This post introduces InterLab, a toolkit for experiments with multi-agent interaction. We plan to release more posts on the overall project, technical details, design considerations, and concrete research projects and ideas over the next few weeks to months. This post focuses on the motivation behind the project and touches upon...
A series of interactive visualisations of small-scale experiments to generate intuitions for the question: "Are sparse models more interpretable? If so, why?" Assumptions and motivation * Understanding interpretability may help AI alignment directly (e.g. recursive approaches, short/mid-term value; see here) or indirectly by supporting other directions (mechanistic transparency, open-source game...
In this post we lay out some ideas around framing interpretability research which we have found quite useful. Our framing is goal-oriented, which we believe is important for making sure interpretability research is meaningful. We also go over a variety of dimensions which we think are useful to consider when...
This post introduces InterLab, a toolkit for experiments with multi-agent interaction. We plan to release more posts on the overall project, technical details, design considerations, and concrete research projects and ideas over the next few weeks to months.
This post focuses on the motivation behind the project and touches upon more high-level considerations; if you want to jump to the implementation itself or want to start experimenting, you can jump directly to the Getting started section, to the InterLab GitHub repo with project overview and further links, or explore the example Google Colab notebook.
The research agenda of ACS is primarily focused on understanding complex interactions of humans and AI agents, both on individual... (read 2259 more words →)
A series of interactive visualisations of small-scale experiments to generate intuitions for the question: "Are sparse models more interpretable? If so, why?"
In this post we lay out some ideas around framing interpretability research which we have found quite useful. Our framing is goal-oriented, which we believe is important for making sure interpretability research is meaningful. We also go over a variety of dimensions which we think are useful to consider when thinking about interpretability research. We wanted to have a shared vocabulary when talking about this kind of research, and found that these ideas helped us communicate effectively.
One of our motivations for having these thoughts and discussions is so we can understand the relevance of interpretability to alignment, and to help us think about which categories or dimensions of interpretability research are important