Deepfake Advertising and Social Engineering: Exploring Trust, Manipulation, and Consumer Protection in AI-Generated Content
Explore the intersection of deepfake advertising and social engineering, focusing on trust, manipulation, and consumer protection in AI-generated content. Discover innovative research topic ideas that address the challenges and implications of trust in advertising.
Realyn Manalo
5/27/20252 min read
In an era where digital authenticity is increasingly under scrutiny, deepfake technology has emerged as both a disruptive innovation and a deceptive threat. These AI-generated media forms—capable of imitating real people with uncanny precision—have reshaped how information is consumed, trusted, and spread online. In marketing and social engineering contexts, deepfakes now enable hyper-personalized yet potentially manipulative campaigns that challenge the very fabric of consumer perception and psychological safety. This study investigates how deepfakes are influencing public trust, consumer behavior, and digital ethics, with a focus on the evolving interplay between AI manipulation, media credibility, and regulatory readiness.
Who Can Use These Topics
This research is ideal for students and professionals pursuing the following courses or strands:
College Programs:
BSBA Marketing Management
BS Psychology
BS Information Technology
BA Communication
BS Criminology
Senior High School Strands:
Humanities and Social Sciences (HUMSS)
TVL-ICT
General Academic Strand (GAS)
Why This Topic Needs Research
While current studies provide valuable insight, major research gaps still exist:
Limited evaluation of behavioral outcomes: Prior research demonstrated the psychological manipulation risk of deepfakes, but few studies assessed how combined interventions—like AI detection tools and user education—can mitigate these effects across diverse digital populations (Blake, 2025).
Lack of cultural-context validation: Deepfake perception studies have been largely Western-centric. There is minimal research on how users in different cultural contexts, such as Southeast Asia, emotionally and behaviorally respond to AI-generated content (Denslinger, 2025).
Absence of real-world advertising data: While voice-based and video deepfakes have been shown to influence trust in simulations, their effect on actual consumer decisions in commercial platforms remains underexplored (Schanke et al., 2024).
Unmeasured long-term effects of content exposure: Deepfake advertising and entertainment may seem persuasive short-term, but no longitudinal study has yet examined their impact on cognitive dissonance, memory, or emotional resilience over time (Debroy & Bhargavi, 2024).
No universal metric for ethical AI labeling: Although ethical labeling is widely proposed, there is no standardized system that assesses its effectiveness in preserving trust and clarifying content manipulation in AI-driven marketing (Pramod et al., 2025).
Feasibility & Challenges by Target Group
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References
Blake, H. (2025). AI-Powered Social Engineering: Understanding the Role of Deepfake Technology in Exploiting Human Trust.
Debroy, O., & Bhargavi, D. (2024). Psycho-social Impact of Deepfake Content in Entertainment Media. Monthly, Peer-Reviewed, Refereed, Indexed Journal with IC Value, 86(87), 10.
Denslinger, A. T. (2025). Deceptive Authenticity: Consumer Perceptions of AI-Generated Deepfake Advertising and the Impact on Consumer Behavior (Doctoral dissertation, Capitol Technology University).
Pramod, D., Patil, K. P., & Bharathi S, V. (2025). Is it really unreal? A two-theory approach on the impact of deepfakes technology on the protection motivation of consumers. Cogent Business & Management, 12(1), 2461239.
Schanke, S., Burtch, G., & Ray, G. (2024). Digital Lyrebirds: Experimental Evidence That Voice-Based Deep Fakes Influence Trust. Management Science.