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Other literature type . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
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Policy Paper: Perceived and Actual AI Deepfakes: The Case of Sudan

Authors: Eilaf Salaheldeen Ahmed Mohamed;

Policy Paper: Perceived and Actual AI Deepfakes: The Case of Sudan

Abstract

Sudan’s AI deepfake risk currently appears driven more by demand-side vulnerabilities than the volume of AI deepfake content. While AI-generated disinformation in Sudanese feeds remains limited, perceived (alleged) AI deepfakes and general AI skepticism worsen the situation and contribute to general uncertainty in multimedia content. Within the analyzed cases, we found that the prominent stance was distrust driven more by motivated reasoning and contextual reliance than by durable AI detection skills. In practice rejection or acceptance to AI deepfake often reflects belief-driven judgement more than technical assessment. These weak defenses leave the information environment vulnerable to future sophisticated AI deepfake campaigns and risk normalizing truth indifference. Short-term interventions should prioritize modality-agnostic demand-side interventions such as pre-bunking, AI literacy, scaled fact-checks, and tip lines that strengthen public resilience across all forms of disinformation. More technical AI-specific and supply-side interventions can be developed as institutional capacity and technology allow.

Keywords

Sudan, Technology, Conflict Studies & Peacebuilding, Conflict Studies & Peacebuilding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average