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In-Ear Insights: Data Protection, AI and Privacy
In this week’s In-Ear Insights, the TrustInsights.ai podcast, Katie and Chris discuss data protection, AI and privacy. How do you protect your data and client/customer data when using AI tools like ChatGPT? Learn the two major protection classes and three levels of data protection in this episode. Tune in to find out more!
Watch the video here:
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
https://traffic.libsyn.com/inearinsights/tipodcast-data-protection-ai-privacy.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’re answering a question from our free Slack group, Analytics for Marketers, which you can find at TrustInsights.ai. Lauren asks, “How are you keeping client data safe inside generative AI tools like ChatGPT?” There’s a whole range of options and ways of doing this, and we can talk through the entire structure. Katie, just off the top of your head, when you think about this—because this is really a data governance question—what should people be asking?
Katie Robbert – 00:34
Well, that’s exactly it. Choosing the tool first is the wrong way to approach it because you first need to know what, when you say “keep my data safe,” what does that mean? That’s pretty vague. Am I protecting it from the sun and I need to put sunblock on it? In reality, we’re talking about data governance and data privacy. First and foremost, you need to define what data you’re collecting that needs to be protected, and then what protection actually means. Are you anonymizing it and then using it in publicly available tools, or do you need to keep it completely firewalled from the rest of the internet?
Katie Robbert – 01:26
You need to have some sort of an intranet versus an internet. These are the kinds of things you need to define first. Once you know what data protection and data privacy actually mean for your client data and your company, then you can go ahead and choose whatever generative AI tool. Now, in reality—because I’m also a realist—I know you’ve already chosen a tool. I know you’re already using something. I know you’ve already put your client data in it, and you’re like, “Huh, I wonder if I should be doing this. I wonder if I read the terms when I agreed to something, I agreed to the wrong thing.” So I would probably start there.
Katie Robbert – 02:17
I would go back through the terms you agreed to, see how the data is being used, and see if you need to change the settings in the tool you’ve been putting all of your client data into.
Christopher S. Penn – 02:31
There are two major considerations with generative AI tools: training data and human review. Training data means, hey, when you use pretty much any free tool out there, your data is the price of admission. The company c
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By Trust Insights
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In this week’s In-Ear Insights, the TrustInsights.ai podcast, Katie and Chris discuss data protection, AI and privacy. How do you protect your data and client/customer data when using AI tools like ChatGPT? Learn the two major protection classes and three levels of data protection in this episode. Tune in to find out more!
Watch the video here:
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
https://traffic.libsyn.com/inearinsights/tipodcast-data-protection-ai-privacy.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’re answering a question from our free Slack group, Analytics for Marketers, which you can find at TrustInsights.ai. Lauren asks, “How are you keeping client data safe inside generative AI tools like ChatGPT?” There’s a whole range of options and ways of doing this, and we can talk through the entire structure. Katie, just off the top of your head, when you think about this—because this is really a data governance question—what should people be asking?
Katie Robbert – 00:34
Well, that’s exactly it. Choosing the tool first is the wrong way to approach it because you first need to know what, when you say “keep my data safe,” what does that mean? That’s pretty vague. Am I protecting it from the sun and I need to put sunblock on it? In reality, we’re talking about data governance and data privacy. First and foremost, you need to define what data you’re collecting that needs to be protected, and then what protection actually means. Are you anonymizing it and then using it in publicly available tools, or do you need to keep it completely firewalled from the rest of the internet?
Katie Robbert – 01:26
You need to have some sort of an intranet versus an internet. These are the kinds of things you need to define first. Once you know what data protection and data privacy actually mean for your client data and your company, then you can go ahead and choose whatever generative AI tool. Now, in reality—because I’m also a realist—I know you’ve already chosen a tool. I know you’re already using something. I know you’ve already put your client data in it, and you’re like, “Huh, I wonder if I should be doing this. I wonder if I read the terms when I agreed to something, I agreed to the wrong thing.” So I would probably start there.
Katie Robbert – 02:17
I would go back through the terms you agreed to, see how the data is being used, and see if you need to change the settings in the tool you’ve been putting all of your client data into.
Christopher S. Penn – 02:31
There are two major considerations with generative AI tools: training data and human review. Training data means, hey, when you use pretty much any free tool out there, your data is the price of admission. The company c
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