With the increasing awareness of AI, especially generative AI, machine learning and AI are presenting new challenges for data governance in companies ranging from online service providers to retail. Generative AI can be considered a category of artificial intelligence that “generate[s] new outputs based on the data they have been trained on.” Large Language Models (LLMs) are machine learning models that are trained to process large amounts of data to generate natural language.

In the Future of Privacy Forum’s training, Fundamentals of AI & Machine Learning, participants will learn about the current state of ML &AI, explore the associated opportunities and challenges, data governance considerations, as well as sector specific applications.

Learning objectives for Fundamentals of AI & ML training session:

What are machine learning and AI, from supervised learning to neural networks and reinforcement learning.
How “generative AI” and Large Language Models (LLMs) are used and their implications
Understand the impact of data collection, labeling, and use on the performance of ML & AI systems
Appreciate the types of bias, harms, and the range of possibilities in AI systems for bias to occur

This training will be a live virtual session.

Your Fundamentals of AI & ML Training Faculty:

Emily McReynolds, Data and Policy Expert

Emily has worked in data protection, machine learning & AI, across academia, civil society, and in the tech industry. At Meta, on the AI Policy team in the Privacy & Data Policy group, she led stakeholder engagement on responsible AI and co-authored documentation projects System Cards, Method Cards, and data collection/labeling for AI with Casual Conversations v2. Before Meta at Microsoft, she led end-to-end data strategy from developing a dataset risk framework to the implementation of Responsible AI Standard at Microsoft Research. During her years as the program director for the University of Washington’s Tech Policy Lab, an interdisciplinary collaboration across the CS, Information, and Law schools, she co-led projects on augmented reality, driverless cars, and Toys That Listen. Emily went to graduate school planning to work on tech policy and previously taught people to use computers back when there were still floppy disks.

FPF Training: Fundamentals of AI & ML | September 28, 2023