What does this research mean for the field?

A novel AI artifact analyzing solely the acoustic properties of the human voice, without speech recognition, can detect deceptive statements with approximately 82% accuracy while preserving data privacy. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to develop an AI artifact that detects deception in speech during HR recruitment processes.

June 13, 2026Journal of Information Technology

It’s not what you say, but how you say it: Using Artifact Intelligence to Detect Deception in Natural Speech in an HR Recruiting Context

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Authors

HGHeiko Gewald SFStefan Faußer

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Overview

Randomized trial demonstrates detection of deceptive speech in recruitment, indicating improved decision-making in hiring processes.

Key Points

This research aims to develop an AI artifact that detects deception in speech during HR recruitment processes.
Utilized natural language processing (NLP) techniques to analyze human voice patterns.
Designed the artifact to ensure data privacy without speech recognition or storage of identifiable information.
Evaluated the artifact's effectiveness in detecting deception during recruitment interviews.
The model achieved approximately 82% accuracy in detecting deceptive statements.
Integration of the artifact could enhance HR personnel's ability to identify deceptive behaviors.
Findings suggest that AI tools can significantly improve decision-making in organizational contexts.

Cite This Study

Gewald et al. (2026) studied this question.

synapsesocial.com/papers/6a2cf528faef96ed7f05733a https://doi.org/10.1177/02683962261462966

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June 13, 2026Journal of Information Technology

It’s not what you say, but how you say it: Using Artifact Intelligence to Detect Deception in Natural Speech in an HR Recruiting Context

View Full Paper

Ask AI

Bookmark

Authors

HGHeiko Gewald SFStefan Faußer

Discussion

Member takes

Overview

Randomized trial demonstrates detection of deceptive speech in recruitment, indicating improved decision-making in hiring processes.

Key Points

This research aims to develop an AI artifact that detects deception in speech during HR recruitment processes.
Utilized natural language processing (NLP) techniques to analyze human voice patterns.
Designed the artifact to ensure data privacy without speech recognition or storage of identifiable information.
Evaluated the artifact's effectiveness in detecting deception during recruitment interviews.
The model achieved approximately 82% accuracy in detecting deceptive statements.
Integration of the artifact could enhance HR personnel's ability to identify deceptive behaviors.
Findings suggest that AI tools can significantly improve decision-making in organizational contexts.

Cite This Study

Gewald et al. (2026) studied this question.

synapsesocial.com/papers/6a2cf528faef96ed7f05733a https://doi.org/10.1177/02683962261462966

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