e.g. In terms of risk. In terms of benefits of sharing. Technical aspects; Supply chain issues (e.g. share plans for nucs, still really hard to get your hands on refined uranium); Offense-defense balance; Both analogies are problematic and have a propensity to mislead, but in different ways. Let’s clarify where each is useful and each problematic.

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Explore RFI from NTIA on risks and benefits of widely available model weights from EO 4.6

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Why is Meta really open-sourcings?: competition and market implication of OS We’ve all heard that open-source is good for competition, and that so much of our technology builds on OS. It is the beating heart of silicon valley. But why does a company want to open-source? It seems counterintuitive. Why sink tons of money into products you give away for free. This is especially counterintuitive in the case of frontier foundation models, where training runs cost in the billions. There are only a ha

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This project would serve as a follow-up to my previous report (below) on structured access for research, essentially adapting/extending it from its current focus on access for research to access for evals & audits. The motivation being that despite my focus on research, a lot of people expressed an interest in implications for evals & audits. While I think there is some meaningful overlap between the two, there are certainly some considerations that seem to be unique to the latter that would be

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Perhaps one of the most important questions that we face is the relative relevance of rational actor theories versus behavioral theories in the domain of AI and International Relations. Empirical findings can sometimes differ dramatically from theoretical expectations, such as in the Ultimatum game. Such differences require us to consider different families of theories. If we empirically find that decision-makers intuitively characterize AI-induced existential risk as an ultimatum game or a sim

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We are likely to soon have personal ‘AI delegates’ (I do not necessarily mean this in the political sense of that word), which will interact with one another on our behalf, in order to further our individual interests. To begin with, such interactions are likely to be quite limited and quite tightly scoped (and thus more easily regulated), but as progress continues, they might become increasingly more general. As an intuition pump, one might imagine ‘Siri on steroids’, capable not only of arrang

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Related to the above, it might be the case that uses of these AI delegates can be better governed if their interactions are conducted through some standardised protocol, in the same way that traffic on the internet conforms to a set of standardised protocols. The question here is something like “what would/should an analogue of the internet protocol suite (TCP/IP) look like for AI agents, and what, if anything could this be useful for?” Examples of the sorts of benefits this might bring include

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Related to the above, I would be interested to know how liability should work in the context of multi-agent settings. If something goes wrong as a product of some phenomena that emerges from multiple AI systems, but is not directly attributable to any one of those AI systems, which developers are/should be liable for that failure? This idea can also be extended to different components of a single AI system, e.g., if one developer provides the training data, another creates the model, another fin

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AI for institutions in some ways flips the AI governance (which includes ‘institutions for AI’) problem. The basic question here is how we might be able to leverage advances in AI to improve our institutions and collective decision-making. This might in turn lead to a virtuous cycle in the governance of emerging technologies, especially those which themselves involve AI, as better integrating governance mechanisms into the technical development of AI models might be a high-leverage way to reach

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See web link. Each section introduces the workstream, briefly outlines the reasons why we are excited about it, and highlights a few select research questions we are investigating. Our workstreams are interconnected, and some projects will fit under multiple workstreams. The bulk of our research is currently concerned with U.S. law, but we also publish some research with a focus on international law.

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See web link. Each section introduces the workstream, briefly outlines the reasons why we are excited about it, and highlights a few select research questions we are investigating. Our workstreams are interconnected, and some projects will fit under multiple workstreams. The bulk of our research is currently concerned with U.S. law, but we also publish some research with a focus on international law.

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See web link. Each section introduces the workstream, briefly outlines the reasons why we are excited about it, and highlights a few select research questions we are investigating. Our workstreams are interconnected, and some projects will fit under multiple workstreams. The bulk of our research is currently concerned with U.S. law, but we also publish some research with a focus on international law.

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See web link. Each section introduces the workstream, briefly outlines the reasons why we are excited about it, and highlights a few select research questions we are investigating. Our workstreams are interconnected, and some projects will fit under multiple workstreams. The bulk of our research is currently concerned with U.S. law, but we also publish some research with a focus on international law.

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See web link. Each section introduces the workstream, briefly outlines the reasons why we are excited about it, and highlights a few select research questions we are investigating. Our workstreams are interconnected, and some projects will fit under multiple workstreams. The bulk of our research is currently concerned with U.S. law, but we also publish some research with a focus on international law.

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See paper

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See paper

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See paper

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See paper

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See paper

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See paper

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See paper

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See paper

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See paper

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See paper

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different jurisdictions, where new bodies or powers might be required, and the tradeoffs of different options.

