Healthcare is an industry where being cautious is of utmost importance. However, many countries are facing shortages of healthcare professionals. This industry also contains large amounts of patient data, which has raised questions about the role and perhaps the necessity of artificial intelligence (AI) in healthcare.
Combining technology and data has always raised the question of data privacy and security, but it can also ease the burden on our healthcare systems. Will AI be able to pierce the market for the greater good? Or will it raise serious concerns and fail terribly?
Understand the benefits and drawbacks of incorporating AI in healthcare.
Here are the benefits and drawbacks of introducing AI in healthcare.
Benefits of AI in Healthcare
Help with Administrative and Operations Needs
A large chunk of the work done by healthcare providers is paperwork and other basic managerial and organizational tasks. A lot of these mundane, but necessary, chores can be handled by AI. This will free up time for employees to focus their expertise better on more crucial affairs that require a human touch.
Easier Data Analysis and Diagnosis
Voluminous amounts of data can be sifted through by AI and ML algorithms, which are significantly faster than humans. This can help with data analysis, which in turn helps patients receive faster and more accurate diagnoses.
Better Health Surveillance
Smartwatches have already penetrated the market for wearable accessories and taken over. A critical component of them is their ability to track health data ranging from heart rate, steps per day, sleep timings, and other day-to-day activities. This allows the user to monitor their own fitness and well-being.
Drawbacks of AI in Healthcare
Data Security and Privacy Concerns
Healthcare data is something that is private and can leave a patient vulnerable to hackers if not properly protected. Data confidentiality is of the utmost importance, and any healthcare provider would be reluctant to share any information that might lead to legal action against them.
Difficulty in Training Due to Lack of Data
Machine learning algorithms depend on a large quantity of data for precise results. Lack of relevant data that is necessary for training may produce faulty results. Along with this, man-made errors are more likely since AI itself is man-made. Biases that stem from differences in race, sex, gender, and other characteristics can present themselves in a machine due to human error.
Social Issues and Job Security
Humans have always been hostile and skeptical at the thought of being replaced. With AI developing at a fast pace, this hostility has resurfaced. Healthcare is an industry filled with complexity, and the replacement of employees will mostly begin with those that are on the service side of it. Other employment opportunities will have to be redesigned to operate simultaneously with AI.
In a nutshell, the consequential rise of AI has solidified the role of technology in our future. But will it be able to smoothly operate side by side with humans, or will it fail to make a significant difference in the field of healthcare? That question can only be answered in the future. For now, the major benefits and drawbacks have been listed as a hope for what the future might hold but also a precautionary measure on what to look out for.