Artificial Intelligence technologies have the potential to improve multiple aspects of healthcare research, diagnosis and care delivery, according to a Bipartisan House Task Force Report on Artificial Intelligence.

The report highlights America's leadership in its approach to responsible AI innovation, while at the same time considering guardrails that may be applicable to safeguard the nation against current and emerging threats. 

The task force gathered information on AI issues from industry, government, civil society and academia and offered guiding principles, 66 key findings and 89 recommendations.

When it comes to healthcare, the report says, "AI can quickly analyze large datasets, improve diagnostic accuracy, streamline operations and automate routine tasks, all of which have the potential to improve efficiency and efficacy in treatment and reduce burdens on healthcare practitioners, freeing up more time for patient care." 

Among the key findings: AI's use in healthcare may reduce administrative burdens and hasten drug development and clinical diagnosis. When used properly, uses of AI could lead to increased efficiency, better patient care and better outcomes.

However, the report notes that the lack of ubiquitous, uniform standards for medical data and algorithms obstructs system interoperability and data sharing. 

Moreover, if AI tools cannot easily connect with all relevant medical systems, their adoption and use could be impeded. 

In response, the task force proposed recommendations, including:

• Encouraging practices to ensure AI in healthcare is safe, transparent and effective.

• Maintaining robust support for healthcare research related to AI.

• Creating incentives and guidance to encourage risk management of AI technologies in healthcare across various deployment conditions to support AI adoption and improve privacy, enhance security and prevent disparate health outcomes.

• Supporting the development of standards for liability related to AI issues.

• Supporting appropriate payment mechanisms without stifling innovation.

The report also stated that generative AI can assist in medical imaging, while AI tools have shown promise in augmenting patient care in clinical applications, such as predicting patients' health trajectories, recommending treatments and supporting population health management.

According to the report, an example of an AI-enabled clinical support tool is one that can recommend specific treatments to healthcare professionals based on a patient's symptoms and medical history. 

In the areas of privacy and cybersecurity, the report highlights that AI tools require huge amounts of data, including patient data, that may be used by or shared between various groups, which could impact patient privacy.

The report notes, "There are concerns among providers, healthcare systems and patients about who has access to data, how it is being used and if it is safely secured."

In the areas of data privacy specifically, the report says, "As AI systems amass and analyze vast amounts of data, there are increasing risks of private information being accessed without authorization."

The authors note that AI has the potential to exacerbate privacy harms, that Americans have limited recourse for many privacy harms and that federal privacy laws could potentially augment state laws. 

In response, the bipartisan group recommends policies and protections to support consumer confidence, including exploring mechanisms to promote access to data in privacy-enhanced ways and ensuring privacy laws are by and large applicable and technology-neutral.