Can AI help us identify who the real authors of classic literature?
According to MIT, the answer is yes. In a recent, article they noted how machine learning was used to identify how much a co-author helped fill in the banks for Shakespeare's Henry VIII. They had long suspected that John Fletcher was the individual but couldn't identify what passages he wrote into the play.
Petr Plecháč at the Czech Academy of Sciences in Prague trained the algorithms using plays that Fletcher that corresponded with the time that play was written because "because an author’s literary style can change throughout his or her lifetime, it is important to ensure that all works have the same style".
Based on his analysis, it appears half the play is written by Fletcher.
The experiment is a proof-of-concept that there is a certain linguistic signature to how people author things. In a sense, it means we have a unique pattern when it comes to how we construct sentences. With respect to the experiment run by Dr. Plecháč, the algorithm was able to detect what was written Fletcher because he "often writes ye instead of you, and ’em instead of them. He also tended to add the word sir or still or next to a standard pentameter line to create an extra sixth syllable."
Can this be used within an audit?
A paper co-authored by Dr. Kevin Moffitt of Rutgers University entitled "Identification of Fraudulent Financial Statements Using Linguistic Credibility Analysis" found just that. In the paper, they explained how they used a "decision support system called Agent99 Analyzer" to "test for linguistic differences between fraudulent and non-fraudulent MD&As". The decision support system was configured to identify linguistic cues that are used by "deceivers". The papers cites as examples of how deceivers when they speak "display elevated uncertainty, share fewer details, provide more spatio-temporal details, and use less diverse and less complex language than truthtellers".
The result?
The algorithm had "modest success in classification results demonstrates that linguistic models of deception are potentially useful in discriminating deception and managerial fraud in financial statements".
Results like these are a good indication of how the audit profession can move beyond the traditional audit procedures.
Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else
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