Yapay Zeka Destekli Medya Manipülasyonu: Kamuoyu Farkındalığı, Güven ve Deepfake Teknolojilerini Ele Almada Algılama Çerçevelerinin Rolü

Abstract

Yapay zeka tarafından desteklenen deepfake teknolojisi, son derece gerçekçi ancak uydurma görsel-işitsel içeriklerin oluşturulmasını sağlayarak dijital medyayı dönüştürdü. Deepfake'ler daha karmaşık hale geldikçe, kamuoyunun medyaya olan güvenine ilişkin endişeler artıyor ve yaygın yanlış bilgi çağında etik, politik ve güvenlik zorlukları ortaya çıkıyor. Bu çalışma, yapay zeka aldatma teknolojilerinin; ses klonlama, deepfake videolar ve yüz değiştirmenin, varlıklı Avrupalı ​​yaşlı vatandaşlar (40+) arasında dijital medyaya olan güven üzerindeki etkisini inceliyor. Dijital içerikteki farkındalıklarını, kimlik hırsızlığı deneyimlerini ve güven erozyonunu değerlendiriyor. Karma yöntemli bir yaklaşım, nicel anketleri yapay zeka aracı gösterileriyle birleştirdi. Çeşitli Avrupa ülkelerinden elli bir katılımcı, farkındalığı, güveni ve yapay zeka destekli aldatma deneyimlerini ölçen Facebook, Gmail ve Instagram üzerinden üç anketi tamamladı. Bulgular, deepfake'lere yüksek maruz kalma (%76,5), sık ses klonlama dolandırıcılıkları (%66,7) ve dijital medyaya önemli ölçüde güvensizlik (%86,3) olduğunu gösterdi. İstatistiksel analiz (χ² = 25.548, p < 0.001), yapay zeka farkındalığı, güven ve kimlik hırsızlığı arasında güçlü bağlantılar olduğunu doğruladı. Güvenilirlik analizi (Cronbach alfa = 0.783), iyi iç tutarlılık gösterdi. BioID tespit yazılımı analizi kesin sonuçlar verdi: analiz edilen iki deepfake videonun puanı 0.00053 ve 0.06223 oldu ve bu da sentetik yapılarını doğruladı; gerçek özçekimler ise 0.92363 canlılık puanı alarak gerçekliklerini doğruladı. Sınırlamalar arasında küçük bir örneklem ve coğrafi kısıtlamalar yer alıyor. Çalışma, dijital okuryazarlık programlarına, BioID gibi yapay zeka tespit araçlarına ve yapay zeka kaynaklı manipülasyon risklerini azaltmak için daha güçlü düzenlemelere olan ihtiyacın altını çiziyor.

Keywords

• Yapay Zeka
• Deepfake
• Medya Güven Aşınması
• Dijital Medya Manipülasyonu
• AI tespiti

AI-Driven Media Manipulation: Public Awareness, Trust, and the Role of Detection Frameworks in Addressing Deepfake Technologies

Abstract

This study examines the impact of AI deception technologies; voice cloning, deepfake videos, and face swapping on trust in digital media among affluent European senior citizens (40+). It assesses their awareness, experiences with identity theft, and trust erosion in digital content. A mixed-method approach combined quantitative surveys with AI tool demonstrations. Fifty-one participants from various European countries completed three questionnaires via Facebook, Gmail, and Instagram, measuring awareness, trust, and AI-driven deception experiences. Findings showed high exposure to deepfakes (76.5%), frequent voice cloning scams (66.7%), and significant distrust in digital media (86.3%). Statistical analysis (χ² = 25.548, p < 0.001) confirmed strong links between AI awareness, trust, and identity theft. Reliability analysis (Cronbach’s alpha = 0.783) indicated good internal consistency. BioID detection software analysis yielded definitive results: two analyzed deepfake videos scored 0.00053 and 0.06223, confirming their synthetic nature, while genuine selfies achieved a 0.92363 liveness score, validating their authenticity. Limitations include a small sample and geographic constraints. The study underscores the need for digital literacy programs, AI detection tools like BioID, and stronger regulations to mitigate AI-driven manipulation risks.

Keywords

• Artificial Intelligence
• Deepfakes
• Media Trust Erosion
• Digital Media Manipulation
• AI detection

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