Balancing Innovation and Ethics in AI Healthcare Applications

Although there are benefits to the quick application of AI, there are also a number of risks that should be carefully considered.

GlobalData October 23 2023

One of the sectors that uses artificial intelligence (AI) the most is the healthcare sector. AI makes it possible to monitor enormous amounts of data, look for patterns and trends and improve speed and accuracy in applications such as patient therapy support, medical diagnosis and even telemedicine.

The FDA has seen a surge in requests for products based on AI and machine learning (ML) in recent years. Thus, the establishment of the regulatory framework coincides with a pivotal moment for medical innovation in this technological domain.

The FDA witnessed an increase in the development and adoption of digital health advancements in 2020. During the Covid-19 pandemic, the FDA declared that it would be easing some regulatory requirements for specific devices in an attempt to improve access to low-risk, clinically suitable digital health solutions.

As the wave of digitalisation sweeping the industry gains momentum, the FDA has taken a bigger step toward improving the regulations governing medical devices by forming a new advisory committee of experts to better understand the benefits and drawbacks of implementing technologies such as AI and ML in healthcare.

By directly tying the FDA's committee to the Digital Health Center of Excellence, which was founded in September 2020, this action plan further demonstrates its commitment to healthcare regulation. The Center aims to empower partners to advance in digital health innovation in a responsible and superior way, thereby improving healthcare.

In the healthcare sector, AI is being used to solve a variety of issues, from image interpretation to medical diagnosis. Although there are benefits to the quick application of AI, there are also a number of risks that should be carefully considered due to the extremely sensitive areas they may affect. In conclusion, the ethical element needs to be central to its introduction, development and continuous supervision.

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