Adrian Johnson
TLDR:
- The healthcare industry faces cybersecurity challenges in the wake of emerging technologies, with differences in handling PII and PHI.
- GenAI will transform healthcare operations and patient care by automating tasks and improving diagnosis.
In this Help Net Security interview, Assaf Mischari, Managing Partner at Team8 Health, discusses the risks associated with GenAI healthcare innovations and their impact on patient privacy. The key cybersecurity challenges in healthcare in the context of GenAI include differences in handling personally identifiable information (PII) and protected health information (PHI). Health providers lag in modern infrastructure and cybersecurity measures, making PHI easier for attackers to target. The development of AI models in healthcare must prioritize algorithmic fairness to avoid biases that could lead to misdiagnosis and improper treatment.
GenAI is set to transform healthcare operations and patient care by automating tasks, analyzing vast amounts of patient data, and providing consistent and objective diagnoses. However, the importance of human context in data analysis suggests that the future of diagnosis will likely be collaborative between humans and AI. Measures to ensure patient privacy with GenAI innovations include data anonymization, improved privacy-preserving techniques, and secure data storage with strict access controls.
Discussing GenAI’s ethical implications in healthcare, Mischari emphasizes the need for transparency and explainability in decision-making processes to foster trust and enable informed decisions. As GenAI rapidly advances in healthcare, regulatory frameworks need to evolve to accommodate these changes, such as establishing standardized ML clinical sites and vetting data sets for bias. Healthcare organizations should prioritize transparency, patient safety, and continuous monitoring to build and maintain public trust in GenAI technologies.
