Econ PhD Candidate @berkeleyecon | Non-Resident Fellow @IFP | PD Soros Fellow

Berkeley, CA
Joined August 2018
Patrick Collard retweeted
Big new IFP report from @GeorgiaCAdamson, @KonstantinPilz, and me on the US-China AI competition. We spent the last 6 months digging into how Chinese AI companies’ access to compute and distillation of American models translate into the current US-China capabilities gap. The result is a 23k-word research report, including an interactive analytical model that visualizes changes in the US AI lead under different policy interventions. Our findings: 1. The US AI lead over China is currently only around 6 months. 2. The US could roughly double this lead, to over a year, using authorities already available to the federal government. 3. On chips: China’s access to AI chips will roughly double over the next year, with chips housed in data centers overseas accounting for roughly half of China’s 2027 compute. 4. On distillation: the current ~16x US training compute advantage would normally yield a 13-month lead. But we estimate adversarial distillation halves this to around 6.5 months. 5. Increasing the lead would have some obvious benefits: - Give the US broadly a greater cyberdefensive advantage against Chinese threat actors. - Give US AI companies breathing room to spend more R&D resources on making their systems safer and more secure, without fear of being overtaken by less safety-conscious Chinese competitors. 6. Provide the US government more leverage in negotiations with China about the future of AI. 7. The two most important interventions are: - For BIS: Create a new end-use control to restrict China’s remote access to training clusters abroad — China’s largest and fastest-growing source of frontier-scale compute. - For DOJ/FTC: Create a narrow safe harbor to allow US companies to coordinate on countering Chinese adversarial distillation. 8. Both interventions (and all the others we discuss in the report) are things the federal government could do today. 9. To estimate the effects of each policy intervention, we model the US lead as a function of its compute advantage over China and China’s ability to adversarially distill the capabilities of the US frontier. 10. The model makes many simplifying assumptions, but provides a useful way to assess and rank the impact of different policy interventions at a high level. Read the full report here: ifp.org/how-to-increase-amer…
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Patrick Collard retweeted
We are on the cusp of a wave of new therapies for some of the worst diseases. But the world won’t benefit unless the US fixes its drug regulatory system. My new essay for @nytimes, on how slow clinical trials are now the biggest obstacle to curing cancer. nytimes.com/2026/09/04/opini… - I interviewed dozens of researchers, especially oncologists at leading U.S. centers. A striking consensus emerged: science is no longer the main bottleneck to new cancer drugs. It is our ability to test discoveries in patients through clinical trials. - The cost of starting a Phase 1 trial in America has roughly doubled over the past decade. As a result, companies increasingly take early trials abroad: Australia’s Phase 1 trial volume has nearly doubled in a decade, driven mainly by U.S. companies. - Unfortunately, the underlying incentives are badly asymmetric: Institutions can be blamed for harms caused by moving too fast, but almost no one is blamed when patients deteriorate during avoidable delays. One doctor called the emerging system “ritualized safety over actual risk assessment.” Or as, @DavidHongMD put it: "We often forget that the biggest risk is the cancer itself." - This problem is becoming more urgent because medicine itself is changing. Sequencing, biological engineering and A.I. make increasingly personalized therapies possible. But our regulatory system was mostly built for standardized drugs tested in large populations. - @sytse, the co-founder of GitLab, shows what personalized medicine can achieve: after relapsed osteosarcoma and being told there were no options left, he pursued a highly individualized approach and has now been cancer-free for a year. But doing so required extraordinary resources and regulatory expertise. - Pierce Ogden’s father was less lucky. After molecular analysis identified a drug that might target his glioblastoma, the manufacturer agreed to provide it. But administrative barriers delayed access until it was too late. “My dad was ready to try anything,” Pierce told me. “But the system is paternalistic.” - The A.I. revolution is making this bottleneck more important, not less. A.I. relies on relevant data. Information from early-stage trials could compound with A.I. tools to achieve truly revolutionary medicines. Without the data, this is far less likely to happen. - Another important shift is that innovation increasingly comes from academic labs and small biotech companies rather than Big Pharma. These small companies find it far harder to unable to absorb delays and regulatory barriers. - Apart from cancer, China is the biggest winner from America's outdated medical regulations. China has a much faster trial system, with testing often starting a full year earlier. This allows Chinese pharmaceutical companies to experiment and improve medicines while American companies play with mice. Today, half of all drugs licensed by major pharmaceutical companies originate there, up from less than 5 percent only a decade ago. - But we don't need to copy China. The best model is Australia: lots of on-site scientific and ethics reviews, and requirements that are proportionate to small, early-stage trials. Phase 1 studies there begin roughly 6–12 months faster, without any notable increases in adverse safety events. - Operation TrialBlazer, a 2026 HHS initiative is a good start in this direction, but we need legislative action by Congress to truly make Phase I trials faster and more efficient! I want to thank everyone who helped me with this article: everyone I interviewed and the amazing editors at the Times. This is the result of a months long journey of extensive interviews and research. Special thanks go to those who came on the record. One of the features of the system is an atmosphere of fear, where practitioners are afraid to publicly come out and explain these issues. So anyone who does is a hero in my book!
