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Smart replies, writing enhancements, and virtual assistants powered by artificial intelligence language technologies are increasingly being integrated into consumer products and everyday experiences.
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!
This session is specifically designed for full-time graduate students within one year of obtaining their PhD, as well as current postdoctoral scholars, fellows, and researchers.
This session is specifically designed for full-time graduate students within one year of obtaining their PhD, as well as current postdoctoral scholars, fellows, and researchers.
Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.
Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.
This research explores both the potential and risks of AI-mediated communication (AI-MC) technologies such as GPT-4—specifically in the political sphere—through a series of experiments designed to assess the possible uses and misuses of AI-MC. The initial part of the research evaluates whether human-AI collaboration can increase legislator responsiveness by studying citizen responses to AI-generated tweets and email correspondence. The findings point to the importance of disclosure, transparency, and human-in-the-loop accountability for AI-mediated political communication. The research then turns to the plausibility of misuse by actors seeking to influence the democratic process. It shares results from a field experiment on legislators, highlights the challenge these technologies present to democratic representation, and suggests techniques elected officials might employ to guard against AI-sourced astroturfing.
