Calculating Cognitive Augmentation, A Case Study

TL;DR

This paper discusses a case study on cognitive augmentation, demonstrating significant improvements in accuracy and precision when humans collaborate with AI, and proposes new metrics for measuring such augmentation.

Contribution

It introduces formal metrics for cognitive augmentation and provides empirical evidence of their effectiveness through a detailed case study.

Findings

74% increase in cognitive accuracy

27% increase in cognitive precision

Proposes standard metrics for cognitive augmentation measurement

Abstract

We are entering an era in which humans will increasingly work in partnership and collaboration with artificially intelligent entities. For millennia, tools have augmented human physical and mental performance but in the coming era of cognitive systems, human cognitive performance will be augmented. We are only just now beginning to define the fundamental concepts and metrics to describe, characterize, and measure augmented and collaborative cognition. In this paper, the results of a cognitive augmentation experiment are discussed and we calculate the increase in cognitive accuracy and cognitive precision. In the case study, cognitively augmented problem solvers show an increase of 74% in cognitive accuracy (the ability to synthesize desired answers) and a 27% increase in cognitive precision (the ability to synthesize only desired answers). We offer a formal treatment of the case study results and propose cognitive accuracy and cognitive precision as standard metrics to describe and measure human cognitive augmentation.