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Patrick Collard retweeted
Today I’m launching the Center for Technology & Statecraft (CTS), an initiative inspired by the lessons I learned first as a policy researcher and later in the White House. I'm an optimist about technology. Institutions adapt to disruptions — whether the industrial revolution, computing, the internet — through competition, self-correction, and iteration, and we mostly figure it out in the long run. But we've never had to adapt to a technology that is both this transformative and developing this fast. AI capabilities continue to scale rapidly with no sign of slowing, and it's a full-time job just to keep up with model releases. I worry policy will stay reactive right up until we face immense disruptions — including basic challenges to human agency and relevance in a world of powerful AI. Even still, I believe policy can steer this transition, but only with foresight and the right information. CTS aims to provide just that. Our two initial policy focus areas: 1) How policy can shape virtual and physical automation over the next decade as we reimagine the social contract in light of advanced AI. 2) How to manage long-term strategic US-China AI competition while ensuring stability. These focus areas will build on a deep model of the AI value chain, from chipmaking tools, to the compute, algorithms, and data that make AI, to the tokens, agents and robots that affect the world. For more on our worldview and research philosophy, read techstatecraft.org/launch. I’ve seen firsthand how technical, forward-looking research can inform policy if it’s ready for the policy window. After a decade as an IP and tech lawyer, I joined a think tank, CSET, in 2019 to study AI chips, their supply chains, and AI policy. This was three years before ChatGPT, so these weren't seen as urgent topics at the time. Soon after, AI quickly became an increasingly salient policy issue. From 2021–2025 I served in the White House NSC and the Commerce Department and put new policy ideas into practice (alongside many brilliant colleagues). One goal of CTS is to scale this kind of experience to a whole team: @KonstantinPilz @nchlsbrwn @amelia__michael @mary_clare_m already bring a wealth of technical and policy expertise and we’ll continue to grow to tackle an ambitious research agenda. We're thrilled to be supported by and affiliated with @IFP, and grateful to the advisors and colleagues who helped get CTS off the ground, including @ohlennart, @fiiiiiist, @AlecStapp, and @calebwatney. Our first major reports will launch soon. You can follow us at @techstatecraft.
