AI in Healthcare: Promising Yet Vulnerable

Written by: Martijn Looijmans _ Nebul

Artificial Intelligence (AI) is poised to revolutionize healthcare. From faster diagnoses to streamlined administration, the potential is immense. However, a recent report by Swiss researchers at the University Hospital Basel highlights serious risks. When large language models (LLMs) like GPT-4 are used in clinical settings, threats such as data poisoning, manipulation of image analysis, and other forms of misuse become real concerns.

Without proper security measures, these powerful AI models are attractive targets for malicious actors. And in healthcare, where lives and highly sensitive data are at stake, the consequences can be severe.

A Serious Warning from Switzerland as recently published on icthealth.nl ( “Meer beveiliging nodig om misbruik llms te voorkomen”)

The researchers advocate for three critical safeguards:

• Strong encryption of data, both at rest and in transit
• Secure and controlled implementation environments, to prevent AI models from interacting with external systems in unauthorized ways
• Mandatory cybersecurity training for healthcare professionals using AI tools

Their findings are aligned with the stricter requirements set forth in the European AI Act, which classifies healthcare applications of AI as high-risk.

What Does This Mean for Healthcare Providers?

For healthcare organizations, this means AI can no longer be implemented casually. The responsible deployment of LLMs requires an integrated approach that combines security, compliance, and practical usability. But how can this be achieved in a sector already under significant pressure?

Nebul’s Role: A Secure Bridge Between AI and Healthcare

At Nebul, we understand this challenge deeply. Our mission is to make AI both safe and practical for healthcare. All without compromising usability or innovation.

Our solutions include:

• 🔒 End-to-end security: API integrations with open source LLMs with similar or better output quality as GPT-4, due to RAG workflows and fine-tuning. Open source LLMs keep data exclusively within the domain of the organization without 3rd party access, unlike proprietary LLMs like GPT-4.
• 🛡️ Controlled AI environments: Our sandboxing technology ensures that AI applications operate strictly within predefined boundaries
• 🎓 Training and support: We provide tailored training for healthcare professionals in AI use and cybersecurity hygiene
• ✅ Compliance-first architecture: Our LLM and AI systems are designed to comply with the EU AI act, GDPR and ensure strict data compliance for European Sovereignty. This includes no access from 3rd parties for data training or access from foreign governments, for example via the US Cloud Act.

Looking Ahead: Responsible Innovation

The message from the Swiss researchers is clear: AI offers great promise-but no guarantees. Only through a combination of technology, policy, and human-centered training can we unlock the full potential of LLMs while minimizing risks.

Nebul helps healthcare organizations strike that balance-ensuring AI is not just intelligent, but also secure.

Want to know how Nebul can help your organization deploy AI safely and responsibly? Contact us for a free demo or consultation.