Emma McClure

We argue that machine learning algorithms can inflict microaggressions on members of marginalized groups and that recognizing these harms as instances of microaggressions is key to effectively addressing the problem. The concept of microaggression is also illuminated by being studied in algorithmic contexts. We contribute to the microaggression literature by expanding the category of environmental microaggressions and highlighting the unique issues of moral responsibility that arise when we focus on this category. We theorize two kinds of algorithmic microaggression, stereotyping and erasure microaggressions, and argue that corporations are responsible for the microaggressions their algorithms create. As a case study, we look at the problems faced by Google’s autocomplete prediction and at the insufficiency of their solutions. The case study of autocomplete demonstrates our core claim that microaggressions constitute a distinct form of algorithmic bias and that identifying them as such allows us to avoid seeming solutions that recreate the same kinds of harms. Google has a responsibility to make information freely available, without exposing users to degradation. To fulfill its duties to marginalized groups, Google must abandon the fiction of neutral prediction and instead embrace the liberatory power of suggestion.

At first glance, hate speech and microaggressions seem to have little overlap beyond being communicated verbally or in written form. Hate speech seems clearly macro-aggressive: an intentional, obviously harmful act lacking the ambiguity (and plausible deniability) of microaggressions. If we look back at historical discussions of hate speech, however, many of these assumed differences turn out to be points of similarity. The harmfulness of hate speech only became widely acknowledged after a concerted effort by critical race theorists, feminists, and other activists. Before the 1990s, slurs were widely considered socially acceptable behavior: mere jokes that weren’t intended to be harmful. Authors like Richard Delgado, Mari Matsuda, and Charles Lawrence pushed back against this dismissal. In this chapter, I show that their arguments for the serious harmfulness of hate speech prefigure and provide support for current debates about the serious harmfulness of microaggressions. Exploring resonances with the 1980s hate speech debate will allow us to explain why microaggressions fall below the cutoff for legal liability but remain apt targets for moral blame.

Scientists, philosophers, and policymakers disagree about how to define microaggression. Here, we offer a taxonomy of existing definitions, clustering around (a) the psychological motives of perpetrators, (b) the experience of victims, and (c) the functional role of microaggression in oppressive social structures. We consider conceptual and epistemic challenges to each and suggest that progress may come from developing novel hybrid accounts of microaggression, combining empirically tractable features with sensitivity to the testimony of victims.

Microaggressions are seemingly negligible slights that can cause significant damage to frequently targeted members of marginalized groups. Recently, Scott O. Lilienfeld challenged a key platform of the microaggression research project: what’s aggressive about microaggressions? To answer this challenge, Derald Wing Sue, the psychologist who has spearheaded the research on microaggressions, needs to theorize a spectrum of aggression that ranges from intentional assault to unintentional microaggressions. I suggest turning to Bonnie Mann’s “Creepers, Flirts, Heroes and Allies” for inspiration. Building from Mann’s richer theoretical framework will allow Sue to answer Lilienfeld’s objection and defend the legitimacy of the concept, ‘microaggression’.

Many theorists have focused on Wittgenstein’s use of examples, but I argue that examples form only half of his method. Rather than continuing the disjointed style of his Cambridge lectures, Wittgenstein returns to the techniques he employed while teaching elementary school. Philosophical Investigations trains the reader as a math class trains a student—‘by means of examples and by exercises’ (§208). Its numbered passages, carefully arranged, provide a series of demonstrations and practice problems. I guide the reader through one such series, demonstrating how the exercises build upon one another and give us ample opportunity to hone our problem-solving skills. Through careful practice, we learn to pass the test Wittgenstein poses when he claims that something is ‘easy to imagine’ (§19). Whereas other critics have viewed the Investigations as merely a diagnosis of our philosophical delusions, I claim that Wittgenstein also writes a prescription for our disease: Do your exercises.