Page 62 - Cyber Defense eMagazine April 2023

4. Lack of Regulation:

Currently, there are no clear regulations or guidelines for the use of AI in healthcare. This can lead to
inconsistencies in how AI applications are used and a lack of accountability.

Implications for PHI and the Doctor-Patient Relationship:

1. Privacy:

AI applications require access to personal health information, raising concerns about patient privacy.
Patients may be hesitant to share sensitive medical information if they are unsure of how it will be used
or who will have access to it.

There is a concern around the potential for AI to violate patient privacy. As AI algorithms are often trained
on sensitive patient data, there is a risk that the algorithms could be used to identify individual patients,
even if the data has been de-identified.

2. Confidentiality:

The use of AI in healthcare raises important questions around the confidentiality of the doctor-patient
relationship. As AI requires vast amounts of patient data to operate effectively, patients may be hesitant
to share sensitive information with their healthcare providers. This could lead to patients withholding
important information, which could negatively impact their care.

There is also a risk that AI could be used to identify individual patients, even if the data has been de-
identified. This could lead to a breach of patient privacy and a violation of the doctor-patient relationship.

To address these concerns, healthcare providers must ensure that they have robust data security
measures in place. This includes using encryption to protect patient data, implementing access controls
to limit who can access patient data, and ensuring that all employees are trained on data security best
practices.

Healthcare providers must also be transparent with patients about how their data will be used. Patients
must be informed about how their data will be collected, stored, and used, and they must have the
opportunity to opt-out of data sharing if they so choose.

Healthcare providers must always ensure that they are using unbiased AI algorithms. This includes
ensuring that the data used to train the algorithms is diverse and representative of the patient population,
and regularly monitoring the output of the algorithms for bias.

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