HAI Weekly Seminar with Lisa Simon
The Future of Work and How the Workforce Adapts to Change
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The Future of Work and How the Workforce Adapts to Change
The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced computational methods.

The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced computational methods.
This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!
The labor market is changing ever more rapidly, and with that, the pressure to adapt and evolve has increased on everyone, One of the main drivers of change is technological progress, with technologies such as robots, software or AI fundamentally changing how work gets done and by whom. Automation both replaces certain tasks that humans used to do, and more importantly changes the required skills in occupations that are adapting new technologies. This presentation will draw on my research that sheds light on how individual adapt to change on the labor market. I explore how individuals transition between different career pathways and how they react, when faced with negative shocks. Knowing who can adapt to change and who may need help, provides important policy implications for the future of work. The research presented uses data spanning Europe and the US as well as state-of-the art empirical methods, including machine learning.
