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In-Ear Insights: Responsible AI Part 4: Implementing Responsible AI
In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss implementing Responsible AI in your business. Learn how to align AI with your company values, establish accountability, ensure fairness in AI outputs, and maintain transparency in your AI practices. By understanding these elements, you can unlock the true potential of AI while avoiding potential pitfalls. Gain valuable insights to navigate the complex world of AI implementation and build a framework for responsible AI usage in your organization.
Watch the video here:
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
https://traffic.libsyn.com/inearinsights/tipodcast-responsible-ai-implementation.mp3
Download the MP3 audio here.
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Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
Christopher S. Penn – 00:00
In this week’s In-Ear Insights, we are finishing up our responsible AI series. This is part four. In part one, we talked about what responsible AI is—talking about the difference between ethics and morals, and how you would decide what your ethical principles for AI use are, even things like intellectual property and licensing. In part two, we talked about bias, the different types of bias, the way that models are biased, and what you should be doing to counteract that. In part three, we talked about data privacy, how to keep your data private, and the considerations you need to be thinking about when you’re working with Generative AI. And so, in this last part, let’s talk about the implementation of responsible AI.
Christopher S. Penn – 00:40
And to absolutely no one’s surprise, the implementation of responsible AI follows the 5P process, which is purpose, people, process, platform, performance, which you can get a copy of at TrustInsights.ai 5PFramework. So Katie, when we think about implementing the responsible AI framework—which, by the way, you can get a copy of at TrustInsights.ai RAFT—where do we start helping people understand and make the concept of generative responsibilities of AI? How do we turn that into reality?
Katie Robbert – 01:18
I mean, you have to start at the top of the 5Ps and really have a clear goal in mind of why are we doing this in the first place. So, a couple of weeks ago, we spoke at MAICON, and I spoke specifically about managing the people who manage AI. And when I talked about AI integration—I didn’t use the word responsible AI, but it was, if you saw the talk, it was very heavily implied, because it’s all about focusing on the people and not the technology itself.
There’s a lot of groundwork you need to do before you bring AI into your organization as a whole, especially if you want to do it responsibly and ethically. And so, you need to make sure that you understand, number one, what it is and why you’re doing it. That’s your purpose. But then you need to get into the people, and really
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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss implementing Responsible AI in your business. Learn how to align AI with your company values, establish accountability, ensure fairness in AI outputs, and maintain transparency in your AI practices. By understanding these elements, you can unlock the true potential of AI while avoiding potential pitfalls. Gain valuable insights to navigate the complex world of AI implementation and build a framework for responsible AI usage in your organization.
Watch the video here:
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
https://traffic.libsyn.com/inearinsights/tipodcast-responsible-ai-implementation.mp3
Download the MP3 audio here.
[podcastsponsor]
Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
Christopher S. Penn – 00:00
In this week’s In-Ear Insights, we are finishing up our responsible AI series. This is part four. In part one, we talked about what responsible AI is—talking about the difference between ethics and morals, and how you would decide what your ethical principles for AI use are, even things like intellectual property and licensing. In part two, we talked about bias, the different types of bias, the way that models are biased, and what you should be doing to counteract that. In part three, we talked about data privacy, how to keep your data private, and the considerations you need to be thinking about when you’re working with Generative AI. And so, in this last part, let’s talk about the implementation of responsible AI.
Christopher S. Penn – 00:40
And to absolutely no one’s surprise, the implementation of responsible AI follows the 5P process, which is purpose, people, process, platform, performance, which you can get a copy of at TrustInsights.ai 5PFramework. So Katie, when we think about implementing the responsible AI framework—which, by the way, you can get a copy of at TrustInsights.ai RAFT—where do we start helping people understand and make the concept of generative responsibilities of AI? How do we turn that into reality?
Katie Robbert – 01:18
I mean, you have to start at the top of the 5Ps and really have a clear goal in mind of why are we doing this in the first place. So, a couple of weeks ago, we spoke at MAICON, and I spoke specifically about managing the people who manage AI. And when I talked about AI integration—I didn’t use the word responsible AI, but it was, if you saw the talk, it was very heavily implied, because it’s all about focusing on the people and not the technology itself.
There’s a lot of groundwork you need to do before you bring AI into your organization as a whole, especially if you want to do it responsibly and ethically. And so, you need to make sure that you understand, number one, what it is and why you’re doing it. That’s your purpose. But then you need to get into the people, and really
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