News

Stay up to date with the work we’re doing to reduce catastrophic risks from competition for the development of transformative AI. Here you can find posts about our research results, software tools, and community developments. While we love sharing our insights, we always make sure that they aren’t considered information hazards. Therefore, some of our research isn’t publicly available.


    Progress report 2022-H2

    March 16, 2023

    We're delighted to share our sixth progress report summarizing the work we conducted during the second half-year of 2022. The report elaborates on our accomplishments including launching the research software tool we built in collaboration with Robert Trager and releasing the first version of the software we implemented in collaboration with Shahar Avin. Additionally, it introduces two new team members and mentions any changes to our strategy and goals since the previous progress report.


    Progress report 2022-H1

    December 31, 2022

    We're excited to introduce our fifth progress report providing an overview of the work we did in the first half-year of 2022. We dedicated almost all of our resources to our collaboration with other AI governance researchers and are happy to report the milestones we achieved together. The progress report also highlights the reasons behind the prioritization of different projects, the roadblocks we encountered, any updates to our community, and additions to our future goals since the previous progress report.


    $83,000 grant awarded to Modeling Cooperation

    December 29, 2022

    We're grateful to announce the continued support from the Survival and Flourishing Fund (SFF). Thanks to the $83,000 grant funded by Jaan Tallinn, we're looking forward to advancing our collaborations with other AI governance academics by building research software tools and conducting research on improving cooperation in competition toward the development of transformative AI.


    Announcing the Safety-Performance Tradeoff web app

    August 4, 2022

    In collaboration with Associate Professor Robert Trager, we've created an interactive web app implementing the Safety-Performance Tradeoff (SPT) model created by him, Paolo Bova, Nicholas Emery-Xu, Eoghan Stafford, and Allan Dafoe. The web app allows other researchers and decision-makers to explore how safety insights could affect the safety choices of competing AI developers. When exploring the models, one can either set the parameters for two different scenarios or choose one of multiple presets. The effects can then be compared graphically and the web app summarizes the key model insights—e.g. explaining how it is possible that an AI safety breakthrough fails to decrease the risks of AI systems.

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    Progress report 2021-H2

    June 18, 2022

    We're happy to share our fourth progress report summarizing our work during the second half-year of 2021. As explained in the strategy section, we primarily focused on building research software tools in collaboration with other AI governance researchers such as Associate Professor Robert Trager and Shahar Avin while also revising and substantially extending our technical report about our evaluation of the Windfall Clause policy. The progress report elaborates on these accomplishments and the roadblocks we encountered and mentions any updates regarding our team members and future goals since our previous progress report.


    $83,000 grant awarded to Modeling Cooperation

    January 2, 2022

    We’re excited to announce that we received funding from the Survival and Flourishing Fund (SFF) for the third time in a row. The $83,000 grant funded by Jaan Tallinn enables us to continue to fund our current team for the entire year of 2022 and even very slightly expand Modeling Cooperation. We’re looking forward to advancing our research and ongoing collaborations—so please reach out to us in case you are interested in discussing how we could work together.


    Progress report 2021-H1

    September 19, 2021

    We’re delighted to introduce our third progress report which provides an overview of the work we conducted in the first half-year of 2021. The report summarizes our accomplishments including authoring a technical report about our evaluation of the Windfall Clause policy and starting a collaboration with Associate Professor Robert Trager to build a web app implementing an AI competition model. It also highlights the roadblocks we encountered as well as any updates to our strategy and future goals since our previous progress report.


    Progress report 2020-H2

    February 12, 2021

    We’re happy to share our second progress report which summarizes the work we’ve been doing during the second half-year of 2020. In addition to elaborating on our accomplishments and roadblocks, the report also reflects any changes to our team, strategy, and future goals since our previous progress report.


    How we build simulations

    January 19, 2021

    While implementing our model, we created a write-up in which we identify three foundational issues with scientific model implementations and describe how we address them: Reliability, composability, and sustainability. In addition to ensuring our model’s reproducibility and accuracy, we hope to provide a starting point for a technological foundation that enables others to create high-quality agent-based models.

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    $74,000 grant awarded to Modeling Cooperation

    December 9, 2020

    We’re proud to announce that we received a $74,000 grant from Jaan Tallinn (via SFF) to continue our research in 2021. Thanks to this contribution, we’re looking forward to further advancing our research on improving cooperation in competition for transformative AI and making computational approaches less of a neglected topic in AI governance.


    Release of the Monte Carlo simulation tool bl.cli

    November 22, 2020

    As part of our agent-based modeling approach, we released version 1.0.0 of bl.cli, a tool to run Monte Carlo simulations of our model. We initially built bl.cli to make it easier for our economists to produce data to quickly compare results of AI competition scenarios under heuristic strategies. bl.cli runs the Monte Carlo simulation and streams the results to a file. It has grown into a tool that allows anyone comfortable with command-line applications to run Monte Carlo simulations of our model and, in the long run, reproduce our results.

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    Progress report 2020-H1

    August 9, 2020

    Wondering what Modeling Cooperation has been up to lately? We’re excited to share our first progress report which focuses on the first half-year of 2020. The report introduces our team members, explains our strategy, elaborates on our accomplishments as well as roadblocks, and discusses our future goals.