Ethical Concerns, Privacy Issues and Lack of Trust in AI
BSI’s International AI Maturity Model was developed to assess readiness for advanced AI adoption. Healthcare scored lowest in terms of maturity over seven sectors, with ethical concerns, privacy issues and a significant lack of trust slowing the adoption process.
But this isn’t necessarily a worrisome result. Investment-heavy regions and industries, while appearing to be on the front foot, may still face significant barriers to achieving true AI maturity. There is plenty of time and space for sectors such as healthcare to accelerate progress and do so with key considerations in mind.
Protecting data and privacy is one element of that. The U.S. healthcare industry operates under a strict regulatory environment focused on patient safety and personal data protection. AI systems in this space generally involve large amounts of patient data, raising concerns about how this information is collected, stored and accessed. U.S. healthcare providers work under strict and complex data protection regulations such as HIPAA, making the considerations of AI implementation greater.
Additional BSI research shows that data protection in the healthcare industry is a main concern for professionals, and currently only 18% report that their organizations have AI risk assessments in place, compared with the life sciences and pharmaceutical industry at 46%. To achieve AI maturity, this is a key area for healthcare to focus on.
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Building Trust to Accelerate AI Adoption Rates
One of the first components of successful AI adoption journey is for businesses to establish clear, ethical internal guidelines for AI use. This includes setting boundaries, ensuring the technology is used in ways that align with new policies and protect patient data and well-being.
Accelerating AI adoption in healthcare hinges on building a culture of trust for providers and patients by positioning transparency, accountability and a commitment to ethical standards at the forefront. By working under these principles, providers can ensure the technology is designed to prioritize the patient.
Ensuring compliance with regulations is a critical aspect that must be implemented throughout the industry. Currently, only 36% of healthcare leaders report that their businesses are implementing policies and procedures regarding the safe and ethical use of AI – a concerning figure, as developing clear guidelines for AI deployment and data protection helps healthcare organizations ensure responsible AI use and build trust with stakeholders.
When organizations adhere to regulation, patients can also be assured that AI will not become the judge and jury of decision-making but instead a tool for professionals. While AI can assist by providing data-driven insights, it’s crucial that humans make the final call.
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Fostering Education and Workforce Development for AI
Building an understanding around the technology is another important aspect of successful AI adoption. To be effectively integrated into healthcare, AI models will need to be explainable and interpretable, offering professionals and patients clarity on how decisions are made. Such transparency has the potential to help build confidence in AI-driven outcomes, making it easier for professionals to incorporate these tools into their workflows.
Education and workforce growth initiatives can help establish trust, yet currently only 17% of healthcare leaders said their businesses have learning and development programs to ensure successful delivery of AI training, according to additional BSI research. To reap the benefits of AI in healthcare, increasing the training on offer is critical.
Ultimately, healthcare is on the cusp of a digital transformation driven by AI, but progress is needed to achieve the same readiness for AI other sectors are displaying. The journey to widespread AI adoption is complex and nonlinear, but with a focus on compliance and ethics to establish trust in the technology, the sector can unlock AI potential and reshape the standard of patient care.
