AI-Washing'den AI-Booing'e: Yapay Zekâ İddialarının Beklenti Şişmesi, Güven Erozyonu ve Marka Meşruiyeti Üzerindeki Döngüsel Etkisi — Kavramsal Bir Çerçeve
DOI:
https://doi.org/10.5281/zenodo.22795397Anahtar Kelimeler:
AI-Washing, AI-Booing, Expectation Disconfirmation, Trust Erosion, Legitimacy Theory, Social Risk AmplificationÖzet
Yapay zekânın pazarlama pratiğine hızla yerleşmesi, AI-Washing adıyla anılan yeni bir etik sorunu beraberinde getirmiştir. Bazı markalar gerçek yapay zekâ kapasitelerini olduğundan gelişmiş biçimde sunmakta ve bu durum tüketici beklentilerini yapısal olarak şişirmektedir. Elhajjar ve Itani (2025), bu olguyu ilk sistematik kavramsal çerçeveye kavuşturmuş; Ozturkcan ve Bozdag (2025) ise buna karşı gelişen kamuoyu tepkisini — AI-Booing'i — güven döngüsü çerçevesinde ele almıştır. Her iki çalışma da alanın kavramsal temelini atmış; ancak AI-Washing'den kolektif meşruiyet yaptırımına uzanan nedensel zinciri teorik düzeyde modellememiştir. Bu çalışma söz konusu boşluğu kapatmayı amaçlamaktadır. Meşruiyet Teorisi (Suchman, 1995), Beklenti Bozulması Teorisi (Oliver, 1980; Bhattacherjee, 2001), Atıf Teorisi (Weiner, 1985; Kelley, 1973) ve Sosyal Risk Amplifikasyon Çerçevesi'ne (Kasperson ve diğerleri, 1988; 2022) dayanan bu kavramsal çalışmada sekiz aşamalı bir mekanizma modeli önerilmektedir: AI-Washing → Beklenti Şişmesi → Beklenti Bozulması → Atıf Filtresi → Algılanan Aldatma → Güven Erozyonu → AI-Booing → Meşruiyet Kaybı → Marka Sonuçları. Çalışmanın özgün katkıları arasında AI-Washing'den kolektif meşruiyet yaptırımına uzanan zinciri teorize eden ilk bütünleşik model, Atıf Teorisi ile Beklenti Bozulması Teorisi entegrasyonuyla kurulan Algılanan Aldatma halkası ve bireysel güven erozyonunu kolektif AI-Booing'e taşıyan Sosyal Risk Amplifikasyon mekanizması yer almaktadır.
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