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Birgit Maria Kemphues (2025) — Trust engineering in Gulf government communication

Original study
Practitioner
Publisher
Dr. Birgit Maria Kemphues
Vendor interest:
Low
Sample:
45 GCC government communication case studies; sentiment analysis of Arabic-language engagement on Twitter, WhatsApp, and Instagram; interviews with 18 officials from AI councils and digital transformation units; testing on 3 pilot platforms.
Methodology
Not disclosed
Geography
MENA
Data period
01.01.2020 – 31.12.2025
Published
2025

Summary:

This piece looks at how Gulf governments have reshaped citizen communication as AI spreads across public services, focusing on “trust engineering”: designing digital services and messaging to make people feel confident, understood, and willing to use them.

Written and self-published by Dr. Birgit Maria Kemphues, it argues that communication style matters as much as technical performance and explores how trust engineering could be applied in GCC platforms.

The research is presented as mixed-methods but described only loosely: 45 GCC communication case studies, sentiment analysis of Arabic engagement on Twitter/WhatsApp/Instagram, interviews with 18 officials, OECD/UN benchmarking, and a model tested on three pilots (Dubai Now, Qatar AI Legal Assistant, Saudi Digital ID). Sampling, measures, and analysis steps are largely unclear.

Reported results claim emotionally tuned AI interfaces raised satisfaction by 26%, and that tone mattered more for trust than speed.

It also suggests women responded more to empathy cues, while men prioritized predictability.

Case examples cite adoption and trust gains in Dubai, Qatar, and Saudi platforms after calmer language, emotion recognition, or tone matching, and argue that culturally local signals, respectful formality, and explainable AI can boost trust.

Big caveat: it reads more like a practitioner concept paper than a fully documented study. Methods aren’t detailed enough to evaluate, and several strong percentage claims appear without tables, uncertainty ranges, or clear sourcing — so the numbers should be treated cautiously.

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