FPF Training Program:
Building a Responsible AI Program

June 18 | 1PM - 3PM ET

Overview

FPF’s Training Program provides an in-depth understanding of today’s most pressing privacy and data protection topics. FPF staff experts design the sessions for professionals who develop policies for their organizations, work with clients on complex privacy issues, or those interested in emerging privacy topics.

In the Future of Privacy Forum’s training on Building a Responsible AI Program, participants will learn about the most used frameworks for AI governance and appropriate governance intervention points in the AI development lifecycle. From the basics of how to add AI governance to existing data governance structures to scaling AI transparency & accountability assessments, this course will provide you with the knowledge to build and scale a program to meet existing and upcoming regulatory requirements.

Participants will gain an understanding of:

  • The current state of Responsible & Trustworthy AI Frameworks and how to choose what for your situation
  • How to approach the key RAI components: fairness, transparency, privacy, safety & security, accountability
  • Where are the best assessment and intervention points in the machine learning and AI lifecycle
  • From piloting to scaling implementation,  how to assess the effectiveness of a Responsible AI Program
  • Successful approaches to company & employee RAI training

After completing each training course, you will receive a digital badge from Credly that can be shared on your professional network as a mark of the skills you’ve acquired.

Cancellation Policy

Cancellations will be honored, minus our vendor’s processing fee, up to 3 days prior to the session. For cancellations after that date, we will honor the registration for the next scheduled date of this session or an alternate FPF training class.

FPF Faculty

Jevan Hutson

Associate, Hintze Law PLLC

Jevan Hutson is an Associate at Hintze Law PLLC. Jevan is a respected expert and thought leader on artificial intelligence (AI) and machine learning (ML) ethics, law, and policy. His practice focuses on the intersection of privacy, security, and data ethics, with experience in emerging ethical and policy issues in generative AI, large language models (LLMs), ML, and computer vision (CV). He helps clients assess and mitigate the reputational, regulatory, and legal risks associated with the development and deployment of AI/ML technologies.