AI In Healthcare 2018

In 2018, the vast majority of healthcare practices are ill prepared for the value and changes Artificial Intelligence currently provides, and will continue to provide the industry overall. This includes the need to implement systems that accurately, and transparently assist AI systems. This is something everyone should be concerned about.

AI has the tools to become a transformative technology in healthcare in mostly positive, but other concerning ways. For example, according to an Accenture survey: over 80% of health executives agree that within the next two years, AI will be a noticeable component in the workforce such as working next to physical humans, as a collaborator or advisor, or even a coworker in some cases!

Jobs will ultimately be phased out in some cases, as AI will make them obsolete such as certain support staff positions. This is why there is a major need for the healthcare industry to both transform and adapt to AI and to figure out a way for the eventual job disruption that will ensue.

Bias, naturally is an area that needs to be addressed. There must be clear and concise understanding behind any data that AI provides so that the users of the AI platform can understand the reasoning behind what the data suggests. Therefore, AI needs to implemented without any clear bias apart from assisting on any key organizational definitions or previously defined performance indicators.

Training for the AI platform, whatever that may be i.e. communication, health predictions, etc. is key to preventing any bias from disrupting the effectiveness of the AI.

As much as a benefit Artificial Intelligence can be for patient care, communication, and physician assistance, people must be able to have the skills to comfortably understand and work with the AI and continue to make improvements when needed.

Perhaps the most essential aspect of the development and implementation of AI in the future is educating physicians and all staff who work with the AI. Without proper education and training, the algorithms and sophisticated speeds in which AI can perform data crunching, clinical care decisions, and predicting and defining medical conditions will be without merit.