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Articles by McKenna Fitzgerald
Evaluating Oversight Robustness with Incentivized Reward Hacking — LessWrong
This work was supported by the Effective Ventures Foundation USA through their EA Funds program. It was started as part of the MATS (ML Alignment and Theory Scholars) program, with mentorship from Julian Michael and research management by McKenna Fitzgerald. Code for this project is available on GitHub. Explore samples from the different training runs at our interactive website.
Talent Needs of Technical AI Safety Teams — LessWrong
Co-Authors: @yams, @Carson Jones, @McKennaFitzgerald, @Ryan Kidd MATS tracks the evolving landscape of AI safety to ensure that our program continues to meet the talent needs of safety teams. As the field has grown, it’s become increasingly necessary to adopt a more formal approach to this monitoring, since relying on a few individuals to intuitively understand the dynamics of such a vast ecosystem could lead to significant missteps.
Talent Needs in Technical AI Safety — LessWrong
Co-Authors: William Brewer @Carson Jones, @McKennaFitzgerald, @Ryan Kidd MATS tracks the evolving landscape of AI safety to ensure that our program continues to meet the talent needs of safety orgs. As the field has grown, it’s become increasingly necessary to adopt a more formal approach to this monitoring, since relying on a few individuals to intuitively understand the dynamics of such a vast ecosystem could lead to significant missteps.
MATS Winter 2023-24 Retrospective — LessWrong
Co-Authors: @Rocket, @Ryan Kidd, @LauraVaughan, @McKennaFitzgerald, @Christian Smith, @Juan Gil, @Henry Sleight The ML Alignment & Theory Scholars program (MATS) is an education and research mentorship program for researchers entering the field of AI safety. This winter, we held the fifth iteration of the MATS program, in which 63 scholars received mentorship from 20 research mentors.
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