In this paper, I discuss how Facebook's Deepfake Detection Challenge (DFDC) translated deepfakes’ controversial social implications into a technical challenge that rendered unthinkable the political and instead focused on rules and optimalities. I show how Facebook articulated the challenge, the social and cultural biases inherent in the solutions proposed for the competition, and the lack of ethics regarding privacy protection. By crowdsourcing the problem, big tech corporations mobilize free labour, algorithms, and extensive user-generated datasets to produce predictive models for detecting and asserting what is true and what is fake and, consequently, producing new forms of subjectivation.