
Shoshone-Bannock Tribes reaffirm opposition to proposed AI data center in Pocatello
The Shoshone-Bannock Tribes have reaffirmed their opposition to a proposed AI data center in Pocatello, citing concerns over insufficient information from the developer regarding electricity rates, water resources, and environmental impacts. An appeal hearing before the Pocatello City Council is scheduled for July 16, following a conditional use permit hearing where the developer failed to provide adequate details.
The Shoshone-Bannock Tribes have restated their opposition to a proposed artificial intelligence data center at the former Hoku site in Pocatello, Idaho. This reaffirmation follows a review of public records, project materials, and testimony from a May 14 Conditional Use Permit (CUP) hearing.
Roselynn Yazzie, public affairs manager for the Shoshone-Bannock Tribes, stated that officials are concerned by the developer's failure to provide sufficient information regarding potential increases in electricity rates, impacts on water resources, and broader environmental effects. The Tribes are specifically concerned about the data center's potential to raise electricity rates for Tribal members and its projected water requirements for liquid cooling systems, particularly for on-site power generation.
The Tribes concur with the Pocatello City’s Hearing Examiner’s determination that the developer did not provide enough information for a meaningful review to justify the CUP's approval. They also highlighted environmental concerns, including construction impacts, pollution from gas-fueled generators, heat release, and wastewater runoff, particularly affecting the Portneuf River. The Tribes insist that local, state, and federal environmental reviews must be completed before the project can advance, emphasizing that economic interests should not compromise the people, lands, and waters.
An appeal hearing for the project is scheduled to take place before the Pocatello City Council on July 16, where the Tribes plan to continue advocating for data-driven decision-making and environmental stewardship.