Artificial intelligence has a very high potential in the healthcare industry. It has helped medical professionals to design treatment plans and find the best methods of treating each patient. Artificial intelligence can also assist in monotonous and repetitive tasks so that doctors and other healthcare professionals can concentrate on their jobs. Artificial intelligence can prioritize the email inboxes of medical doctors and keep them updated while at the same time assist in finding the latest and most relevant scientific research at a moment’s notice. The transformative power of AI in the healthcare industry makes it as critical as the stethoscope; the modern medicine symbol that was invented in the 19th century.
There are already excellent examples of the use of AI in healthcare facilities. For instance, a partnership between the National Health Service of UK and DeepMind was launched to improve the process of healthcare delivery by the use of digital methods. Just this year, DeepMind expanded its services by bringing in incentives like data management applications and streams to another hospital in the UK.
However, the million dollar question is how human beings can translate the vast potential of AI into their daily lives. Despite the many benefits of Artificial intelligence to the healthcare sector, it has also posed some challenges. In this article, we shall discuss the obstacles of AI in the field of medicine.
As it stands at the moment, the term AI might be confusing to some as it represents a wide array of technological advancements. There are narrowly intelligent programs that have been seen to defeat human beings in specific tasks. For instance, machine learning has enabled the development of narrow artificial intelligence (ANI) in many fields which are developing at a swift rate. Such technological advances in artificial intelligence have created robots that are task specific. However, these machines are only designed and programmed to perform a certain task to perfection. Unlike human beings, these machines cannot perform multiple different tasks without having to be reprogrammed which is proving to be increasingly difficult. In healthcare, artificial intelligence can only help in making machines that can do a single task perfectly.
We have to acknowledge the medical limitation of modern artificial narrow intelligence to avoid over-hyping the technology. There is the risk of underlying bias and feeding the computer with millions of images in the case of using machine learning and deep learning image recognition in radiology. There is also a huge limitation in introducing ANI to healthcare facilities to perform administrative tasks. This is because it will be difficult to standardize and streamline medical records in a way that the algorithms make sense to humans. Follow Sentient’s profile on linkedin.com.
It will be much easier to overcome the technological as well as the medical limitations of artificial intelligence in healthcare as compared to the moral issues that are associated with the technology. For instance, technology is to blame if there is a mistake made by a smart algorithm in failing to detect a cancerous cell on a lung x-ray. There are complex legal and ethical issues that confront AI, and they have to be solved for AI to be efficient.