AI in Healthcare (Part Three)

AI Risks

One of the main risks in AI is the potential for data to be stored and processed offshore. This poses a data privacy and security risk. Even HIPPA Australia-compliant companies like HH say that they use ‘a combination of localised and when necessary for performance, offshore services’. They say they ensure all state and territory laws are kept ‘through pseudonymisation, non-retention policies, and compliant local storage solutions’. As a business owner, you must assess the risk and make an informed decision.

Another risk of AI, as mentioned before, is the worry of compromising the development of clinical competencies with the reliance on AI. AI can also fail to provide the correct answers and cannot replicate clinical experience. With dependence on AI, analysis, clinical judgment, evidence-based insight and reasoning skills can be compromised. "Success is not about taking shortcuts; it's about taking the time to develop, for the depth you build today truly will be the foundation of lasting achievement tomorrow." This is also why our clinic has strict policies around AI use. AI can also mean that answers become standard and repetitive, which reduces the diversity of perspectives and creativity, potentially limiting personalised solutions and the richness of human input.

From a non-industry specific point of view,  there are risks with job displacement and workforce impact as AI take over some of the roles previously done by humans. As AI continues to automate tasks and streamline processes, specific jobs, particularly those that involve routine or repetitive tasks, may become obsolete. This shift can lead to workforce challenges. While AI offers efficiency gains, it also presents a responsibility to ensure that the workforce is prepared for these changes and that displaced workers are supported in transitioning to new opportunities.

Accountability is a concern with AI because when automated systems make decisions, it can be unclear who is responsible for the outcomes. Where does the fault lie? The data it was trained on or the individuals who implemented it? Additionally, over-reliance on AI can lead to a lack of human oversight, where professionals may defer responsibility to the system, assuming it is infallible. This shift can reduce accountability and lead to a lack of transparency in decision-making processes.

How are you managing your risks?