Personalized AI Adoption: Nillion Forging a New Path for Data Privacy while Training AI

In today’s technological era, it is impossible to claim that you’ve not interacted with artificial intelligence (AI). AI is fast becoming a daily part of our interactions with technological products or services, from home to professional use. This ranges from fintech applications, e-commerce, and healthcare to as close as having a Meta AI integrated on Facebook, Instagram, and WhatsApp.

It won’t be long before we start seeing personalized AI in action. It is not a question of “if it is possible.” Instead, it is a question of “when.” Even at that, it is closer than you think. However, with personalized AI and how it can bring ease and seamless operations to individuals, people aren’t sure they want to trust AI with sensitive information. And without data, you can’t train AI models.

This intersection is what Nillion, a secure computation network, explores for individuals and companies. Nillion is building a platform that will allow you to train and personalize AI while securing your data without compromising data ownership. Let’s dive deeper.

The Conflict of Data and User’s Interest in the New Technological Era

Individuals used to be reserved when interacting with AI, but the release of ChatGPT changed the adoption of AI. This doesn’t mean AI hasn’t been used widely across various industries like education, cybersecurity, marketing, healthcare, predictive analytics, etc. People are now more comfortable using AI to optimize their productivity and ease their operations.

The debate for data security and privacy became a hot discourse. People want to use AI but are unsure if they want it to have deep access to personal information. This is one of the reasons some significant companies, such as Wells Fargo, Bank of America, Apple, and Samsung, banned ChatGPT.

They guard these data as though they are the next thing to inheritance. But the main problem is data exploitation. Centralized companies are fighting hard to have access to sensitive data they can manipulate for their gains.

One of them is to help them tailor their offers to maximize their profits and increase their revenues, as evident in digital advertising. We’ve seen how e-commerce websites use our search histories to recommend products that might suit our needs or satisfy temporary wants. This explains how vital data becomes in the business world. Thus, data access and exploitation are why people are conservative about AI.

How Nillion is Crafting a Pivotal Scheme to Win the Data War

On the other end of the spectrum, Nillion is solving the problem of data exposure to and leak by AI. Nillion answers, "What if you can have a personalized AI that you feed data to train, which is private for you only?”

Individuals are open to having a personalized AI. But access to sensitive information is a delicate affair. This is evident in the research conducted by Nillion. About 95% of 2000 people love the idea of personalized AI, but the same 95% won’t give it deep access to their sensitive information.

However, Nillion is leveraging blockchain computation to solve that problem. This brings life to blind computing. An AI will compute what you want it to without knowing it has the answers. It is like feeding an AI machine with information stored in it unaware.

Although this is secure by cryptographic security, which makes your data yours only, no one can use or steal it. As a result, you own the data used to train AI through a blockchain network. This blockchain use case brings data ownership while creating a digital clone of yourself. As a result, your data are safe and secured beyond a cloud-based environment.

Beyond data used for transactions on the blockchain, Nillion is opening up a vast green land for more emerging industries through the collaboration between blockchain and data. This will birth emerging industries, and Nillion will usher in a new era of blockchain use cases through data.

Data and AI WITHOUT Nillion Network Data and AI WITH Nillion Network
No data privacy and exclusive security. There is data privacy and exclusive security.
There is no data ownership. Thrid party tends to have more control and power over one’s data. You have exclusive data ownership. No third party has control and power over your data.
Third party tends to leak one’s information without securing your identity. You can share your data with the public while being anonymous. Safe and secure identity.
The need to decrypt and re-encrypt when you want to build using the data in the storage. Blind computation allows you to use the data without the need for the traditional decrypting and re-encrypting.
Do not always have privacy-enhancing technologies (PETs) Uses privacy-enhancing technologies like Multi-party Computation (MPC), fully homomorphic encryption (FHA), and zero knowledge proofs (ZKP) to store and manage high-valued data on their network
Cannot help in successfully creating a digital clonen of yourself. Can help in successfully creating a digital clonen of yourself.
Cannot successfully open up the path for mass adoption of personalized AI. Opens up the path for the mass adoption of personalized AI.

Examining the difference in what the synergy of AI and data will be with and without the Nillion Network.

Unlocking Mass Adoption of Personalized AI

The era of personalized AI is imminent, but it is puzzling that the responsibility for data privacy and security might be shifted upon individuals or centralized companies.

While this might threaten data security, Nillion, as a network, is eradicating the limitations for individuals in maximizing personalized AI. Nillion is creating a computation network that allows you to train an AI with private and sensitive inputs that only you can use. This will open up the channels for mass and public adoption of personalized AI.

We’ve gone past the debate of whether personalized AI will happen. We are now in the era of making it possible without data compromise. That is what Nillion is working on: building a computation network where you can train an AI with sensitive data and create a digital clone of yourself through decentralized technology.

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