While AI is making significant inroads into healthcare and other sectors of the economy, federal policymakers need to step up and enhance health data access, invest in AI research and education, and implement policies to address potential concerns about the technology.

That’s according to a new report from the Center for Data Innovation, which found 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 six areas and related initiatives:

1. Support key AI organizational inputs. To effectively develop or use AI, organizations need abundant access to three key resources: high-value data, AI skills, and publicly funded research and development.

2. Accelerate public-sector adoption of AI, including for national security. One of the most straightforward and effective steps government can take spur AI progress is to rapidly adopt AI in support of its own missions. Government can help prove the value of deploying AI, as well as provide markets and increase economies of scale for AI firms. 

3. Spur AI development and adoption in industry, including through sector-specific AI strategies. The federal government has significant influence and involvement in sectors such as health care, transportation, and education through funding, procurement, and regulation. Federal agencies should be charged with developing sector-specific AI strategies to shape their policies affecting these industries in ways that support AI transformation. 

4. Support digital free trade policies. Data is at the core of AI, and many nations are enacting policies that restrict cross-border data flows. The U.S. government needs to accelerate its efforts to establish free trade in data and fight other protectionist efforts that inhibit AI, such as source code disclosure requirements.

5. Foster innovation-friendly regulation. If poorly implemented, AI can produce undesirable outcomes. In response, some have called for strong regulations on AI, including through tougher enforcement of antitrust and regulation of algorithms. Policymakers should instead pursue a more innovation-friendly framework built around the principle of “algorithmic accountability,” in which the operators of algorithms are held accountable for explicit and serious harms.

6. Provide workers with better tools to manage AI-driven workforce transitions. AI-enabled automation will increase productivity and per-capita incomes but also will likely modestly increase the rate of worker displacement, which can lead to support for policies that restrict how firms can use AI. To help workers more effectively make transitions, policymakers need to modernize workforce training and worker dislocation policies and programs.

“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.”

“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.