The Radical AI Podcast

Measurementality #7: Why AI Registries are Critical for Metrics of Accountability with Sara Jordan and Anand Rao

Dec 19, 2021

52:29

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Highlights

AI Chapters

Episode notes

How to Define Fairness and Bias, Right?

02:14

Ai Governance

02:28

Are These Systems Really Secure?

04:21

Introduction

3min

How to Measure Success in a I Systems?

2min

Is Your Return on Investment a Good Thing?

2min

Ai Governance

2min

How to Define Fairness and Bias, Right?

2min

Are These Systems Really Secure?

4min

Ai Governants - What Are You Missing?

3min

Is There a Roll for Model Registry?

3min

What Is the Model Registry?

3min

10.

Are You Using a Char Modal?

2min

11.

I Governance

3min

12.

Deploning

4min

13.

Is There a Solution to the Regindustry?

54sec

14.

Is It Possible to Measure Ai Performance in the Future?

4min

15.

How Much Water Are We Pushing Through Our Cloud Computing Centers?

1min

16.

The Future of Artificial Intelligence

2min

17.

The Future Privacy Forem - A Review

4min

18.

How Deep Learning Can Help the Environment

2min

19.

I'd Buy Offsets for the Flights, but I'll Still Do Cool Stuff

4min

In this 7th episode of Measurementality we'll be "identifying what counts in the algorithmic age" by exploring how AI development can better engage with governance and privacy with Sara Jordan and Anand Rao

Sara Jordan is Senior Researcher, Artificial Intelligence and Ethics at the Future of Privacy Forum

Anand Rao is a Principal with PwC’s US Advisory practice

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The Radical AI Podcast

Measurementality #7: Why AI Registries are Critical for Metrics of Accountability with Sara Jordan and Anand Rao

How to Define Fairness and Bias, Right?

Ai Governance

Are These Systems Really Secure?

Get the Snipdpodcast app

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Discoverhighlights

Save anymoment

Share& Export

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Get the Snipd
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