The falling barrier between scientific scholarship and politics represents a looming challenge for our field. A growing number of authors, spanning statistics (Clayton 2020), data science (D’ignazio and Klein 2020), and computational social science (Hu 2021), urge us to give up the pretense of objectivity, impartiality, and neutrality in our work, and instead “embrace a political orientation” (Green 2021). Indeed, technologies are not neutral: they encode particular sets of values and as such shape the world and the people in it (Miller 2021). These authors recognize, correctly, that when mathematical or computational methods are oriented toward social questions, the answers necessarily involve politics. But, the most difficult subsequent questions have been left open. Toward what politics should we orient ourselves, as individuals? How can or should a community of scholars adjudicate when different views emerge? And given that data do not (and should not) speak for themselves, how should we fill the silence?

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