Reliability and faithfulness of post-hoc explanations do not suffice to support claims about how a scientific phenomenon is structured.
Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv:1611.04135)
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
In November 2016 we submitted to arXiv our paper "Automated Inference on Criminality Using Face Images". It generated a great deal of discussions in the Internet and some media outlets. Our work is only intended for pure academic discussions; how it has become a media consumption is a total surprise to us. Although in agreement with our critics on the need and importance of policing AI research for the general good of the society, we are deeply baffled by the ways some of them mispresented our work, in particular the motive and objective of our research.
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2026 1verdicts
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Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models
Reliability and faithfulness of post-hoc explanations do not suffice to support claims about how a scientific phenomenon is structured.