Deepfake in Kenyan Media Landscape: Assessing Awareness, Detection Capacity, and Training Needs among Communication Practitioners

Abstract

This study sought to examine deepfake awareness, detection capacity, and training needs among media and communication practitioners in the Kenyan media landscape. The objectives were: to assess the level of awareness of deepfake technology among practitioners; to evaluate their ability to identify deepfakes; to investigate existing training programmes and institutional frameworks aimed at combating deepfakes in Kenyan media houses and communication agencies; and to recommend strategies for capacity building and policy formulation in response to the growing threat of AI-generated misinformation. The study was guided by the Technology Acceptance Model (TAM), which was used to explore awareness, detection capabilities, and training needs related to deepfake technology. Additionally, the Media Literacy Theory (MLT) informed the examination of the skills, knowledge, and attitudes required to critically evaluate media content. A quantitative descriptive survey design was employed to collect data from media and communication practitioners across Kenyan media houses and agencies. Purposive sampling was used to target individuals working in media, public relations, or communication roles, while stratified sampling enabled comparisons across different media platforms, including print, radio, television, and online outlets. Data analysis revealed that a majority of respondents demonstrated low levels of awareness regarding deepfake technology and had limited capacity to detect or respond effectively to such AI-generated content. Furthermore, the findings highlighted a significant gap in professional development, most practitioners reporting a lack of relevant training or institutional support to equip them with the skills and frameworks necessary to address the deepfake challenge. The study recommends that media practitioners undergo mandatory training on deepfake awareness and detection. Additionally, media institutions should develop and implement clear frameworks and policies to guide the identification and management of AI-generated misinformation.