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Artificial Intelligence is rapidly changing the landscape of healthcare, enabling medical professionals to interpret and assess patient information in real-time. The technology is also leading to better learn and make precise predictions from large datasets. However, the ability of AI to analyze data relies on processes that are not transparent, which makes it intricate to authenticate and trust outputs from AI systems. This AI use in healthcare raises questions around its ethics-based governance to dodge potentially harming patients, creating accountability for caregivers and undermining public trust in the technology.

Undeniably, AI plays an increasingly significant role in the fields of medical research and education. But its tools in healthcare have been observed to imitate racial, socioeconomic and gender bias, reports noted. There are also some questions raised about the privacy of patient data and the risk of inadvertent discrimination becoming encoded within the technology have left a large number of industry experts concerned about the ethical implications of machine learning.

As the technology continues to advance, the implications for patient safety, privacy and engagement will become more profound. Thus, as large healthcare systems significantly adopt AI, data governance structures must evolve to ensure that ethical principles are applied to all clinical, IT, education, and research activities.

According to the health division of the European Institute of Innovation & Technology (EIT) survey, 59 percent of healthcare machine learning start-ups expected the AI technologies they were developing to need regulatory approval, while just 22 percent could suggest topics that should be addressed by guidelines of ethics and AI.

These data and privacy concerns over the use of AI technologies make healthcare systems to embrace a data governance framework that can assist them by reducing ethical risks to patients and care providers. The European Union’s Ethics Guidelines for Trustworthy AI make seven key requirements, including human agency and oversight; technical robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; environmental and societal well being; and accountability.

A pharmaceutical company Sanofi, for instance, is building its own policy on the use and governance of AI, based on three principles that should be upheld when it comes to AI in healthcare. They are AI should be used in the interest of patients; the use of AI should not treat any groups of patients unfairly; and dignity needs to be preserved so the patient should have autonomy of thought, intention, and action when making decisions regarding health care.

Increasing Interest in Healthcare AI

In recent years, interest in healthcare AI has only grown as the technology has the potential to transform nearly every aspect of healthcare. From diagnosis of critical diseases to routine hospital management, AI is able to provide clinicians a collective understanding of all their data to see where best to deploy their products.

The technology flourishes in the imaging field where it can process information from X-rays and scans with speed and, increasingly, precision far beyond humans. AI is also used to train an open-source prosthetic leg to pivot and move based on the wearer’s movements, enhancing at every turn with new user data.