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Ethical Considerations; Automated Diagnosis of Skin Disease Using Deep Learning.
While deep learning-based automated skin condition diagnosis has the potential to
improve healthcare, IT managers must be mindful of the ethical considerations involved to
prevent unexpected effects. They are responsible for guaranteeing that the technology is
created in an impartial, safe, and favorable mode to healthcare professionals and that patients
are informed about it and given a chance to make individual decisions about whether or not to
use it.
One of the most crucial ethical issues is the possibility of partiality in the records applied
to prepare the deep learning system. Using training data not representative of the diverse
population may result in inaccurate and biased diagnoses. IT managers' job is to ensure that the
statistics applied to create the procedure are varied and impartial and that the system is
repeatedly examined to ensure biases do not, over time, become ingrained in its logic.
Another important ethical duty is to secure patient information and keep it secret. Deep
learning requires access to a large amount of patient data, including images of the patient’s skin
conditions, to be used for the automated diagnosis of skin diseases. IT managers are responsible
for ensuring that this data is obtained and managed securely and that the necessary security
measures are taken to prevent unauthorized access or other security breaches.
Another aspect CIOs and other IT administrators need to consider is the potential impact
of the automated diagnosis on healthcare practitioners' jobs. The technology has the potential
to completely replace medical experts' work, even while it may help them make more accurate
diagnoses (
Wu et al.,2020)
. Information technology managers must ensure that new
