AI Content Privacy Issues: A Solution By Sophia Solanki, Founder of Narrato

Roberto Popolizio Roberto Popolizio

Generating personalized content at scale is nowadays easier than ever thanks to AI content generators, but at the price of our privacy.

However, these tools leverage user behavioral data, which can be an ethically and legally sound approach only if the data is used in compliance with data protection regulations and always with the user’s consent.

So how can AI content generation tools create personalized content at scale and respect your data privacy?

You will learn that in this chat between Safety Detectives and Sophia Solanki, Founder of Narrato,one of the most successful AI content solutions on the market right now with $1M raised from investors like Airtree Ventures and other marquee angels, a 4x ARR growth, and multiple awards received for their content autopilot, AI Content Genie.

What are the benefits of content personalization with AI for consumers and businesses?

With the advent of AI in the content creation space, generic content has become a commodity that everyone can generate at scale, making it worthless.

Building a strong brand and improving user experience are now the keys to stand out.

Our goal with Narrato is to provide an entire suite of personalization and customization options that make it easy to generate content always aligned with a brand’s identity. So far we have developed over 100 solutions to customize content at scale, but we can group them in two core points of our approach to branded content creation.

Custom AI templates

Save your frequently used prompts as reusable templates where you can simply input your variables to generate new content. This helps you simplify the creation of any type of content that you need frequently, and for which there may not be a pre-built template on other AI platforms.

Custom brand voices

All you have to do is provide a few examples of your existing content, be it from your blog, social media, or other channels, and let our proprietary AI analyze your brand voice.

Once done, the AI generates a detailed description of your custom brand voice which can be saved and applied to all your AI content generation prompts.

This way your audience will always be able to identify your content from the style and tone in which it is written, while first-time visitors to your website and social accounts will better understand your brand’s image.

What type of data do generative AI platforms collect?

Generative AI tools are trained on vast amounts of content from the web. This includes content like blogs, social media content, website content, newsletters, emails, descriptions, and any other type of content the AI is expected to create. From such content, generative AI platforms are designed to collect certain data to enhance their performance and generate creative outputs. They typically collect and analyze large datasets, including text, images, audio, and video data.

The machine learning algorithms used by generative AI platforms learn from these datasets and develop the ability to generate original content based on the patterns and information they pick. By leveraging diverse and extensive datasets, generative AI platforms can produce realistic text, images, voices, and even human-like conversations. The collection and analysis of different types of data enable these platforms to continuously improve their accuracy, creativity, and overall performance.

And what Are the Privacy Concerns Regarding AI-generated content?

Most AI platforms must pay keen attention to data privacy, and what most AI software providers do is adopt privacy-by-design principles. This means they embed privacy features into the software architecture from the early stages of development, ensuring that privacy is a core consideration. By doing so, they are proactive in addressing privacy concerns and minimizing any potential risks associated with data collection and usage.

The real concerns are about unregulated use of AI with technologies like Deepfakes. Deepfake videos, which are created using AI algorithms, can make it difficult to distinguish between real and fake content. AI technology has the capacity to manipulate visual and audio elements to create realistic but entirely fabricated content. This raises concerns about privacy, as individuals can be targeted by manipulated videos that can damage their reputation or deceive others.

Tighter regulations are necessary in areas like these, but thankfully most software providers employ advanced encryption methods to safeguard sensitive user information, ensuring that data cannot be accessed or breached by unauthorized individuals or entities.

AI software providers follow strict compliance with data protection regulations and industry standards. They ensure that their software adheres to legal requirements, like the General Data Protection Regulation (GDPR) in Europe or the California Consumer Privacy Act (CCPA) in the United States.

We at Narrato also believe in the privacy-by-design principle. We’ve ensured that no user information is stored or used for any other purpose when you use our AI tools. We follow very strict data privacy and security protocols, keeping all our security certificates up to date, ensuring that there is no violation of the above mentioned legal guidelines.

How can businesses implement AI-driven personalization in their content without collecting user data?

Instead of relying on individual user data, businesses should focus on contextual personalization. Narrato’s AI algorithms can determine relevant recommendations and tailor the content accordingly by analyzing the content and context of the interaction.

But how to collect the data needed for personalization while preserving the user’s privacy?

Businesses can also aggregate and anonymize user data to gather insights at a group level without compromising individual privacy. By analyzing patterns and trends among a large cohort of users, AI algorithms can provide personalized recommendations without directly associating them with individual users. This approach protects user privacy while still providing a personalized experience.

Some examples of personalized content that can be created without collecting user data?

As far as content creation goes, most of the content can be created without collecting user data. Blog posts, social media posts, website content, and most other types of content can be generated from information like context, audience, product or service details, and other inputs like your tone. They do not require any specific user data.

What will be in your opinion the future key trends in AI content and privacy?

In my opinion, the future key trends in AI content and privacy will revolve around two main aspects:

1. Advanced Natural Language Processing (NLP)
AI will continue to advance in its ability to understand, interpret, and generate human-like language leading to improvements in automated content creation, translation, and personalized recommendations. NLP advancements should also be able to empower AI to better identify and mitigate harmful and malicious content, such as fake news and hate speech.

2. Privacy-enhancing AI
With growing concerns about data privacy, there will be an increased focus on developing AI technologies that prioritize the protection of user data. Privacy-enhancing techniques, such as federated learning and differential privacy, will enable AI models to be trained on decentralized datasets without compromising individual users’ sensitive information. This approach allows individuals to have more control over their data while still benefiting from AI-based services.

About the Author

About the Author

Over a decade spent helping affiliate blogs and cybersecurity companies increase revenue through conversion-focused content marketing and Digital PR linkbuilding.