AI has become one of, if not the most, transformative technologies of our time. It has helped doctors diagnose illness and businesses serve their customers more efficiently. But at the heart of this issue is an important question: What role should AI play in the protection of our data?
According to the Pew Research Center, 72% of U.S. adults do not trust in companies to make responsible decisions on how they use AI, and that is fear understandable. If AI systems must constantly gather data to improve itself, is our personal data being sacrificed to build a better bot and make companies more money?
The simple answer is that how we approach AI is crucial to where this technology ultimately ends up in our society. AI is an effective and transformative tool that, when working in collaboration with human ingenuity, can achieve crucial breakthroughs in almost every sector of our lives. AI experts by and large are optimistic about AI’s potential, but the average American is more concerned than excited about the increased use of AI in our daily lives. The polarizing nature of AI can often blind the very real ability of this technology to change our lives.
People, Profits, Planet.
When developed and applied responsibly, AI can and will achieve great things. A Human-in-the-loop approach can ensure proper guardrails are in place to protect people and planet, while still generating profit. Let’s take a look at two positive examples of businesses and researchers driving profitable AI innovation while protecting their users’ bests interests.
Protecting Patient Data
It is possible! NVIDIA Clara enables hospitals and medical institutions to collaboratively train artificial intelligence models without sharing sensitive patient data, heavily relying on Federated Learning and differential privacy frameworks to safeguard privacy. Essentially, participating institutions keep their private data on local servers. Each client trains a model locally and shares only a fraction of the updated model parameters with a centralized server, which then aggregates these into a master model. Additionally, client-server authentication is handled securely. Connections require specialized tokens, and all exchanges are routed through the HTTPS protocol using SSL certificates to ensure trust and encryption.
This is what is known as a Trusted Execution Environment (TEE). Engineers and users move away from “Download and Protect” (where data leaves the vault and becomes the user’s liability) to “Visit and Analyze” (where the data stays in a secure cloud, and the user only takes home the knowledge). This automates the provisioning of secure cloud enclaves and verifies code against the approved data use agreement. The TEE approach is crucial to the future of NIH products, like Controlled-Access Data Repositories (CADRs), where patient privacy is paramount.
Bottom line: Humans can create AI solutions to improve healthcare delivery and accelerate drug discovery without putting patients’ information at risk
Protecting Private Identities in AI Photo Tools
A team at Purdue University has developed the patent-pending system, which is utilized before and after photos are uploaded to an AI editing platform. Essentially, they have created a way to mask sensitive biometric data in a photo so users can safely use other AI tools. It’s AI protecting AI. The Purdue system is the first solution that delivers full privacy where sensitive data never leaves the user’s device. The technology is moving closer to real-world deployment, and the research is optimistic that they can expand the system to protect additional sensitive features such as medical details, ID documents and other privacy-critical content.
Bottom line: A “Privacy by design” approach to AI development can build public trust in AI systems.
Conclusion
The question is not whether AI will become more integrated into our lives—it already has. The real question is whether we will build and deploy AI systems in ways that earn and maintain public trust. As AI continues to evolve, success should not be measured solely by how powerful these systems become, but by how responsibly they are developed and deployed. By keeping people at the center of AI development and maintaining strong human oversight, we can create a future where technological progress, privacy protection, and economic growth advance together. In that future, the answer to the question “Is your data safe from AI?” can be a confident yes.
The Mind Moves Approach
Mind Moves’ team of experts is unstoppably optimistic about the potential of AI for people, profits and planet. Read related case studies and blogs:
- Meeting Users’ Information Needs in Biomedical Research
- Chatbots and Challenges: Balancing Innovation with Policy
- Avoiding Another AI Winter: Lessons from the Past and Strategies for the Future
- From Pilot to Progress: Accelerating Public Health Innovation with Generative AI
- Our Phygital Future must be Designed Responsibly
Sources
- https://www.pewresearch.org/internet/2023/10/18/views-of-data-privacy-risks-personal-data-and-digital-privacy-laws/
- https://www.investopedia.com/terms/t/triple-bottom-line.asp
- https://www.pewresearch.org/internet/2025/04/03/how-the-us-public-and-ai-experts-view-artificial-intelligence/
- https://docs.nvidia.com/clara/index.html
- https://developer.nvidia.com/blog/federated-learning-clara/
- https://www.purdue.edu/newsroom/2026/Q1/privacy-by-design-purdue-tech-protects-against-identity-leaking-during-ai-photo-editing/
