The Keystones Of Responsible AI: Explainability And Visualizations Intelligent Data Exploration podcast

Virtualitics에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Virtualitics 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Intelligent Data Exploration «
The Keystones of Responsible AI: Explainability and Visualizations

3+ y ago 41:26

MP3•에피소드 홈

The future is no-code or low-code, but as more and more companies implement AI solutions and enable non-technical users, how do you maintain accuracy and responsible use?

The answer: explainable AI paired with multi-dimensional visualizations. These combined provide a more complete picture of the story playing out in a predictive system and are a must for ensuring responsible AI applications.

Join Caitlin Bigsby, Head of Product Marketing, as she sits down with Virtualitics’ Co-Heads of AI, Sarthak Sahu, and Aakash Indurkhya to discuss ways to incorporate visualizations into the ML lifecycle and key considerations.

챕터

1. Introduction (00:00:00)

2. The Importance of Exploration (00:09:54)

3. Exploring for More Responsible AI (00:16:45)

4. Exposing the Mechanisms of AI (00:22:37)

5. What Stakeholders need to know BEFORE (00:26:02)

6. Why Context for the User is Necessary (00:30:11)

7. Why Context Makes AI More Responsible (00:34:20)

46 에피소드

#Tech #Virtualitics