- Increasing the adoption of artificial intelligence (AI) in healthcare and other industries will require federal policymakers to enhance health data access, invest in AI research and education, and implement policies to address potential concerns about the technology, according to a new report from the Center for Data Innovation.
The report states that while the US has made positive strides in AI development and use, other nations are implementing strategies that could put them ahead in AI innovation. The report outlines the steps the US should take in order to develop a national artificial intelligence strategy across all economic sectors.
“Succeeding in AI requires more than investments from leading companies. It requires a healthy ecosystem of AI companies, inputs such as skills and data, and organizations that are motivated and free to use AI,” said Joshua New, the Center's senior policy analyst and author of the report.
“Building a robust AI ecosystem will require the federal government to actively support the development and adoption of AI, which will be best done through a comprehensive national strategy.”
In order to accelerate the development and adoption of meaningful AI tools in healthcare, the Center suggests that federal agencies focus on the following areas and initiatives.
Improve access to health data through enhanced interoperability
The success of AI relies on the sharing, collection, and use of data. However, many organizations, especially those in the healthcare industry, are often restricted in their ability to access and leverage the data needed to develop AI tools.
“The potential for AI to deliver benefits in the healthcare sector, such as by discovering new drugs, reducing costs, and improving patient care, is significant,” New stated. “Yet organizations face a wide variety of factors limiting their ability to access the data necessary to take advantage of AI effectively.”
“In many cases, some organizations are still not fully digitized, making the collection, sharing and analysis of data virtually impossible. In other cases, some individuals and communities are not included in data collection efforts, limiting the benefits the data can provide. Regulatory obstacles can also unnecessarily limit data collection, access, and use.”
To overcome barriers to data sharing, the report suggests that federal agencies should support the development of shared pools of high-quality data. Policymakers should also continue to support efforts to digitize the healthcare sector, as well as establish data sharing use cases for AI development.
“Congress should ensure that any national legislation addressing privacy considers the importance of data for the development and use of AI and does not impose undue restrictions on the collection, sharing, and use of data that come at the direct expense of AI innovation,” the report said.
Increase federal investments in AI research, education
To further expand AI use, federal stakeholders should invest in research and development (R&D) ventures that may lead to important breakthroughs in AI technologies.
“Public and private R&D investment is a crucial driver of innovation and economic growth,” the report noted.
“Notwithstanding the fact that major IT companies invest in AI research, federal R&D investment is needed to continue advance AI. This is because companies tend to invest in later stage applied research and development, rather than more foundational basic and early stage research.”
The Center suggested that policymakers substantially increase R&D funding for AI, placing particular emphasis on basic and applied research. The organization also recommended that federal agencies support R&D for all types of AI applications, and not just certain kinds of AI and related technologies.
In addition to increased funds for AI research, the report urged federal agencies to invest in building a skilled, AI-focused workforce.
“If the AI economy is to expand it will require considerably more workers with AI skills. However, the United States is already struggling to meet the demand for workers with such skills and this limitation, more so than any technical limitation, holds back AI progress,” the report said.
To build an AI-savvy workforce, the Center advised policymakers to launch initiatives that will cultivate AI talent, such as computer science fellowship programs or academic grants. Federal agencies should also provide funding to universities that have increased enrollment in computer science.
Implement regulations while encouraging innovation
As AI continues to show its potential in healthcare and other industries, there are concerns that the technology will cause more issues than it solves, including security problems and systemic bias.
Additionally, the prevalence of “black box” software, which makes it difficult for even big data experts to understand the inner workings of a machine or device, can significantly impact users’ trust of AI.
“Concerns about the potential harms of AI can have a chilling effect on AI acceptance,” the report said. “Consumers’ distrust of AI will drive down demand for AI products and services, and businesses in turn will be less likely to develop or offer these products or services.”
“Thus, there is a need for regulatory action that addresses potential harms without inhibiting AI innovation.”
To achieve this, the report recommends that policymakers pursue regulatory frameworks based on algorithmic accountability. This would ensure that an algorithmic system promotes desirable outcomes and protects against harmful ones.
Policymakers should mandate that public agencies conduct thorough assessments for algorithms they intend to use for decisions that have significant consequences, such as clinical decisions.
If the US is to reap the benefits of AI in healthcare and other key industries, policymakers will have to develop a comprehensive strategy that accelerates AI implementation and growth.
“The benefits of AI—to the competitiveness of firms in the United States, to economic growth, to government operations, and to social welfare—and the risks of falling behind are too vast for policymakers to sit on the sidelines hoping private-sector action is enough,” the report concluded.
“It is time for a national AI development and adoption strategy.”