AI in Healthcare: Embracing Innovation While Navigating Risks and Accountability

In New Zealand and Australia, AI-driven tools have already been integrated into healthcare systems and are increasingly being used, with new products continuously emerging to further enhance clinical documentation, support diagnostic decisions, personalised treatment planning, and patient monitoring.

While AI tools are already being used in healthcare, many important questions and challenges remain unresolved. As these technologies continue to be implemented, it’s essential that governments develop clear rules and regulations to address potential risks. Several key issues still need to be tackled before AI can be fully embraced in healthcare:

Who is responsible when AI makes mistakes?

A key question in AI adoption in healthcare is who is accountable when an AI system makes an incorrect diagnosis or recommendation. While AI tools assist in decision-making, the responsibility for patient care ultimately rests with human healthcare providers. In cases where harm occurs due to AI, accountability may be shared between developers, healthcare organisations, and clinicians. Developers are responsible for ensuring AI systems are accurate and properly tested, while clinicians must verify AI recommendations and use their professional judgement. As AI continues to evolve, clear regulations will be needed to define accountability, ensuring that errors are addressed fairly while maintaining human oversight in healthcare decisions.

Ensuring Fairness: Validating AI for All Communities

Validating AI models to ensure fairness is crucial in New Zealand, where diverse populations, including Māori and Pacific Islanders, must be represented in healthcare data. Without proper validation, AI systems could perpetuate existing healthcare disparities, leading to inaccurate diagnoses or treatment recommendations for underrepresented groups. For instance, if Māori health data is underrepresented, AI may miss conditions more common in these communities, resulting in poorer outcomes.

To prevent bias in areas like diagnosis and resource allocation, AI models must be continuously tested and refined using diverse datasets. Collaboration with cultural and healthcare experts is essential to ensure AI systems provide equitable care for all populations in New Zealand, supporting culturally appropriate healthcare and better patient outcomes.

Training and Change Management for Effective AI Integration

To use AI effectively, the healthcare workforce needs upskilling in several areas. First, clinicians must be trained to understand how AI works, its capabilities, and limitations. This includes interpreting AI-generated recommendations and knowing when human judgment is necessary. Additionally, training should address ethical issues, such as data privacy and AI bias, and teach professionals how to collaborate with AI tools while ensuring patient care remains the priority.

Effective change management is also crucial when introducing AI in healthcare settings. Organisations must communicate the benefits of AI, address concerns, and foster a culture of innovation. Training must be provided to staff at all levels, with ongoing support and opportunities for feedback to ease the transition.

Lastly, healthcare professionals must engage in continuous learning to keep up with AI advancements, ensuring they remain competent and confident in using these technologies as they evolve. With proper training and support, AI can enhance healthcare outcomes while maintaining the essential role of human oversight.

As AI continues to shape the future of healthcare in New Zealand and Australia, it’s essential that we address key challenges to ensure these technologies are used responsibly and effectively. From ensuring fairness and inclusivity in AI models to providing comprehensive training for healthcare professionals, thoughtful planning is critical for successful integration. By focusing on collaboration, continuous refinement of AI tools, and supporting healthcare staff through change management, we can unlock AI’s full potential while prioritising patient care and equitable healthcare outcomes.

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Related Links:

Evaluation of Dragon Medical One by the Queensland government

Dragon Medical One Product overview