
11 - 50 employees
Founded 2014
đ€ Artificial Intelligence
đ§Ź Biotechnology
đ€ Non-profit
đ° $482.5k Grant on 2021-11
Artificial Intelligence âą Biotechnology âą Non-profit
Future of Life Institute (FLI) is a non-profit organization dedicated to steering transformative technologies, such as artificial intelligence and biotechnology, towards benefiting life and minimizing large-scale risks. The Institute focuses on cause areas like artificial intelligence, biotechnology, and nuclear weapons, advocating for policy changes and public awareness to mitigate associated risks. FLI engages in policy advocacy, outreach, grantmaking, and hosting events to discuss safe development and governance of these technologies. It collaborates internationally with entities like the United Nations and the European Union to ensure that powerful technologies are harnessed for positive future outcomes.
đ June 6, 2025
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11 - 50 employees
Founded 2014
đ€ Artificial Intelligence
đ§Ź Biotechnology
đ€ Non-profit
đ° $482.5k Grant on 2021-11
Artificial Intelligence âą Biotechnology âą Non-profit
Future of Life Institute (FLI) is a non-profit organization dedicated to steering transformative technologies, such as artificial intelligence and biotechnology, towards benefiting life and minimizing large-scale risks. The Institute focuses on cause areas like artificial intelligence, biotechnology, and nuclear weapons, advocating for policy changes and public awareness to mitigate associated risks. FLI engages in policy advocacy, outreach, grantmaking, and hosting events to discuss safe development and governance of these technologies. It collaborates internationally with entities like the United Nations and the European Union to ensure that powerful technologies are harnessed for positive future outcomes.
âą Develop techniques for discovering threat models and generating risk pathway analyses that capture societal and sociotechnical dimensions âą Model multi-node risk transformation, amplification, and threshold effects propagating through social systems âą Contribute to the design of robust technical governance frameworks and assessment methodologies for catastrophic risks, including loss-of-control scenarios âą Provide strategic and tactical quality control for the teamâs research, ensuring conceptual soundness and technical accuracy âą Drive or take ownership of original research projects on comprehensive risk management for advanced AI systems, aligned with the team's objectives âą Collaborate across CARMA teams to integrate risk assessment paradigms with other workstreams âą Contribute to technical standards and best practices for the evaluation, risk measurement, and risk thresholding of AI systems âą Craft persuasive communications for key stakeholders on prospective AI risk management
âą 5+ years of experience in AI safety, alignment, and/or governance. We are open to candidates at different levels of seniority who can demonstrate the required depth of expertise. âą Strong understanding of multiple risk modeling approaches (causal modeling, Bayesian networks, systems dynamics, etc.) âą Experience with systemic and sociotechnical modeling of risk propagation âą Excellent analytical thinking with ability to identify subtle flaws in complex arguments âą Strong written and verbal communication skills for technical and non-technical audiences âą Publication record or equivalent demonstrated expertise in relevant areas âą Systems thinking approach with independent intellectual rigor âą Track record of constructive collaboration in fast-paced, intellectually demanding environments âą Comfort with uncertainty and rapidly evolving knowledge landscapes âą Background in complex systems theory, control theory, cybernetics, multi-scale modeling, or dynamical systems âą Work history at AI safety research organizations, technical AI labs, policy institutions, or adjacent risk domains âą Experience with quality assurance processes for technical research âą Ability to model threshold effects, nonlinear dynamics, and emergent properties in sociotechnical systems âą Understanding of international dynamics and power differentials in AI development âą Ability to balance consideration of both acute and aggregate AI risks âą Experience with causal, Bayesian, or semi-quantitative hypergraphs for risk analysis âą Demonstrated methodical yet creative approach to framework development
âą plus good benefits if a U.S. employee
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