The current lack of public trust in AI risks inhibiting innovation and adoption of AI systems, meaning new methods will not be discovered and new benefits won’t be felt. A failure to uphold high standards in the technology we deploy will also place our nation at a strategic disadvantage compared to our competitors.
Research funding agencies should apply the content of grant applications to AI tools to predict the future of scientific and technological breakthroughs, enhance peer review, and encourage better research investment decisions by both the public and the private sector.
Inconsistent metrics and opaque reporting make future AI power‑demand estimates extremely uncertain, leaving grid planners in the dark and climate targets on the line
Federal and state governments need to ensure that the development of new AI and data center infrastructure does not increase costs for consumers, impact the environment, and exacerbate existing inequalities.
As AI becomes more capable and integrated throughout the United States economy, its growing demand for energy, water, land, and raw materials is driving significant economic and environmental costs, from increased air pollution to higher costs for ratepayers.
Without robust transparency and community engagement mechanisms, communities housing data center facilities are left with little influence or recourse over developments that may significantly affect their health and environment.
Preempting all state regulation in the absence of federal action would leave a dangerous vacuum, further undermining public confidence in these technologies.
Surging energy demand and increasingly frequent extreme weather events are bringing new challenges to the forefront of electric grid planning, permitting, operations, and resilience.
Many of the projects that would deliver the energy to meet rising demand are in the interconnection queue, waiting to be built. AI can improve both the speed and the cost of connecting new projects to the grid.
The decline of the coal industry in the late 20th century led to the dismantling of the economic engine of American coal communities. The AI boom of the 21st century can reinvigorate these areas if harnessed appropriately.
At this inflection point, the choice is not between speed and safety but between ungoverned acceleration and a calculated momentum that allows our strategic AI advantage to be both sustained and secured.
Improved detection could strengthen deterrence, but only if accompanying hazards—automation bias, model hallucinations, exploitable software vulnerabilities, and the risk of eroding assured second‑strike capability—are well managed.