The possibilities of this technology are immense. Imagine every student having access to an empathetic tutor, every patient being able to instantly contact a medical expert, and every traveler having a real-time translator at their fingertips. As AI becomes more helpful, intuitive, and reliable, the technology will have a profound impact on virtually every area of the economy and society, from how people work and learn to how they play and socialize. In addition to boosting productivity and competitiveness, thereby raising standards of living, AI has the potential to address major global challenges, such as public health, clean energy, and environmental concerns.
Yet despite so many bright spots on the horizon, it is tempting to fear change. Some worry about how AI may affect their lives or livelihoods or agonize over the risk that AI may unleash bias and misinformation. Others see elements once relegated to science fiction, such as self-driving vehicles, virtual companions, and intelligent agents, becoming part of their world and fear that the darkest elements of these tales—machines destroying human civilization—may also come to pass.
It is with this bifurcated vision of the future that policymakers must confront the key question of how the United States should respond to the rise of AI. Should it prioritize accelerating innovation to maximize benefits or slowing down innovation to minimize risks? Indeed, the question is not merely rhetorical as hundreds of experts issued a demand last year for a six-month pause on AI research. In this environment, public opinion on AI is crucial. Elected officials are chosen to represent the will of the voters, and their policies and priorities tend to reflect public sentiment. At the same time, elected officials are chosen to lead and make informed decisions based on their constituents’ long-term interests.
This poll shows Americans have a multitude of views about AI. They are curious, interested, worried, and amazed. They think the technology will help advance science, make jobs less mundane, and improve health care, but they also worry that it could help create misinformation, enable hacking, and cause job losses. Overall, they are divided between AI optimists who believe the technology will make things better, and AI pessimists who think it will make things worse. And many have not yet made up their mind.
To remain a global leader in AI, the United States faces two big challenges. First, it must stay on the frontier of AI development, which requires maintaining a robust ecosystem of AI skills, chips, data centers, and models. Second, it must lead in AI adoption, especially in trade sectors of the economy where it faces global competition, and areas like education and government where there are significant rewards. Both efforts will require extensive coordination and cooperation between the public and private sectors, as well as a regulatory environment that fosters responsible innovation.
Policymakers have their work cut out for them, not only to design the right policies for AI that keeps the United States on course in the global AI race, but also to build public support for these initiatives. This task is especially challenging because AI, and the companies that make it, are regularly vilified in the media. As more Americans use and experience the benefits of AI and realize that their worst fears have not come to pass, hopefully public support will follow.
* Daniel Castro is the director of the Center for Data Innovation and vice president of the Information Technology and Innovation Foundation. He focuses on IT and internet policy issues such as data privacy, security, and accessibility. His work has been featured in major media outlets like The Washington Post and NPR. In 2013, he was named to FedScoop’s “Top 25 most influential people under 40 in government and tech,” and in 2015, he was appointed to the Commerce Data Advisory Council. He previously worked at the Government Accountability Office and the Software Engineering Institute. Castro holds a B.S. in Foreign Service from Georgetown University and an M.S. in Information Security Technology and Management from Carnegie Mellon University.
Source: Center for Data Innovation
