On the US AI Safety Institute: And the role of evaluations in AI governance

Hyperdimensional

On the first day of the Trump Administration, the White House’s Office of Personnel Management (OPM) issued a memo that suggested federal agencies consider firing so-called probationary employees. Despite the name, this is not a designation for employees who are in some kind of trouble. Instead, it refers to a “probation” period that applies to newly hired career civil servants, employees who have been transferred between agencies, and sometimes even employees who have been promoted into management roles. These employees are much easier to fire than most federal employees, so they were a natural target for the Trump Administration’s cost-cutting initiatives.

Because probationary employees are disproportionately likely to be young and focused on more recent government priorities (like AI), the move had unintended consequences. The Trump Administration has since updated the OPM memo to add a paragraph clarifying that they are not directing agencies to fire probationary staff (the first link in this article is the original memo, if you would like to compare).

While the memo was a disruption for many federal agencies, it would have been an existential threat to the US AI Safety Institute, virtually all of whose staff are probationary employees. The threat did not come to fruition, but the whole affair gave me, and I suspect others in Washington, an opportunity to ponder the future of the US AI Safety Institute (AISI) under the Trump Administration.

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