Equation 1 · Mechanistic Interpretability in 2035: Scenarios and Falsifiers
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Symbol A
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Symbol t
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Whether interpretability evidence becomes admissible for a safety certification is not a third axis; it is what the other two jointly produce, and the joint requirement is a conjunction rather than an average. Write A(t) for the share of a frontier model’s decision-relevant behaviour with a validated, causally checked account — Circuit Tracing’s own figures are the best public anchor for where A(t) sits today [ 2 ] — and S(t) for the share of published interpretability results built on a method that has cleared an agreed, cross-lab benchmark rather than a proxy metric of the kind SAEBench found unreliable [ 10 ] . A regulator or a court asked to accept mechanistic evidence needs both a…
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Whether interpretability evidence becomes admissible for a safety certification is not a third axis; it is what the other two jointly produce, and the joint requirement is a conjunction rather than an average. Write A(t) for the share of a frontier model’s decision-relevant behaviour with a validated, causally checked account — Circuit Tracing’s own figures are the best public anchor for where A(t) sits today [ 2 ] — and S(t) for the share of published interpretability results built on a method that has cleared an agreed, cross-lab benchmark rather than a proxy metric of the kind SAEBench found unreliable [ 10 ] . A regulator or a court asked to accept mechanistic evidence needs both a guarantee about how much of the model the evidence covers and a guarantee that the method itself is not still under live dispute; a high-coverage result from a disputed method and a well-validated result covering a hand-picked sliver of the model fail for different reasons. Admissibility is therefore better modelled as a conjunction of two thresholds than a weighted sum of two moving averages:
Sources cited in the surrounding passage
- [2] Circuit Tracing: Revealing Computational Graphs in Language Models ↗
- [10] SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability ↗
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