• The utilisation of AI in healthcare comes with a set of opportunities and trade-offs that keep it both topical and controversial.
  • The use of artificial intelligence in health care is expected to grow significantly over the next decade.

Even within the constantly evolving landscape of healthcare in the United States, the utilisation of AI has emerged as a complete game-changer. From predictive and personalised treatment plans to models for early diagnosis, AI is already transforming the healthcare sector in unprecedented ways. However, like any novel and groundbreaking technology, the utilisation of AI in healthcare comes with a set of opportunities and trade-offs that keep it both topical and controversial.

The pros of AI in healthcare

1. Early detection and diagnosis

AI-driven algorithms can analyse vast amounts of medical data with previously impossible speed and accuracy. For example, they are able to process medical images, such as X-rays, MRIs and CT scans, with remarkable precision that often surpasses human capabilities.

2. Personalised treatment plans

AI models can also be used to analyse extensive patient histories, genetic data, lifestyle and other relevant data sets to assess risk factors and develop highly personalised treatment plans. It is believed that this tailoring of care can lead to more effective treatments with fewer side effects, improving the overall patient experience.

3. Telemedicine

AI can continue to enable the growth of telemedicine by enhancing remote patient monitoring and diagnosis. With AI-driven chatbots and virtual assistants, patients can have their symptoms and concerns assessed, receiving tailored advice without the need for in-person visits to healthcare facilities.

Also read: Opportunities of AI in healthcare

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The cons of AI in healthcare

1. Ethical dilemmas

AI’s deployment in healthcare applications raises complex ethical questions with unclear liability and accountability. Who is responsible for AI-related mistakes? How and should AI handle end-of-life decisions? How to ensure that AI does not perpetuate healthcare disparities or demographic biases?

2. Diagnostic accuracy

While AI systems can be highly accurate, they are not infallible. There is always a risk of misdiagnosis or overlooking crucial information, leading to potentially life-threatening errors. The “black-box” nature of some of these AI systems can also make it challenging to understand the basis for their decisions or where responsibility lies in the event of these errors.

3. Data privacy and security

AI relies on expansive amounts of sensitive patient data, which makes data privacy and security a paramount concern. The misuse, unauthorised access to, or exposure of this data can have serious personal, ethical and legal consequences.

The future of AI in health care

As with many other industries, AI is poised to change the health care landscape over the coming years. In addition to improving health facility operations, patient diagnoses, treatment plan development, and overall health outcomes, AI is also expected to help with the development and discovery of new medical cures.

The use of artificial intelligence in health care is expected to grow significantly over the next decade. According to Grand View Research, AI in health care is forecasted to be valued at $208.2 billion in 2030, which is many times higher than its 2022 market size value of $15.4 billion.