Poster #89 - A Socio Algorithmic Systems Variant of The Bioecological Systems Theory of Human Development: AI, Big Data, and The New Challenges of Researching Digital Natives

• In Event: Poster Session 08

Abstract

This article attempts to motivate the creation of a human development framework that contends with the socio algorithmic ecology of the modern world and can inform future research. To achieve this, I draw on Socio Technical Theory, Critical Race Digital Studies, and Relational Developmental Systems models as the basis of theorizing the role that AI and machine learning play in the development of human beings. Today's youth – digital natives – are developing in a unique socio historical period in which a new and unique class of objects, predictive technologies, are altering the fabric of their developmental ecologies. As such, I posit that existing frameworks for understanding biological and psychological development should be updated to account for the fact that machine learning and AI directly and indirectly interact with individuals during their most sensitive developmental periods. Further, these socio algorithmic systems are defined by deep inequities across social identity markers such as race/ethnicity, gender, and ability, which poses unique vulnerabilities for marginalized youth. I end the article with an eye toward empirical research framed by this novel theory, which questions developmental scientists should ask, and what methodological considerations should be made.

Author

• Avriel C Epps-Darling, Harvard University
  Presenting Author