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See paper

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See paper

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This project explores the impact of US nuclear strategists on nuclear strategy in the early Cold War. What types of experts provided advice on US nuclear strategy? How and in what ways did they affect state policy making on nuclear weapons from 1945 through to the end of the 1950s (and possibly beyond)? How could they have had a larger impact? This project provides a detailed case study to help us understand how and through what pathways technical experts have been able to shape state policymaki

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A model for determining these effects is outlined in Klinova and Korinek (2021), "AI and Shared Prosperity," Proceedings of the AIES '21. Useful resources are also provided by the Partnership on AI's Shared Prosperity Initiative. From an economic perspective, among the greatest challenges that transformative AI may pose are increases in inequality - if advanced AI systems can perform work far more efficiently than humans, workers may no longer be able to earn a living wage, whereas entreprene

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From an economic perspective, among the greatest challenges that transformative AI may pose are increases in inequality - if advanced AI systems can perform work far more efficiently than humans, workers may no longer be able to earn a living wage, whereas entrepreneurs and the owners of corporations may see their incomes rise significantly. Inequality has been rising and been a significant challenge for policymakers for decades. But increases in inequality are not an unavoidable by-product of

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From an economic perspective, among the greatest challenges that transformative AI may pose are increases in inequality - if advanced AI systems can perform work far more efficiently than humans, workers may no longer be able to earn a living wage, whereas entrepreneurs and the owners of corporations may see their incomes rise significantly. Inequality has been rising and been a significant challenge for policymakers for decades. But increases in inequality are not an unavoidable by-product of

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Approaches to studying this question: Review how human-machine interactions affected past military accidents like the Vincennes incident, the Patriot fratricides, etc. One possible data source is the FORUM on Risks to the Public in Computers and Related Systems, a community of computer safety researchers. See, for instance, robust discussion on the Vincennes here. Researchers could also explore how organizations learn from past incidents to reduce the risks of faulty human-machine interactions

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In some regulatory domains, such as environmental standards for cars, has seen a California Effect (see e.g. Ch 8 in Vogel’s 1995 Trading Up), where Californian, more stringent regulation has proliferated across the US. Often, this happens where companies find it cheaper to simply produce one California-compliant product and sell that outside California as well (e.g. due to the cost of maintaining two separate production lines). There is a case to be made that the similar dynamics will be at pla

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In some regulatory domains, such as environmental standards for cars, has seen a California Effect (see e.g. Ch 8 in Vogel’s 1995 Trading Up), where Californian, more stringent regulation has proliferated across the US. Often, this happens where companies find it cheaper to simply produce one California-compliant product and sell that outside California as well (e.g. due to the cost of maintaining two separate production lines). There is a case to be made that the similar dynamics will be at pla

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In some regulatory domains, such as environmental standards for cars, has seen a California Effect (see e.g. Ch 8 in Vogel’s 1995 Trading Up), where Californian, more stringent regulation has proliferated across the US. Often, this happens where companies find it cheaper to simply produce one California-compliant product and sell that outside California as well (e.g. due to the cost of maintaining two separate production lines). There is a case to be made that the similar dynamics will be at pla

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In some regulatory domains, such as environmental standards for cars, has seen a California Effect (see e.g. Ch 8 in Vogel’s 1995 Trading Up), where Californian, more stringent regulation has proliferated across the US. Often, this happens where companies find it cheaper to simply produce one California-compliant product and sell that outside California as well (e.g. due to the cost of maintaining two separate production lines). There is a case to be made that the similar dynamics will be at pla

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Studying this would require finding and reading Chinese-language sources on this topic. It would also involve comparative analysis of the safety cultures of the U.S. and Chinese nuclear communities. This is a tough but hugely important research area. As a program officer for Stanley Center for Peace and Security told me, this "is a really tough research area. There aren’t many NC3 [Nuclear Command and Control and Communications] experts anymore, China is a hard research topic for NC3, and cross

May require Chinese language proficiency to read primary sources

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I think one could make significant progress on these questions just by talking to people who were engaged in (or at least aware of) debates around transformative nanotech in the 1980s or 1990s, including Eric Drexler, Christine Peterson, Eliezer Yudkowsky, and Robin Hanson. It would also be useful to read available histories of nanotechnology and to read essays, news coverage, popular fiction, and mailing list discussions from this period.

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I think one could make significant progress on these questions just by talking to people who were engaged in (or at least aware of) debates around transformative nanotech in the 1980s or 1990s, including Eric Drexler, Christine Peterson, Eliezer Yudkowsky, and Robin Hanson. It would also be useful to read available histories of nanotechnology and to read essays, news coverage, popular fiction, and mailing list discussions from this period.

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I think one could make significant progress on these questions just by talking to people who were engaged in (or at least aware of) debates around transformative nanotech in the 1980s or 1990s, including Eric Drexler, Christine Peterson, Eliezer Yudkowsky, and Robin Hanson. It would also be useful to read available histories of nanotechnology and to read essays, news coverage, popular fiction, and mailing list discussions from this period.