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Patrick Collard retweeted
OpenAI, Anthropic, and >1,300 employees at all the major AI companies think the US government should prepare to “pace” automated AI R&D. The problem: “pacing” is pretty vague, and could be pretty bad. To fix this, we pulled our team together and developed 23 low-regret policy ideas to understand and manage the risks of automated AI R&D. Here they are: 1. Frontier AI companies and relevant industry bodies should publicly share information relevant to trends and risks in AI R&D automation 2. Congress should legislate transparency about automated AI R&D risk management, incident reporting, whistleblower protections, and model behavior specifications 3. Congress should resource the Center for AI Standards and Innovation (CAISI) with a budget of at least $84 million per year and empower it to directly advise senior government officials and frontier AI companies 4. The White House should set clear roles and responsibilities of US government agencies to increase specialization across AI policy 5. Intelligence agencies should improve their collection and analysis on foreign AI development and counter threats targeting US AI companies 6. CAISI should develop guidelines for managing the risks of rapid AI capability improvement 7. CAISI should co-lead an AI Verification Consortium (AIVEC) with industry to prototype and deploy verification technologies 8. AIVEC should coordinate the creation of AI hardware testbeds and make them available to government, industry, and nonprofit partners 9. AIVEC should launch philanthropically funded prize competitions for AI verification headed by CAISI 10. AIVEC should coordinate the construction of a fully verifiable data center 11. DARPA and the NSF should set up AI verification R&D programs 12. Intelligence agencies should develop and operationalize unilateral means of AI compute monitoring 13. NSA, CAISI, CISA, and ONCD should further invest in cybersecurity resilience 14. Congress, OSTP, and the CDC should invest in biosecurity resilience 15. Congress and the Bureau of Industry and Security (BIS) should strengthen controls on US and allied semiconductor manufacturing equipment 16. Congress and BIS should close gaps in AI chip controls 17. The Federal Trade Commission (FTC), Department of Justice (DOJ), BIS, CAISI, and Congress should help industry counter adversarial distillation of US AI model capabilities 18. BIS should maintain visibility into sales of US chips 19. DOW, the IC, CAISI, and relevant Federally Funded Research and Development Centers (FFRDCs) should establish consensus security guidelines for protecting model weights from theft and prototype them in a government facility 20. Congress should ensure the US has sufficient electrical capacity to sustain AI leadership 21. Congress should ensure data centers can be constructed in America 22. The US government should use its bilateral AI dialogue with China to jointly develop guidelines for managing risks from rapid AI capability growth and prepare verification measures 23. Countries with national AI institutes should collaborate on automated AI R&D risk management guidelines and technical capacity for AI verification You can read an intro to the report over at @Noahpinion’s Substack: noahpinion.blog/p/should-we-… And read the full report here, which has a bunch more detail on each recommendation: ifp.org/preparing-for-ai-res…
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Patrick Collard retweeted
"We need to run the experiment!" Exciting to hear more about incoming metascience units from @mkratsios47 -- I've been very excited to see this development, see our @IFP piece on metascience units here: ifp.org/science-agencies-nee…
One of the key takeaways in Science: A New Golden Age is meta-science — the science of science itself. We need to rigorously evaluate how we fund and conduct research, run real experiments on mechanisms like fast-track grants, measure what actually works, and course-correct when it doesn’t. Government has rarely done this. That’s changing: we’re standing up meta-science units at places like NIH and NSF so continuous improvement becomes the default.
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Patrick Collard retweeted
Since 2022, @IFP has hosted the Economics of Ideas, Science and Innovation online PhD course. It includes lectures from luminaries of innovation economics like @ChadJonesEcon, @KRoyMyers, @inaganguli, @pierre_azoulay, @Afinetheorem, and others. Until now, the only way to see those lectures was to be an econ PhD student and join the course live. We think the insights and ideas included in this course are so important, though, that this year we recorded the lectures and will be publishing all of them on Macroscience. In our launch essay, @mattsclancy lays out five reasons to study the economics of innovation. Find out what they are, and watch the first lecture - Ben Jones providing a framework for thinking about the economics of ideas - here: macroscience.org/p/five-reas…
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No one likes the H-1B lottery. But what system would be better? To answer this question, I FOIAed the US government to get never-before-seen data on H-1B petitions and modeled what different H-1B reform proposals would actually do. Here’s what I found…🧵
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Patrick Collard retweeted
New op-ed from me in the @WSJ. Why are we still awarding H-1Bs by lottery? 400k+ applications are filed for 85k slots, so companies offering higher pay can lose out to others undercutting Americans. Ditch the lottery, award H-1Bs by salary, and turn it into a growth engine.
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Re-posting this call for applications targeting PhD students and early career researchers (PhDs 2014 or later) doing research on the fiscal and economic effects of three productivity policies: R&D, permitting, and immigration. Applications due at midnight on Thurs January 16.
