Algorithmic Autonomy in Data-Driven AI
Ge Wang, Roy Pea
TL;DR
The notion of algorithmic autonomy is explored, examining what it means for individuals to have autonomy in the face of the pervasive impact of algorithms on the authors' societies, and highlighting current challenges and directions for future research.
Abstract
In societies increasingly entangled with algorithms, our choices are constantly influenced and shaped by automated systems. This convergence highlights significant concerns for individual autonomy in the age of data-driven AI. It leads to pressing issues such as data-driven segregation, gaps in accountability for algorithmic decisions, and the infringement on essential human rights and values. Through this article, we introduce and explore the concept of algorithmic autonomy, examining what it means for individuals to have autonomy in the face of the pervasive impact of algorithms on our societies. We begin by outlining the data-driven characteristics of AI and its role in diminishing personal autonomy. We then explore the notion of algorithmic autonomy, drawing on existing research. Finally, we address important considerations, highlighting current challenges and directions for future research.