Little Known Challenges Facing Artificial Intelligence Deployment in Health Care Systems

Artificial Intelligence (AI) is one of the emerging technologies that are largely deployed in the health care industry. AI is a broad-based term that includes machine learning, deep learning and natural language processing to accomplish “smart tasks” that we mostly associate with human beings. 

The technology augments human skills to perform the most complex problems, while offering insightful data. However, AI in health care poses unique data challenges. In medicine, AI is empowered to use deep learning and machine learning algorithm to emulate human skills in the analysis, understanding and display complex medical report.

According to IDC research, healthcare industry records a larger amount of data that continues to grow as time goes by. US Patient Protection and Affordable Care Act exacerbated the challenges related to data privacy due to adoption of electronic records that contain the information about patients.

Companies like Pfizer, IBM and Salesforce use the electronic health records to forecast the beginning of conditions such as breast cancer, Alzheimer’s diabetes, schizophrenia and diabetic retinopathy. 

AI in medicine is increasingly becoming vulnerable to cyber attack. Criminals can hold someone’s data hostage demanding ransom. 

Data should be secured through deploying encryption technologies to prevent phishing and espionage. Stakeholders should adopt privacy preserving methods such as federated leaning, differential privacy and homomorphism.