Einstein monotile background

Blog

Conversational AI and privacy: a user-friendly guide for end users

Explore how conversational AI safeguards your privacy through secure storage, controlled access, and compliance with GDPR regulations.

my image Some great alternative text

Conversational AI systems are becoming a staple in our daily lives, offering convenience and efficiency. However, with this advancement comes the pressing need to protect user privacy, especially in accordance with EU legislation like the General Data Protection Regulation (GDPR). Let’s explore how end user privacy is safeguarded in systems like UNLESS, focusing on key questions about data storage and access.

Why is my data being stored?

If you consent to this, an AI may remember your conversations so you can continue later. Very useful. But data storage in conversational AI is not just about keeping records. It’s about enhancing the system’s ability to serve you better. By storing data, these AI systems can learn from past interactions, leading to more accurate responses and improved performance. Usually, this process is compliant with GDPR, which mandates that only necessary data should be collected and that users must be informed about its use. Thus, data storage is often a means to an end: a better user experience. It shouldn't contain personally identifiable data, though.

Where is my data stored?

Once collected, your data needs a secure home. Typically, it is stored on secure servers, which could be located on-site or in the cloud (which means in a shared bunker somewhere). These servers are fortified with strong security measures, including encryption and access controls. Cloud storage solutions often provide advanced security features and compliance certifications, adding an extra layer of protection. It’s crucial that wherever your data is stored, it adheres to regional data residency laws, which helps maintain your trust. For example, as a European citizen, it helps if your data is in the EU, too.

Who has access to my data?

Access to your data is tightly controlled. Only authorized personnel, who have passed strict authentication checks, can access it. This is where role-based access controls (RBAC) come into play, ensuring individuals only see what they need to fulfill their role. Regular audits and monitoring help detect any unauthorized access attempts, safeguarding your data further. It’s equally important to ensure that any third-party partners also comply with these privacy standards. You can find third party partners in a sub-processor list in a DPA - which stands for Data Processing Addendum - that any AI provider should have publicly available.

What data can be accessed?

Not all data is created equal. Conversational AI systems prioritize data minimization, meaning they only collect what is necessary. This includes basic inputs, metadata, and user preferences, while ensuring sensitive information like Personally Identifiable Information (PII) is either not collected, filtered or masked, or at least well-protected. Techniques like anonymization or tokenization further reduce the risk of exposure. These measures ensure that your privacy is respected at every step.

When is my data deleted?

Data should not overstay its welcome. Robust data retention policies dictate how long data is kept. Once its purpose is fulfilled, it must be securely deleted. Automated processes help maintain compliance with these policies, reducing the risk of breaches. Furthermore, GDPR empowers you with the right to request data deletion, enhancing transparency and trust. Knowing when your data is deleted gives you peace of mind.

Here’s the surprising part: GDPR requires that AI providers be able to delete your data from AI models, but that’s technically nearly impossible. So, many AI providers flat out refuse, which breaks EU laws. Providers like UNLESS address this by ensuring the AI model never sees your data. They replace private data in conversations with completely unreadable labels (“tokenization”) before it’s sent to the model, and then re-identify the answer before delivering it back to you. That way, the external model has no access to your data and is therefore no longer a sub-processor. Funky, right?

So, there's a lot to it

In summary, protecting privacy in conversational AI involves a well-rounded approach. From secure storage to controlled access, and from data minimization to timely deletion, each step is guided by EU regulations like GDPR. By prioritizing these measures, organizations can build a foundation of trust, ensuring that your data is handled with care and respect. As these technologies continue to evolve, keeping privacy at the forefront remains essential.

my image Some great alternative text

Friendly support from real people

We’re here to help

We are known for our quick responses if you have an issue. Feel free to ask us anything. But you can also ask our conversational AI a question, of course!