Implementing AI in Healthcare: The Challenges

1/ Data gathering and technical capabilities

AI requires a set of massive data to perform, and that goes to the very first concern, the process of gathering data. The limited data and unqualified data quality are slowing down the implementation of AI in healthcare. AI can only perform at its best if they are trained with a high volume of "the right" data. The source of data must be trusted, or else AI output would be adversely affected. But acquiring reliable data has never been an easy step. The foremost reason is that information related to health is strictly regulated, and only authoritative individuals are able to collect from hospitals.

Other than the lack of quality data, the technical capabilities are another challenge. Very few people have necessary "AI literacy" for data processing, especially with that large amount of data. The infrastructure and tools needed to support AI techniques are also in their very early stage, which makes it hard to perform a wide range of algorithms for a wide range of diseases.

2/ Local and governmental regulations

As mentioned, data from hospitals are valuable, yet difficult to obtain. The lack of or vague regulatory acts regarding data collection for the purpose of AI implementation are the main reason here. The only solution is for government and healthcare organizations to create uniform regulatory acts that every hospital must comply with to enable a smooth data giving-receiving process. Such acts will also create an extent of trust for patients, enabling them to feel comfortable sharing their health data without fearing a breach of privacy.

3/ Trust and fear

The implementation of AI in healthcare will only be successful if patients are well aware of its potential and ready to embrace its solutions. Due to the current lack of awareness and trust towards AI, patients may fear being treated and operated by "a robot".

The same goes to doctors. Introducing AI as a tool or an amplifier to the medical field by including AI literacy in medical schools is a good move, considering that there's a chance that doctors (not all, obviously) regard AI as a threat and a displacement to them, therefore refusing to consider suggestions of AI.

What we're gonna do now is to educate both medical employees and patients about AI and its various potential, as well as its procedures to narrow the skills gap and gain trust from patients.


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