Saif M. Khan is a Distinguished Technology Fellow at the Institute for Progress (IFP). He previously held senior technology-policy roles across the executive branch and Congress, and his published work concentrates on semiconductor export controls, US–China technology competition, and the governance of automated AI research and development (Source: ifp.org).
Background
Khan served as Counselor for Critical and Emerging Technologies to the Secretary of Commerce, acting as the Secretary's principal advisor and coordinator on AI policy. Earlier he served in the White House as Director for Technology and National Security at the National Security Council, where his portfolio covered semiconductor, AI and quantum information technology policy, and as a senior advisor to the US House Select Committee on the Chinese Communist Party (Source: ifp.org).
His academic and research affiliations include a visiting professorship of the practice at the University of Maryland Applied Research Laboratory for Intelligence and Security and a research fellowship at Georgetown University's Center for Security and Emerging Technology, where his research focused on AI policy. He has testified before Congress multiple times on AI, semiconductors and China policy. Before entering policy he practised as an intellectual-property lawyer in the technology industry. He holds a J.D. from the Ohio State University and a B.S. and M.A. in physics from Wayne State University (Source: ifp.org; cset.georgetown.edu).
Export controls and chip policy
At IFP, Khan has co-authored a series of assessments of whether specific NVIDIA accelerators should be exportable to China. "Should the US Sell Blackwell Chips to China?" (October 2025), written with Georgia Adamson, Tao Burga and Tim Fist, assesses the effects of exporting the B30A; "Should the US Sell Hopper Chips to China?" (December 2025), with Burga, Fist and Adamson, does the same for the H200 and H100 (Source: ifp.org). He also co-authored an October 2025 paper on implementing a coordinated federal programme to secure the US rare-earth supply chain. See Compute Governance and US-China AI Competition: Different Races, Different Metrics.
Automated AI research and pacing
Khan is a co-author, with Fist, Burga, Arthur Tellis, Ben Schifman, Jonah Weinbaum and Olivia Scharfman, of "How Should the US Prepare for Increasingly Automated AI R&D?", published by IFP on August 6, 2026 with 23 recommendations the authors describe as low-regret How Should the US Prepare for Increasingly Automated AI R&D? (IFP, August 2026) (Source: ifp.org).
In a guest post dated August 9, 2026 responding to the July 2026 "Pacing the Frontier" statement, Khan and Fist argued that the United States should take low-regret steps now to prepare for possibly having to pace automated AI research. They identify three risks such a capacity would address — offence-dominant capability uplift, loss of control, and power concentration — propose two ways of making pacing concrete, list seven government preparatory actions, and name the AI Data Center Moratorium Act as the counterproductive default they expect otherwise Should we \"pace\" AI self-improvement? (Fist and Khan, August 2026). See Recursive Self-Improvement (RSI).
Provenance note: The August 6, 2026 IFP report and the August 9 guest post are queued for foundational ingest; citations here should upgrade to the primary texts once those pages exist.
Relationships
- affiliated-with: Institute for Progress (IFP), Center for Security and Emerging Technology (CSET) (former)
- co-author: Tim Fist
- supports: Recursive Self-Improvement (RSI) (pacing of automated AI R&D), Compute Governance
- related: Pacing the Frontier (statement from employees of frontier AI companies, July 2026), Artificial Intelligence Data Center Moratorium Act, US-China AI Competition: Different Races, Different Metrics