Terminator Economy
The "Terminator Economy" refers to research exploring the impact of advanced artificial intelligence (AI), particularly large language models (LLMs), on the job market and related tasks. Current research focuses on quantifying job exposure to AI-driven automation using data-driven frameworks and indices, often employing matrix and tensor factorization techniques for efficient model compression and analysis of large datasets. This work is significant for understanding the potential societal and economic transformations driven by AI, informing policy decisions, and guiding the development of AI systems that augment rather than replace human capabilities.
Papers
Dynamic Collaborative Filtering for Matrix- and Tensor-based Recommender Systems
Albert Saiapin, Ivan Oseledets, Evgeny Frolov
A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia
Giovanni Monea, Maxime Peyrard, Martin Josifoski, Vishrav Chaudhary, Jason Eisner, Emre Kıcıman, Hamid Palangi, Barun Patra, Robert West