Cognitive Science of Augmented Intelligence

Abstract

Cognitive science has been traditionally organized around the individual as the basic unit of cognition. Despite developments in areas such as communication, human–machine interaction, group behavior, and community organization, the individual‐centric approach heavily dominates both cognitive research and its application. A promising direction for cognitive science is the study of augmented intelligence, or the way social and technological systems interact with and extend individual cognition. The cognitive science of augmented intelligence holds promise in helping society tackle major real‐world challenges that can only be discovered and solved by teams made of individuals and machines with complementary skills who can productively collaborate with each other.

Against naïve induction from experimental data

“…Most areas of social and behavioral sciences use experimental manipulations and outcomes to measure unobservable constructs. Social and behavioral scientists in most domains are still engaged in iterative refinement of the experimental paradigms and dimensions of the design space that will best measure these constructs (Dubova & Goldstone, 2023). For instance, while a plethora of paradigmsincluding the multisource interference task, the task switching paradigm, and the N-back taskare utilized for the study of mental effort, there is little agreement about which experimental manipulations evoke mentally effortful processes, let alone how these manipulations would be combined into an integrative experiment (Bustamante et al, 2022;Koch, Poljac, Müller, & Kiesel, 2018;Kool, McGuire, Rosen, & Botvinick, 2010;Shenhav et al, 2017;Westbrook & Braver, 2015).…”

Developmental Sequences Constrain Models of the Mind

“…Researchers in psychology and neuroscience aim to find analytic categories, analogous to the concept of "element" in chemistry or "species" in biology, to facilitate our understanding of cognition, emotion, and behavior. However, arriving at the right categories in any science is challenging because research is necessarily concept laden, i.e., formulated using the very concepts that may turn out to be questionable (Dubova & Goldstone, 2023). Additionally, in cognitive science, we are uncertain about whether we are aiming to characterize the mind and brain as composed of distinct modules or as overlapping constructs instantiated in large neural networks with considerable overlap as well as points of difference.…”

Disembodied AI and the limits to machine understanding of students' embodied interactions

“…Given dAI limitations, alternatives are needed to manage the complexities of embodied interactions while still offering time-sensitive, human-centered interpretations and accountable decision-making. The emergence of augmented intelligence systems (AISs; Dubova et al, 2022) in areas such as healthcare with high-levels of personal interactions (Crigger et al, 2022) and need for trust ([HLEG-AI] High-Level Expert Group on Artificial Intelligence, 2019) offer promising avenues for education. One exemplar is detector-driven interviewing (DDI) methods.…”