The Nonverbal Gap: Toward Affective Computer Vision for Safer and More Equitable Online Dating

arXiv cs.AI / 3/31/2026

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Key Points

  • The paper argues that mainstream online dating platforms remove key nonverbal cues (gaze, facial expression, posture, timing), producing a “nonverbal gap” with disproportionate safety risks for women.
  • It frames affective computer vision as both a technical opportunity and a moral responsibility, noting existing CV capabilities (facial action unit detection, gaze estimation, engagement/affect recognition) that could be adapted to dating.
  • The authors propose a fairness-first research agenda spanning real-time discomfort detection, modeling engagement asymmetry between partners, designing consent-aware interactions, and producing longitudinal interaction summaries.
  • They call for purpose-built datasets collected with dyadic consent protocols and fairness evaluations broken down by race, gender identity, neurotype, and cultural background.
  • To prevent surveillance misuse, the paper emphasizes architectural choices such as on-device processing so that affective signals are not repurposed as platform-wide monitoring infrastructure.

Abstract

Online dating has become the dominant way romantic relationships begin, yet current platforms strip the nonverbal cues: gaze, facial expression, body posture, response timing, that humans rely on to signal comfort, disinterest, and consent, creating a communication gap with disproportionate safety consequences for women. We argue that this gap represents both a technical opportunity and a moral responsibility for the computer vision community, which has developed the affective tools, facial action unit detection, gaze estimation, engagement modeling, and multimodal affect recognition, needed to begin addressing it, yet has largely ignored the dating domain as a research context. We propose a fairness-first research agenda organized around four capability areas: real-time discomfort detection, engagement asymmetry modeling between partners, consent-aware interaction design, and longitudinal interaction summarization, each grounded in established CV methodology and motivated by the social psychology of romantic communication. We argue that responsible pursuit of this agenda requires purpose-built datasets collected under dyadic consent protocols, fairness evaluation disaggregated across race, gender identity, neurotype, and cultural background, and architectural commitments to on-device processing that prevent affective data from becoming platform surveillance infrastructure. This vision paper calls on the WICV community, whose members are uniquely positioned to understand both the technical opportunity and the human stakes, to establish online dating safety as a first-class research domain before commercial deployment outpaces ethical deliberation.

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