AI and Medicine
AI goes on to simplify processes, the ability to manually carry out such tasks is not lost – as there must always be skill within the department, either for verification or indeed if the AI systems fail.
Impact on job demand: Many fear that the widespread use of AI in healthcare could lead to a reduction in the demand for some healthcare jobs, particularly those that involve routine tasks. The majority of proposed applications that are currently in various stages of development would not make any healthcare professionals redundant. However, it is possible that many administrative workers within hospitals could face redundancy. This is a downside that has to be weighed against the benefits increased efficiency would bring to the patient such as reducing wait times as well as backlogged patients. It is also possible that the use of AI could increase the demand for certain types of healthcare professionals. This is because AI could potentially reduce the workload for some of the higher-intensity professions which are rendered unappealing due to the rigour involved. AI could reduce this stress improving both recruitment and retention (Goldhahn, 2018). Overall, the impact of AI on the healthcare workforce is still evolving, and its full extent remains to be seen. However, healthcare professionals will need to adapt to new technologies and ways of working as AI continues to develop and be integrated into healthcare. Despite that, if implemented in a manner that supports healthcare professionals, it has sizable benefits to offer.
Ethical considerations
Data Privacy and Security
One of the most important ethical components of AI is how data is protected and how it is used. Giuseppe Placidi, on the issue of data use for AI, states: ‘ Regarding ethics in the use of data, that is ownership, sharing (including consent to share) of anonymized personal data and privacy, they can be treated as in the case of any imaging modality, such as CT or MRI, where data are massively produced and their management is regulated by legal and ethical codes. Hence, these ethical aspects could be directly inherited by those of other digital systems. ‘ From this, we can understand that there are pre- existing models of data use to draw upon however, given the elevated scale and frequency of data use in a healthcare system that uses AI, it is important to re-examine how cyber security is maintained. Improved data security: AI can enhance the security of medical data by detecting and preventing potential cyber-attacks or data breaches, such as by monitoring network traffic for unusual activity or encrypting sensitive data. This can help reduce the risk of unauthorized access or data theft, protecting patient privacy and to maintain trust in the healthcare system. Enhanced patient privacy: AI can help protect patient privacy by automatically de-identifying sensitive medical data, such as removing patient names or other identifying information. This can help minimize the risk of unauthorized access or data exposure, particularly for research purposes where large datasets may be shared among multiple parties.
There are also some unique drawbacks to the use of AI that are relevant when exploring the ethical implications of this technology.
Risk of data breaches: The use of AI can increase the risk of data breaches or cyber-attacks, particularly if the AI system is connected to a network or cloud-based service. This can expose sensitive medical
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