Generative AI: Ethics, Black Boxes, Explainability
This second session in our CAI Learning Series focuses on Generative AI as a strategic imperative. AI is at the top of the hype cycle and it’s not coming down. How do you cut through the noise to gain a full understanding of the impact on your organization? In this session, CAI welcomes Rainbird, a cognitive decision automation platform for scaling knowledge and automating human decision-making. Join us for a discussion on ethics, the limitations of black boxes, and explainability as it relates to large language models (LLM) and ChatGPT.
Audience learning objectives and key takeaways:
- Cut through the noise for a full understanding of the implications of adding generative AI and LLM to your organization.
- Learn how to add predictability, consistency, and auditability to your AI solutions.
- Understand what explainability is expected to achieve and how it differs related to degrees of technical expertise, understanding, and fear.
- The need to consider ethics, policy, and governance around AI models, then proceed with caution in a strategy for success.
Hosted by:
Christina Kucek
Executive Director, Intelligent Automation, CAI
Executive Director, Intelligent Automation, CAI
Christian Ventriglia
Automation Consultant, Intelligent Automation, CAI
Automation Consultant, Intelligent Automation, CAI
Session 2 guests:
Matt Peters
Chief Technology Officer, CAI
Chief Technology Officer, CAI
James Duez
Co-Founder and Chief Executive Officer, Rainbird Technologies
Co-Founder and Chief Executive Officer, Rainbird Technologies