The availability of experienced professionals to vet, oversee, and contextualise AI suggestions is crucial to ensure that such technologies are used responsibly and effectively.
EXPERT INSIGHTS
work like scheduling appointments, billing, and documentation is being minimised by automation so that providers can dedicate more time to clinical responsibilities. The benefits of the tools are widely acknowledged— they work with great amounts of data at unparalleled speeds, provide consistent results, and minimise the administrative burden on clinical personnel.
But the promise of AI should be carefully considered against the limitations. Healthcare is by nature complicated and highly personal. No machine learning can exactly model the subtle judgement that comes from decades of clinical experience, nor can it capture the emotional intelligence that is at the heart of empathetic care. That is why clinical leadership is necessary. The availability of experienced professionals to vet, oversee, and contextualise AI suggestions is crucial to ensure that such technologies are used responsibly and effectively.
Bias, Transparency, and the Limits of Data
One of the main reasons for continued monitoring is the potential for algorithmic bias. AI models learn from past data, and if that data is biased— either by gender, ethnicity, or socio-economic level— the model will repeat or even compound those differences. For instance, if historical data is biased toward underrepresentation of certain groups in certain diagnoses, AI models could be less precise in those groups. Clinicians have to be vigilant for such gaps and question AI results so that the quality of patient care is not compromised in the process.
The availability of experienced professionals to vet, oversee, and contextualise AI suggestions is crucial to ensure that such technologies are used responsibly and effectively.
Another issue is the ' black box ' characteristic of most AI frameworks. Especially in deep learning, why a decision is made may be unknown even to the creators of the system. In the health sector, where life hangs in the balance, such obscurity is undesirable. Patients and clinicians alike are entitled to know why a particular treatment was suggested or why one risk factor over another was targeted. Clinical professionals are
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BioVoiceNews | July-August 2025