Article by Jacob Taylor, Scott E. Page, Kershlin Krishna, Adam Aley, Vivek Ramakrishnan, Sarah Mills, Joshua Becker, Eirini Malliaraki, Fahd Husain, and Sanjay Purohit: “As the artificial intelligence (AI) boom brings large data center proposals to small and rural communities across the United States and beyond, the most resounding story to emerge is one of mismatched agency. In journalist Jasmine Sun’s words, “big companies descend on a small town and run roughshod over small-d democracy.”
Many people do not want data centers in their communities. And for good reasons: the costs are material, if still not fully understood, spanning noise and visual pollution, land-use change, and rising electricity demand with knock-on effects for water withdrawals and utility affordability. As with most large-scale developments, data centers also offer economic upsides—a surge of construction jobs, considerable tax revenue, and improvements in infrastructure. These can be significant but are not always guaranteed.
Given the scale and impact of data centers, people should have a voice. However, decisionmaking about data center siting is often fragmented, noninclusive, and based on criteria other than their impact on communities. In many parts of the country, states set tax exemptions and approve utility contracts, while local officials, often working part-time, negotiate one siting approval at a time, up against experienced corporate counsel imposing time pressure and confidentiality agreements. Local citizens are rarely directly involved in these processes and, where confidentiality provisions apply, may learn the terms of a proposed deal only after negotiations are well advanced. The result is that residents feel sidelined, fueling skepticism as to whether data center proponents are sharing all relevant information and whether public officials are acting in the community’s best interests. Because data center developments are closely associated with the rapid diffusion of generative AI in the U.S. and elsewhere, uncertainty about the projects themselves can also become entangled with broader concerns about AI’s economic and social impacts, as well as its existential risks.
Known remedies for these challenges exist—namely, community-led processes that surface varied priorities, align on a common vision, and help turn it into action. Historically, such processes have proven costly and complex, requiring time to build the trusting relationships on which collaboration depends—time that can be particularly scarce when communities are responding to fast-moving development proposals. Deliberative processes become more difficult to run when issues are emotionally and politically charged, as is increasingly the case with data center developments in the U.S…(More)”.
