influences of law and labor on identity, and finally the role of law and lawyers in solidarity movements. She believes that while Apple says privacy is a "basic human right," these privacy concerns do not apply to the workers who make its products. -
Tom Simonite
Description: Tom is the San Francisco bureau chief of the MIT Technology Review. Prior to his current role at WIRED, he was a technology journalist at New Scientist. He closely follows the events that stir up the news of GAFA, particularly around ethical questions. -
Shalini Kantayya
Description: Shalini Kantayya is an American filmmaker and environmental activist based out of Brooklyn, New York whose films explore human rights at the intersection of water, food, and renewable energy. Shes is well known in the AI community as she was the Director of Coded Bias which is an a documentary film that premiered at the 2020 Sundance Film Festival The documentary follows researchers and advocates, principally MIT computer scientist Joy Buolamwini, as they explore how algorithms encode and propagate bias -
Kareem Carr
Description: Kareem has always had a wide and eclectic interest in the use of calculus and mathematics for science. Kareem worked as a bioinformatician at Harvard and a computational biologist at the Broad Institute and concurrently, a data science consultant at the Harvard Institute for Quantitative Social Sciences, where he participated in over 100 social science projects and taught programming workshops. to Harvard and MIT students. His main research interest is the role of statistics in the production of knowledge. He thinks it's useful to distinguish between reproducibility (the science of it) and replicability (the resulting digital software). He is very involved in the debates related to AI on the internet, in particular with the experts Judea Pearl and Danilo Bzdok.