HORSE 2016: Dissenting viewpoints?

The deadline has now passed for abstract submissions to HORSE 2016, but among those submitted I am disappointed to see that there are no “dissenting viewpoints.” There are definitely applications of machine learning for which it is not at all important to know what has been learned, or to verify that what has been learned is “relevant” to the task at hand. In such cases, a concern of “horses” would be distracting. Or maybe, the concern about “horses” is misplaced entirely with respect to the aims of machine learning, or artificial intelligence more broadly.

Perhaps I can elicit a contribution that might provide such viewpoints?

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