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The project would involve interviewing NeurIPS organisers, both from the 2020 and 2021 committees. For the 2020 conference, the NeurIPS committee introduced a requirement that authors include in their papers a section reflecting upon the broader impact of their work. The idea was to push researchers to consider potential negative societal impacts of AI research (see e.g. Prunkl et al 2021, Ashurst et al 2020, Hecht 2020, Abuhamad & Rheault 2020). For 2021, this requirement is being changed, suc

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The questions could be explored by looking at: Relevant case studies, e.g. the Dot-com Bubble (in the economic literature sometimes referred to as the “Technology Bubble”), the Railway Frenzy, the Bike Boom, the Uranium Bubble. You could also look at cases with long feedback loops, such as perhaps the Great Alpaca Bubble and Tulip Mania. Quantitatively estimating whether there are boom and bust cycles in technology investment by companies, foundations, governments. It should be possible to get

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This research project would explore in detail the systems that exist within synthetic biology, in order to learn lessons for how “structured capability access” (SCA) could be further developed within AI.

It would be beneficial if the researcher had some existing familiarity with biology, but this might not be necessary.

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Notable examples to study include: the Asilomar Conference on Beneficial AI, the Facebook Oversight Board (see Klonick 2020), AI ethics boards (interesting examples include DeepMind's ethics board, Google’s defunct AI advisory board, Microsoft’s AETHER committee), AI ethics principles put out by a huge number of entities, the Partnership on AI, shifts in publication norms (see e.g. Prunkl et al 2021, Partnership on AI 2021, and Shevlane & Dafoe 2020), and companies supporting the AI ethics field

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Notable examples to study include: the Asilomar Conference on Beneficial AI, the Facebook Oversight Board (see Klonick 2020), AI ethics boards (interesting examples include DeepMind's ethics board, Google’s defunct AI advisory board, Microsoft’s AETHER committee), AI ethics principles put out by a huge number of entities, the Partnership on AI, shifts in publication norms (see e.g. Prunkl et al 2021, Partnership on AI 2021, and Shevlane & Dafoe 2020), and companies supporting the AI ethics field

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Notable examples to study include: the Asilomar Conference on Beneficial AI, the Facebook Oversight Board (see Klonick 2020), AI ethics boards (interesting examples include DeepMind's ethics board, Google’s defunct AI advisory board, Microsoft’s AETHER committee), AI ethics principles put out by a huge number of entities, the Partnership on AI, shifts in publication norms (see e.g. Prunkl et al 2021, Partnership on AI 2021, and Shevlane & Dafoe 2020), and companies supporting the AI ethics field

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Notable examples to study include: the Asilomar Conference on Beneficial AI, the Facebook Oversight Board (see Klonick 2020), AI ethics boards (interesting examples include DeepMind's ethics board, Google’s defunct AI advisory board, Microsoft’s AETHER committee), AI ethics principles put out by a huge number of entities, the Partnership on AI, shifts in publication norms (see e.g. Prunkl et al 2021, Partnership on AI 2021, and Shevlane & Dafoe 2020), and companies supporting the AI ethics field

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Notable examples to study include: the Asilomar Conference on Beneficial AI, the Facebook Oversight Board (see Klonick 2020), AI ethics boards (interesting examples include DeepMind's ethics board, Google’s defunct AI advisory board, Microsoft’s AETHER committee), AI ethics principles put out by a huge number of entities, the Partnership on AI, shifts in publication norms (see e.g. Prunkl et al 2021, Partnership on AI 2021, and Shevlane & Dafoe 2020), and companies supporting the AI ethics field

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One approach which might shed light on these questions is to evaluate past cases of emerging industries and trace the path of their evolution to more responsible governance (or else their failure to become responsible). In those cases, did better governance start among firms and then lead to regulation, involve little in the way of self-governance, involve deceptive self-governance (e.g. the tobacco industry), or otherwise fail to achieve responsible governance? Cases should ideally be selected

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One approach which might shed light on these questions is to evaluate past cases of emerging industries and trace the path of their evolution to more responsible governance (or else their failure to become responsible). In those cases, did better governance start among firms and then lead to regulation, involve little in the way of self-governance, involve deceptive self-governance (e.g. the tobacco industry), or otherwise fail to achieve responsible governance? Cases should ideally be selected

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A good place to start might be Imbrie et al 2020 and Imbrie et al 2021.

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A review paper summarizing the state of the literature on strategic-trade theory and related ideas (e.g. “industrial policy”, “high-development theory”). For example, I would like to have a better sense of the magnitudes of the rents that a country can get from having an industrial champion. How much value does the existence of Airbus provide to Europe? How much of modern wealth comes from strategic industries? One estimate puts the commercial aircraft market at roughly $100bn per year (which is

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Forecasting mind reading technologies What, if any, mind reading technologies may be available when? You probably want to think about what the technology can detect, the modality it uses, it’s accuracy, and how invasive the technology is likely to be (e.g. whether it requires implants or the subject to get into an fMRI machine). How easy is it to fool the technology? For example, it’s possible to fool lie detectors; if you know you’re being watched by an emotion recognition system, you can mas

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The potential impact of mind reading technologies Domains that may be affected include: Strategic dynamics and negotiations: Actors becoming more transparent to each other could make it much easier to make credible commitments, causing large changes in the character of negotiations e.g. between firms and between states. Domestic politics: Politicians with incentives or beliefs not approved of by the populous could find it much more difficult to succeed. You could also imagine that these techn

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