Navigating AI Security Challenge

The healthcare sector is at a critical inflection point in the digital transformation journey, mainly due to artificial intelligence (AI) adoption and data management. As healthcare organisations increasingly leverage AI technologies to enhance patient care and operational efficiency, they face unique challenges in securing systems and protecting sensitive information. It is estimated that in 2023 the healthcare sector spent about $13bn on AI-related hardware
and software. This number is forecasted to reach $47bn by 2028.

Recent surveys reveal a contrast in confidence levels regarding AI security across different regions. Globally, IT decision-makers in the healthcare sector display a high level of assurance, with 82% expressing confidence in their ability to protect against AI-related threats1. This optimism suggests a growing recognition of AI's potential and a proactive approach to security measures.This confidence is not uniform across all regions. In the United Kingdom, for instance, the healthcare industry demonstrates significantly less certainty. A concerning 43% of UK healthcare professionals reported feeling "not at all" or "not particularly" confident in their ability to safeguard against AI-related threats1. This regional disparity highlights the need for a more nuanced, global approach to AI security in healthcare.

Healthcare organisations are adopting various strategies to manage the use of AI, mainly generative AI tools:

• Acceptable Use Training: 39% of healthcare organizations provide employees with training on the acceptable use of generative AI1. This approach aims to educate staff on the proper handling of AI tools and associated data.
• Complete Ban: Interestingly, 30% of healthcare organizations have taken the drastic step of banning the use of generative AI completely1. This conservative approach reflects the serious concerns some institutions have regarding the security implications of these technologies.

When it comes to the implementation of generative AI, healthcare leaders have identified several key concerns:

• Exposure of Personally Identifiable Information: This is the top concern, with 47% of healthcare leaders expressing worry about the potential leak of sensitive patient data1.
• Protection of Trade Secrets and Intellectual Property: 40% of leaders are concerned about the exposure of proprietary information and intellectual property through AI systems1.
  These concerns underscore the delicate balance healthcare organisations must strike between leveraging AI's benefits and protecting sensitive information.

To address these challenges, healthcare organisations should consider implementing comprehensive security measures:

• Data Encryption: Utilising strong encryption protocols for all sensitive data, both at rest and in transit.
• Access Controls: Implementing strict role-based access controls to ensure that only authorised personnel can access sensitive information.
• Regular Security Audits: Conducting frequent assessments to identify and address potential vulnerabilities in AI systems.
• AI-Specific Training Programs: Developing comprehensive training programs that focus on the secure use of AI tools and the handling of sensitive data within AI environments.
• Privacy-Preserving AI Techniques: Exploring and implementing advanced techniques such as federated learning or differential privacy to enhance data protection in AI applications.
  

As the healthcare industry continues to modify its IT requirements, a focus on AI security is crucial. Organisations must work towards bridging the confidence gap between global and regional perceptions of AI security.
A combination of robust technical measurement implications and fostering a culture of security awareness or continuous learning will lead to effective AI assimilation.

The varying approaches to AI governance – from providing training to imposing outright bans – indicate that there is no one-size-fits-all solution. Healthcare organisations need to carefully assess their specific needs, risks, and capabilities to develop tailored strategies for AI implementation and security.

By addressing the primary concerns of data exposure and intellectual property protection, healthcare leaders pave the way for more secure and effective use of AI technologies.
This approach will not only enhance patient care and operational efficiency but also maintain the trust that is crucial in the healthcare sector. The medical and healthcare sector needs to remain vigilant and adaptive in its approach to AI security.

Source:
https://www.digitalhealth.net/2023/10/healthcare-sector-has-lowest-levels-of-security-protection-for-ai/