How a Human-Centered Approach is Building Trustworthy AI
Elvis Duran and the Morning Show ON DEMAND
Elvis Duran Podcast Network and iHeartPodcasts
4.7 • 1.2K Ratings
🗓️ 18 November 2021
⏱️ 30 minutes
🧾️ Download transcript
Summary
Creating trust and transparency in AI isn’t just a business requirement, it’s a social responsibility. In this episode of Smart Talks, Malcolm talks to Christina Montgomery, IBM's Chief Privacy Officer and AI Ethics Board Co-Chair, and Dr. Seth Dobrin, Global Chief AI Officer, about IBM’s approach to AI and how it’s helping businesses transform the way they work with AI systems that are fair and address bias so AI can benefit everyone, not just a few.
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Transcript
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| 0:00.0 | Hello, Hello, Hello. This is Smart Talks with IBM, a podcast from Pushkin Industries, |
| 0:11.6 | I Heart Radio, and IBM about what it means to look at today's most challenging problems in a new way. |
| 0:18.0 | I'm Malcolm Gabor. |
| 0:20.0 | Today I'll be chatting with two IBM experts in artificial intelligence about the company's |
| 0:26.4 | approach to building and supporting trustworthy AI as a force for positive change. |
| 0:36.0 | I'll be speaking with IBM's chief privacy officer, Christina Montgomery. |
| 0:41.0 | She oversees the company's privacy vision and compliance strategy globally. |
| 0:45.8 | Looking at things like immunity certificates and vaccine passports. Not what could we do, but what were we |
| 0:51.8 | willing as a company to do. |
| 0:53.2 | Where were we going to put our skills and our knowledge |
| 0:56.5 | and our company brand in response to technologies |
| 1:00.2 | that could help provide information in response to the pandemic. |
| 1:05.0 | She also co-chairs their AI ethics board. |
| 1:09.2 | I'll also be talking with Dr Seth Dobrin, |
| 1:11.7 | Global Chief AI Officer at IBM. Seth leads corporate AI strategy and is |
| 1:17.2 | responsible for connecting AI development with the creation of business value. Seth is also a member of IBM's AI ethics board. |
| 1:26.7 | We want to make sure that the technology behind AI is as fair as possible, is as explainable as possible, is as robust as possible, and |
| 1:38.4 | as as privacy preserving as possible. |
| 1:41.3 | We'll talk about the need to create AI systems that are fair and address bias and |
| 1:45.9 | how we need to focus on trust and transparency to accomplish this. What might the |
| 1:51.3 | future look like with an open and diverse ecosystem with |
| 1:55.1 | governance across the industry. There's only one way to find out. Let's dive in. |
... |
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