Intro
Something we hear in AI is “garbage in, garbage out.” So, of course, if you have better data, better quality data, you’re going to get better outputs. So, I 100% believe that Privacy is a win-win situation for you and for your business.
Hello, my name is Tainá. I work for Roche as Global Privacy Counsel, advising the business on Privacy matters all over the world in both our divisions: Pharmaceuticals and Diagnostics.
Where is a good balance between innovation and data privacy?
I don’t think it’s a trade-off. It’s a feature. Privacy is a feature. If you have Privacy embedded, it means you can even build better products, because Privacy gives you more clarity on your use case and what you want to achieve.
It’s also about trust at the end of the day. If your customers trust your features more, they’re more willing to give you their data, because they know you’re going to do right by them. Of course, this means more clients and more data. It’s very good for your business.
Let’s take Privacy principles and AI features. Take data minimization, for example. Nowadays, a lot of AI companies bill through tokens. So, if you only use the right data, and not all the data you’re just dropping in there, that’s good for you. At the end of the day, your invoice is going to be much lower, because you only used the data that was actually necessary.
Another Privacy principle is data accuracy. And that’s also something we hear in AI: “garbage in, garbage out.” So, of course, if you have better data, better quality data, you’re going to get better outputs. So, I 100% believe that Privacy is a win-win situation for you and for your business.
What sets up AI governance programs to be successful?
One important thing you need in an AI governance program is your AI inventory. It’s basically a compilation of all the AI use cases you have in your company.
It’s very useful if you know nothing about a use case and need information about it. You don’t need to go around asking people. You can go to your single source of truth and get your answers there. I think this is helpful for everyone.
It’s also good for accountability. If you need to show something to the authorities or carry out due diligence, you have the information easily accessible. I think this is paramount in an AI governance program.
How can companies scale AI governance on a global scale?
In any global company that wants to harmonize, you need to ask, “What is the baseline?” Because yes, regulations are different. That’s unavoidable. But in Privacy, we’re actually very lucky that it’s very harmonized. Internationally, the laws share more or less the same principles.
I think it’s important that you define your baseline. This will depend on where your headquarters are, what your biggest market is, and where your affiliates are. Are they mainly in one region that follows one specific framework? If that’s the case, let’s take that as the baseline framework and build on it. Let’s use it as the minimum.
If another country has a regulation that goes further, you can add requirements to the baseline. If the regulation is lighter, you can’t go below the minimum. Sometimes, because your headquarters are based somewhere, you need to follow what applies there, because you may be fined there. So, sometimes that harmonization is unavoidable.
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