A Dynamic Logic for Information Evaluation in Intelligence

TL;DR

This paper introduces L(intel), a formal dynamic logic model for evaluating intelligence messages that emphasizes credibility over reliability, aligning with empirical perceptions and improving classification accuracy.

Contribution

It presents a novel dynamic belief revision framework that prioritizes credibility and incorporates source reliability updates for intelligence evaluation.

Findings

L(intel) aligns with empirical perceptions of credibility and reliability.

The model effectively classifies intelligence messages.

Dynamic operators improve credibility assessment accuracy.

Abstract

In the field of human intelligence, officers use an alphanumeric scale, known as the Admiralty System, to rate the credibility of messages and the reliability of their sources (NATO AJP-2.1, 2016). During this evaluation, they are expected to estimate the credibility and reliability dimensions independently of each other (NATO STANAG, 2003). However, empirical results show that officers perceive these dimensions as strongly correlated (Baker et al., 1968). More precisely, they consider credibility as playing the leading role over reliability, the importance of which is only secondary (Samet, 1975). In this paper, we present a formal evaluative procedure, called L(intel), in line with these findings. We adapt dynamic belief revision to make credibility the main dimension of evaluation and introduce dynamic operators to update credibility ratings with the source's reliability. In addition to being empirically sound, we show that L(intel) provides an effective procedure to classify intelligence messages along the descriptive taxonomy presented in Icard (2023).