Constructing What Counts as Human at Work: Enigma, Emotion, and Error in Connective Labor

Abstract

The rationalization of human life in work, feeling, and relationships is amplified by artificial intelligence (AI), apps and automation, challenging interpersonal workers not only in how and whether they do their work, but also how they understand themselves as human. Given these trends, how do interpersonal workers interpret the humanness of their work? To answer this question, I focus on the interactive service work I call “connective labor,” relying on 80+ in-depth interviews and 300+ hours of ethnographic observations with teachers, therapists and primary care physicians in the San Francisco Bay Area and mid-Atlantic United States, as well as with less advantaged practitioners such as sex workers, hairdressers, and home health care aides. I found that these interpersonal workers differentiated themselves from AI, automated agents, and robots in three ways: (1) by describing and defending their work as not rote, (2) taking pains to prove that they were not robots, and (3) justifying their judgments as safe, unique, and worthwhile. Much of their case rested on the unpredictability of humans, in terms of feelings, secrets, and mistakes. These findings have implications for race, class, and gender inequality, as advantage shaped how people were able to demand, perform, or experience their humanness in the ways that the proliferation of algorithmic technologies made salient.