Metrics for measuring progress are important for better judging where progress has already been made, where it is still lacking and with which pace it is happening. Besides providing insight into the technological landscape, the creation and choice of metrics can also strongly influence the trajectories of technological developments.

In this context, metrics encompass classical indicators of scientific, technological, medical and social progress (e.g., number of papers published, technology readiness levels, quality-adjusted life years saved, gross domestic product), but also more technical metrics for AI progress, i.e., machine learning benchmarks.


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