Can Algorithmic Knowledge about the Self Be Critical?

Knowledge about the self is increasingly mediated by algorithms, processing big data generated by users’ engagement with digital technology. These algorithms portend a new epistemology of the self, a new conception of what humans are. I ask: (1) What is the nature of the new epistemology of the self to which algorithms give rise? and (2) Can this epistemology lead to critical knowledge about the self? To answer these questions, I compare algorithmic knowledge about the self with the psychoanalytic knowledge, an epitome of critical knowledge about the self. Both epistemes share assumptions regarding the inability of the mind and reason to have direct access to the true self, and a methodology aimed at bypassing the mind by accessing performance. While psychoanalytic knowledge was a cultural dominant of self-knowledge in the 20th century, algorithmic knowledge is an emerging cultural dominant of contemporary society, either intentionally (as in the case of the quantified self) or not (as in a plethora of personalized digital interfaces geared to tap users’ feelings, attitudes and desires). While psychoanalytical knowledge is theoretical, assumes a human essence, a teleology of quasi-transcendence, a reflexive mind and intersubjective communication, algorithmic knowledge is intently a-theoretical, assumes no human essence, delegates deduction to the algorithmic black-box and uses machine language, thus undercutting the reflexive and interpretive capacities of subjects. Algorithmic knowledge, I argue, operationalizes and technologizes the notion of performativity, thus also threatening to undercut the critical potentialities of the self. I ponder the possible political ramifications of this move to a new episteme, which transforms the self from a subjective, interpretive and critical project, the horizons of which are expanding human and social freedom into an object to be deciphered and predicted.