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Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective
We observe on three datasets that we can train a model with this loss term to improve explanation consensus on unseen data, and see improved consensus between explainers other than those used in the loss term.
Tensions Between the Proxies of Human Values in AI
Motivated by mitigating potentially harmful impacts of technologies, the AI community has formulated and accepted mathematical definitions for certain pillars of accountability: e. g. privacy, fairness, and model transparency.
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