Attention: PhD students and early-career researchers interested in the fiscal and economic effects of productivity policies -- particularly R&D, immigration, and infrastructure permitting. Consider applying to this @SloanFoundation @nberpubs fellowship: nber.org/graduate-fellowship…
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Patrick Collard retweeted
Congress could dramatically improve the H-1B program with a simple, one-sentence change that could likely pass in a reconciliation bill. Here’s the case… 1. High-skilled immigration is critical if you want America to win. 2. Our immigration system should be a meritocracy that prioritizes talent and hard work. 3. On net, the H-1B program has been positive, but it could be reformed to maximize upside and stop gaming of the system. 4. Currently, if companies employ too much of their workforce on H-1Bs, they are subject to extra rules and requirements, unless they pay $60,000+/year. 5. In 1998, $60k was significant ($116k today) — today, it's far below the average H-1B salary. 6. One sentence changing this floor from $60k to $120k (with automatic increases using CPI or 3x national median income) would transform H-1B usage. 7. Most of the top 20 H-1B filers are outsourcing firms paying relatively low wages — this change would increase their compliance costs dramatically. 8. This change would help prioritize our limited H-1B slots for higher-value work and employers — and likely make it too expensive for companies whose business model is to use H-1Bs to outsource jobs. 9. Finding a change that can pass through reconciliation is key — that way, you only need 50 votes in the Senate. 10. This revision could work because, while it can have a significant budgetary impact, it makes no new policy. It is simply updating a policy Congress enacted into law 26 years ago. 11. Raising the floor would lead to an additional $11+ billion in federal payroll taxes over 10 years (with zero effect on federal spending). 12. There are other reforms that could also improve the H-1B program (like moving away from a lottery system). 13. But this one-sentence change is the simplest, most straightforward improvement that would be eligible for inclusion in a reconciliation bill. 14. Consider it a large downpayment on a better H-1B system.
Replying to @RobertMSterling
Easily fixed by raising the minimum salary significantly and adding a yearly cost for maintaining the H1B, making it materially more expensive to hire from overseas than domestically. I’ve been very clear that the program is broken and needs major reform.
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Update: this fellowship program is accepting applications for a second cohort! Deadline to apply is midnight on Monday, January 5, 2025. Details available here: nber.org/career-resources/ca…
Can we improve how we identify and develop mathematical talent among youth? Thanks to @AgencyFund + @nberpubs, we are supporting five PhD fellows in this area: Ian Calaway, @Econ_Geoff, Salome Aguilar Llanes, Kartikeya Vira, + Iris Vrioni. nber.org/programs-projects/p…
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Patrick Collard retweeted
Today, the window for capped H-1B registrations comes to a close & petitions registered by employers will be in a lottery this coming week. Yet, the H-1B is failing to keep up with the needs of the American STEM ecosystem. Fortunately, there are other tools available! 🧵
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Patrick Collard retweeted
We're doing this again! And like any good franchise, the sequel is bigger than the original. Version 2.0 is a (free) 10-week online course being held this spring, again taught by fantastic scholars. 🧵
Is this you, or someone you know? I have good news. This fall @IFP is hosting a free, 6-week, online course, taught by top scholars in the field! (Link at the end of the thread)
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Patrick Collard retweeted
Next week I'm going to send out a post of PhD job market papers related to innovation. If you're going on the job market this year and want to be included, send me an email! Details here. open.substack.com/pub/mattsc…
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Announcing a short course! ifp.org/economics-of-ideas/ Pierre Azoulay (@pierre_azoulay) Matt Clancy (@mattsclancy) Janet Freilich Ina Ganguli (@inaganguli) Ben Jones (@bfjo) Chad Jones (@ChadJonesEcon) Kyle Myers (@KRoyMyers) John Van Reenen (@johnvanreenen) + me (@heidilwilliams_)
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Re-posting this job opportunity for anyone interested in applying economic policy research to encourage scientific progress, innovation, and economic growth. jobs.80000hours.org/?jobPk=7…
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Patrick Collard retweeted
Huge milestone for our metascience team at @IFP. The leadership at @NSF is committed to using experiments to improve how the agency funds research and innovation. We’re honored to support their work.
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Love you guys. Thanks for celebrating my marriage!!!! And happy birthday Gerry and Pat!!!
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Patrick Collard retweeted
Los quiero eliminados en primera ronda.
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Patrick Collard retweeted
𝗢𝗨𝗥 𝗔𝗫𝗘 🪓 Keeping it in Berkeley where it belongs! #GoBears x #BigGame125
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