most citedMeasuring algorithmic interpretability: A human-learning-based framework and the corresponding cognitive complexity score

2 citations · 2 across the 1 of their papers we have counts for

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cs.AI2022★ 2 cited

Measuring algorithmic interpretability: A human-learning-based framework and the corresponding cognitive complexity score

John P. Lalor, Hong Guo

Algorithmic interpretability is necessary to build trust, ensure fairness, and track accountability. However, there is no existing formal measurement method for algorithmic interpr…