Trauma behind the algorithm: a phenomenological analysis of violent content data work

Abstract One of the promises of artificial intelligence (AI) is that it can automate many roles currently performed by humans. However, in the ethics of AI, increased attention is given to the vast amount of labour required for the development, processing, annotation, and implementation of AI. This hidden employment (or ‘ghost work’) is invisible because of the precarious nature of these jobs, poor working conditions, and the social and economic burdens on employees. For example, to ensure AI does not create undesirable content and that social media platforms do not host it, human data annotators and content moderators (violent content data workers–VCDWs) must read, watch, and listen to content containing torture, rape, bestiality, child sexual abuse, and murder. Through phenomenological analysis, this paper demonstrates that this work has deeply traumatic effects on the affectivity, embodiment, and intersubjectivity of VCDWs. While several other professions (e.g., law enforcement officers, war journalists, and medical professionals) must view violent content, the duration, velocity, and accumulation of exposure to violent images in VCDWs is unprecedented. The outcome of this is trauma from being unable to decipher the ontological status of the content, compassion fatigue due to helplessness to help those suffering, and a myriad of physical, psychological, and interrelation problems for VCDWs. This paper exposes a profession that is systematically concealed, buried under NDAs, outsourced to the Global South, and laundered through ethics-washing and ‘responsible AI’ branding.