America’s data illiteracy imperils its worldwide lead in artificial intelligence

As the U.S. continues to wrestle with myriad concerns over the benefits and risks of artificial intelligence (AI), China has already emerged as an AI superpower with a clear focus on the use of data and analytics to achieve global dominance.

This poses significant short and long-term economic and national security implications for all Americans, from every walk of life and across every corner of our nation.

AI has already begun to alter the global landscape, if not the balance of technological, economic, political, and military balance of power. Indeed, according to McKinsey and the Stanford University AI Index, China ranks second in the world in global AI vibrancy and has “accounted for nearly one-fifth of global private investment funding in 2021, attracting $17 billion for AI start-ups.”

This is not to say America is absent from the AI race. In fact, the Stanford University AI Index reveals that the U.S. leads the world in private investment funding for AI, which was 3.5 times larger than the amount invested in China. The U.S. leads the world in newly funded AI companies, which is more than the European Union, the United Kingdom, and China combined. The U.S. continues to lead the world in AI innovation, as evidenced by the total number of scientific publications about AI. But this lead is eroding due to increased competition from other countries such as China.

The United States’ ability to maintain its AI leadership position and compete in numerous other STEM-related fields is predicated on the country’s commitment to preparing the workforce of today and young people who will comprise the workforce of tomorrow with sufficient data literacy skills.

To be clear, America has a data literacy crisis that threatens our shared security and prosperity. This requires a new national commitment to data literacy education that demands the attention, action, and commitment of policymakers and leaders in Washington and beyond.

In recent years, the government sector, particularly in national security, has been plagued by staffing shortages. This is particularly true when positions require advanced degrees, such as Master’s and Ph.D. degrees, along with stringent citizenship requirements. The private sector attracts the majority of qualified STEM graduates with advanced degrees.

A commitment to data literacy is needed to create a pipeline of students who can fill crucial shortages in anticipated jobs related to national security and AI and meet our need for this type of employment in the future. The U.S. Bureau of Labor Statistics predicts that STEM jobs will increase by 15 percent by 2029, with millions more jobs in other sectors requiring higher levels of data literacy than in the past. The need for a data-literate workforce is only going to become more pressing in the coming years.

Data literacy is the ability to read, understand, interpret, engage with, and communicate data. The data-literate can evaluate the quality and reliability of data, ask informed questions about data, and effectively communicate data-driven findings to others. These will be essential skills needed by the workforce of tomorrow that will no longer just be needed in the data sector.

We need a data-literate work force. We need data-literate policymakers. We need a data-literate populous. To get there, it starts in the schools and on campuses.

In recent years, many universities have added or expanded programs around data science, analytics, computer science and similar disciplines. But that’s not enough. Meaningful education that can shape the trajectory of future generations requires centering data literacy into our educational systems at the start of a child’s education. It means increasing the access to data science education, decreasing equity gaps in data literacy, and centering data skills with the timeless educational ideal of the “three Rs.”

Affecting such a systemic educational change will not be easy. We are all aware of the breadth and depth of the issues facing schools and children everywhere. But without preparing today’s children for meaningful career opportunities and societal imperatives that await them, America is at risk of falling behind in AI innovation to China and other global actors.

That’s why the bipartisan congressional sponsors of the act — Reps. Haley Stevens (D-Mich.), Jim Baird (R-Ind.), Don Beyer (D-Va.), and Young Kim (R-Calif.) — should be applauded for helping to lead the way in Congress with their recent bipartisan introduction of the Data Science and Literacy Act (H.R.  1050).

Their bill would authorize $10 million annually for schools (pre-K-12 and two- and four-year colleges) to increase access to data science and literacy education in pre-K-12 and two- and four- year colleges.  It would leverage data science literacy as a primary strategy to increase representation and diversity in emerging technology.

Although this $10 million won’t change the world, it will make a difference. It sets forth a path for a national commitment that we will become a data literate society.

More can and should be done, but let us embrace this starting point that protects our vital and vibrant national interests by supporting this legislation and the underlying imperative of data literacy for all Americans.

Laura Albert is a professor and Harvey D. Spangler Faculty Scholar in Industrial and Systems Engineering at the University of Wisconsin-Madison. She is president of INFORMS, the largest association for the decision and data sciences.