Co-Arg: Cogent Argumentation with Crowd Elicitation

TL;DR

Co-Arg is a cognitive assistant that combines analyst expertise, computer reasoning, and crowd wisdom to produce transparent, defendable, and understandable conclusions from complex evidence, improving analytic quality.

Contribution

It introduces Co-Arg, a novel system integrating multiple sources of reasoning and crowd input to enhance analytic transparency and decision quality.

Findings

Enhanced clarity of analytic reasoning

Improved decision defensibility

Effective integration of crowd insights

Abstract

This paper presents Co-Arg, a new type of cognitive assistant to an intelligence analyst that enables the synergistic integration of analyst imagination and expertise, computer knowledge and critical reasoning, and crowd wisdom, to draw defensible and persuasive conclusions from masses of evidence of all types, in a world that is changing all the time. Co-Arg's goal is to improve the quality of the analytic results and enhance their understandability for both experts and novices. The performed analysis is based on a sound and transparent argumentation that links evidence to conclusions in a way that shows very clearly how the conclusions have been reached, what evidence was used and how, what is not known, and what assumptions have been made. The analytic results are presented in a report describes the analytic conclusion and its probability, the main favoring and disfavoring arguments, the justification of the key judgments and assumptions, and the missing information that might increase the accuracy of the solution.