GenAI Mirage: The Impostor Bias and the Deepfake Detection Challenge in the Era of Artificial Illusions



Forensic Science International: Digital Investigation, 2024



Mirko Casu1,2, Luca Guarnera1, Pasquale Caponnetto2, Sebastiano Battiato1
1Department of Mathematics and Computer Science, University of Catania, Italy
2Department of Educational Sciences, Section of Psychology, University of Catania, Italy
mirko.casu@phd.unict.it, luca.guarnera@unict.it, pcapon@unict.it, sebastiano.battiato@unict.it









[RELATED WORKS]





Eight potential sources of bias that could impact forensic decision-making



ABSTRACT


This paper examines the impact of cognitive biases on decision-making in forensics and digital forensics, exploring biases such as confirmation bias, anchoring bias, and hindsight bias. It assesses existing methods to mitigate biases and improve decision-making, introducing the novel "Impostor Bias", which arises as a systematic tendency to question the authenticity of multimedia content, such as audio, images, and videos, often assuming they are generated by AI tools. This bias goes beyond evaluators' knowledge levels, as it can lead to erroneous judgments and false accusations, undermining the reliability and credibility of forensic evidence. Impostor Bias stems from an a priori assumption rather than an objective content assessment, and its impact is expected to grow with the increasing realism of AI-generated multimedia products. The paper discusses the potential causes and consequences of Impostor Bias, suggesting strategies for prevention and counteraction. By addressing these topics, this paper aims to provide valuable insights, enhance the objectivity and validity of forensic investigations, and offer recommendations for future research and practical applications to ensure the integrity and reliability of forensic practices.






Download Paper  

Cite:
@inproceedings{casu2023genai,
   title={AI Mirage: The Impostor Bias and the Deepfake Detection Challenge in the Era of Artificial Illusions},
   author={Casu, Mirko and Guarnera, Luca and Caponnetto, Pasquale and Battiato, Sebastiano},
   journal={arXiv preprint arXiv:2312.16220},
   year={2023}
}